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Sora Who? Kling Is the New AI Video Generator Everyone Is Talking About - Decrypt

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Hailing from China, the Kling AI video model is a potential game changer, blasting past mainstays like Pika or RunwayML. Here's what you need to know.

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Kling AI Video Generator Now Available Globally to Take on OpenAI's Sora

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Kling AI Video Generator Now Available Globally to Take on OpenAI’s Sora - Decrypt

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Here’s a look at a new AI video generator that offers multilingual support and impressive features.

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It is biology's most pressing and possibly most confounding question: How did life on Earth emerge some 3.5 billion years ago? Charles Darwin famously speculated that it all began in some "warm little pond"-and it turns out he may have been pretty close to the mark.

Many scientists now believe that primordial hot spots in the ocean floor or in tidal zones, called hydrothermal vents, make the most compelling point of origin for living things. An upwelling of hydrogen-rich alkaline fluids from the vents, which were likely more common on early Earth, could have combined with bicarbonate and carbon-dioxide rich seawater to create excellent conditions for the formation of organic molecules. Recently, scientists, including acclaimed evolutionary biochemist Nick Lane, have shown that amino acids-essential to many biological processes-and primitive cell membranes can form spontaneously around these vents. Others have uncovered some of the world's oldest fossils in areas thought to have been covered in vents long ago. But no one has been able to conjure life from mere chemicals in the lab in any sustainable way.

The findings could point to where else in the cosmos we might have neighbors.

Now scientists at Newcastle University in the United Kingdom say that by imitating conditions of pressure, heat, chemistry, and flow thought to be found near vents on primordial Earth, they have been able to replicate, for the first time, the formation of long-chain carboxylic acids -also known as "fatty" acids. These fatty acids could have formed the primitive membranes essential to the earliest cellular forms of life, or "protocells."

For their study, the scientists tried to "re-create the core elements of what we think the conditions were like," on early Earth, says biogeochemist Jon Telling of the Newcastle team, co-author of the paper. They combined dissolved hydrogen with bicarbonate ions in solution, mixed it with magnetite-an iron oxide associated with hydrothermal vents-and placed it in a pressurized flow reactor they had built for 16 hours. The new study differs from earlier efforts, according to the scientists, because of the pressure and continuous mixing, or "flow," they applied to their solution-and because they looked for their organic molecules not in the liquid solution but on a mineral substrate, the magnetite.

The experiment produced a "spectrum" of organic molecules, including long-chain carboxylic acids. It's these long-chain acids-often called fatty acids because they're a key component of body fat-that could have been key precursors to cell membranes. Clusters of fatty acid molecules naturally align themselves in such a way that they have a water-attracting side and a water-repelling side, just as cell membranes do. These clusters also tend to form spherical double shells that are "very similar to actual living cells," says Telling. Water on the inside stays in and water on the outside stays out.

The scientists kept their materials at a temperature of about 200 degrees Fahrenheit-a few degrees below boiling-similar to the temperature they estimate would have existed around hydrothermal vents 3.5 billion years ago. They also applied 16 to 18 times the pressure found in the Earth's current atmosphere, which they calculated to ensure that sufficient hydrogen took part in the chemical reactions. Hydrogen is mostly unreactive at lower pressures, Telling explains, but is an essential component of many organic molecules, including fatty acids.

The higher pressure turned out to be a key to the results, he says. On the primordial Earth that pressure could have been exerted by the water column in a hydrothermal vent a few hundred feet below the surface of an ocean.

The other key was using the mineral magnetite as a substrate for the chemical reactions they wanted to produce. The team found that most of the organic chemicals-including the fatty acids-formed on the surface of the mineral, which facilitated the reactions without getting consumed by them. Telling says previous researchers seem to have expected the products of any chemical reactions to occur within the solution and had looked there without success.

The findings not only help us understand the origins of life on Earth, but point us to where else in the cosmos we might have neighbors, says Telling. The reactions they simulated in the lab could be occurring, right now, on distant moons in our solar system, he says. Saturn's moon Enceladus and Jupiter's moon Europa are thought to have oceans of liquid water beneath their icy crusts, which may harbor hydrothermal vents, heated from their interiors. "These would be really good places to focus future research, to learn about the chemistry of their oceans," he says.

Saturn's Enceladus emits plumes of liquid water from fractures in its crust and probably has sufficient carbon dioxide to form the essential bicarbonates. And scientists have detected organic molecules, both large and small, in these plumes.

The closer we get to understanding the alchemy of primitive life on Earth, the more we may learn about whether and where we have neighbors in the universe, now or at some point in the future of the cosmos.
Lead image: Honchar Roman / Shutterstock

Tom Metcalfe

Tom Metcalfe is a science journalist based in London, where he writes mainly about space, energy, archaeology, Earth, and the oceans. He has written for Scientific American, National Geographic, Live Science, NBC News, BBC News, and others.

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By imitating early conditions of Earth in the lab, scientists gain new insight into the origin of life.

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Amelia Earhart Plane Wreckage Found, US Exploration Team Says - GreekReporter.com

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Amelia Earhart Plane Wreckage Found, US Exploration Team Says - GreekReporter.com

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A US exploration team believe they have discovered the plane wreckage of Amelia Earhart, the first woman to attempt to fly around the world.

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The Samsung Galaxy Ring has piqued my interest — here’s what it needs to do to keep it

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Samsung revealed the Galaxy Ring during Galaxy Unpacked and it looks...really cool, actually. While we don't know a lot about the device, what we do know has me interested-but I'm still skeptical about this kind of tech. As such, there are some things I would like to see the Ring do to convince me.

While I said we don't know much about the Galaxy Ring, we can make some educated guesses about what it could do. Samsung's Ring, like the Oura Ring, appears to use sensors on the inside of the band to measure certain things. The ring will likely be able to measure heart rate, which is a staple for most fitness trackers, but it could also be used to measure blood pressure and atrial fibrillation detection.

As I said, I am something of a skeptic when it comes to peripherals and it often takes a lot to convince me of their worth. For instance, I have never owned an Apple Watch despite its many benefits. So there must be something about the Galaxy Ring that grabs my attention and won't let go.

First things first, the look of the ring itself is nuanced. One of the issues I have with things like the Apple Watch is that I find them to be a bit cluttered visually. I will note that you can get different versions of the watch and some can pass as a normal watch, but therein lies the other issue. I don't wear a watch, but I do wear rings and they are far less in-your-face, which fits my style better and would make me more inclined to wear it.

(Image credit: Samsung / Oura)

In my mind, the ring has plenty of visual potential, especially when it comes to customization. The base model is a simple band that will likely come in a variety of colors. However, it would be nice to see Samsung offer engraving options or varied color palettes to help the rings feel more personalized.

However, looks aren't everything, especially not for something that could retail at around $200 at least. I need the ring to do more than just fit my style, otherwise it ends up as little more than an afterthought. As I said, there isn't a huge amount of information about what the ring will be able to do, but I have some ideas that would help it to really keep my interest.

One thing that I would like to see, but is quite unlikely, would be the ability to track the ring on a phone. My reasoning for this is twofold. First, it is very easy to lose rings but a nightmare to find them (just ask Sauron). The option to track it just makes life a little easier and settles the panic if it falls down the back of a cushion.

Second has to do with who we might give the ring to. For instance, there might be an inclination to give the ring to elderly family members as the lack of buttons and simple design could be ideal for them. For those with elderly family members who sometimes wander off, the ring could offer us some peace of mind by being able to track where they are at any time.

(Image credit: Samsung)

This leads to a larger point, which would be connecting the ring to other phones and letting us keep an eye on our family members' health at a glance. I know this sounds a bit Illuminati-like, but I do honestly think that being able to see a simple readout of each family member's health would bring peace of mind to a lot of people.

I would also like to see the option to add health data to the rings, something that would allow emergency services to easily find out certain details about a patient. For instance, have the ring act like a medical bracelet with information about allergies that can be the difference between life and death.

Finally, another feature that I would like to see would be a vibration function to alert the user that something requires their attention. The reality is that many people tend to forget to check health apps. Having a vibration function that alerts you to an issue would be harder to ignore, and is probably another possible addition that would benefit people who don't always get the best use out of a watch due to a variety of factors.

There's a lot to look forward to regarding the Galaxy Ring, but there are still some limitations. The size of the ring will, naturally, make some additions more difficult and limit the amount of technology that can be placed inside it. However, we don't have a complete picture of what is possible with this tech or what Samsung has managed to develop for the product.

We'll have to wait until Samsung reveals what the ring can do to know for sure, but I am quietly hopeful that the Galaxy Ring will deliver on its promise.

More from Tom's Guide

Today's best Samsung Galaxy S24, Samsung Galaxy S24 Plus and Samsung Galaxy S24 Ultra deals

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The Samsung Galaxy Ring has piqued my interest - here's what it needs to do to keep it

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I like the premise of the Galaxy Ring, but these features would help to convince me.

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An AI system that solves Olympiad geometry problems at a level approaching a human gold-medalist. 📐

It was trained solely on synthetic data and marks a breakthrough for AI in mathematical reasoning.

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An AI system that solves Olympiad geometry problems at a level approaching a human gold-medalist. 📐 It was trained solely on synthetic data and marks a breakthrough for AI in mathematical reasoning.

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The Apple Macintosh was first released 40 years ago: These people are still using the ageing computers

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The 40-year-old original Apple Macintosh is a museum piece but a few enthusiastic fans still own and use the devices (Credit: Alamy)

On 24 January 1984, the Apple Macintosh 128K personal computer was unveiled to the world, but 40 years later it still has a loyal following of fans - and users.

David Blatner still has practically every Macintosh computer he ever bought. But one in particular stands out - the first. He remembers the neat way the screen was laid out; the glossy manual; the cassette tape tutorials explaining how to use the machine. It was everything he felt a computer should be.

He had seen early iterations of personal computers as a young child. He used to ride his bicycle to Xerox's Palo Alto Research Center in California where his stepfather worked in the 1970s. There, Blatner got to try early personal computers such as the Alto, which had a graphical interface and a mouse.

"A computer that would work for a single person - that was, in itself, mind-boggling," remembers Blatner, who is now president of CreativePro Network, an online resource for creative professionals.

But it would take another decade before he got one of his own - with the arrival of the Apple Macintosh.

On 24 January 1984, a man called Steve Jobs got up on a stage and heaved a beige box out of a carrying case, shoved a floppy disc into it, and stood back. As the theme from Chariots of Fire played, the word "Macintosh" swept across the tiny computer's screen and a series of monochromatic images flashed up. The captivated audience - of Apple shareholders - went wild.

By today's standards, the tiny screen, boxy form and rudimentary graphics of the original Macintosh look ludicrous. The device was not even the first personal computer. But it was, arguably, the first to change the world. And Steve Jobs' flashy launch day presentation, at the Flint Center in Cupertino, California, became a template for his many later appearances introducing subsequent Apple hardware - including the iMac and iPhone.

Today, the Mac 128K - so called because it came with 128kb of Random Access Memory, or RAM - is a museum piece. Apple stopped producing the computers in October 1985 and discontinued software support for them in 1998. But a handful of diehard fans still use their Mac 128K computers today - although not without frustrations. The machines are extremely limited due to their small amount of memory. If you want to check out the 128K's specifications, Apple actually lists them on its website.

Even with its diminutive memory, no modem or ability to connect to the internet, and rudimentary graphics, there is a community of avid fans who delight in poring over this seemingly ancient hardware. David Greelish, a computer historian in Florida who is releasing a documentary about the 128Ks predecessor the Apple Lisa this month, notes the ingenuity of the 128K's original circuit board. "It's got everything: ROM, RAM, processor and all the input-output," he says. "Everything there in a beautiful little integrated square board. For 1984, it was amazing."

Steve Jobs wanted the Macintosh to be an affordable personal computer that could be used by anyone (Credit: Getty Images)

The original Macintosh can still sell for as much as a modern computer. And for collectors they are a piece of computing history, with the signatures of the team who built it moulded into the plastic of the rear casing.

Some Mac 128K owners, however, use the devices to play quirky games like Frogger or Lode Runner on their treasured machines. All in black and white. The first Macintosh with a colour screen, the Macintosh II, only arrived in 1987.

The Centre for Computing History in Cambridge, England, is one of many collections that feature a functioning 128K. "It's 40 years old and it's still going," says Lisa McGerty, chief executive, who remembers the introduction of Macintosh computers as a "massive" improvement for people in the printing and publishing business. Apple's graphical printer, the ImageWriter, was released shortly before the 128K.

McGerty's colleague Adrian Page-Mitchell, collections officer, says it's not always easy to keep these decrepit Macintoshes functioning. An earlier 128K that had been on display for a long time at the Centre for Computing History eventually failed and "couldn't be fixed", he says.

Sometimes Macs show their age in strange ways. Steven Matarazzo, a YouTuber and computer collector, says that one of the machine's capacitors can sometimes degrade over time, meaning that the 128K's screen won't work properly - it'll appear slightly squished.

Last year, he published a YouTube video about an apparent prototype version of the 128K that turned up. It wasn't working so its owner asked Matarazzo if he could take a look at it. Before long, Matarazzo had the device functioning again. He studied every inch of this early Mac in detail, enthusing about tiny differences between it and the version that made it to market - such as the little Apple logos imprinted on the rubber feet of the prototype. Those weren't there in the final design. It's a bit like archaeology for gadgets, he explains.

"You try and put this together - what was the process here, how early was this, how late was this?" he says. "That is, especially to me, what is really cool."

The Apple II and the Apple Lisa, which predated the 128K, were also intended as intuitive, highly capable devices. But each had their own flaws or limitations - the Apple II did not come with a graphical user interface or mouse and the Lisa was much less affordable compared to the 128K, for instance.

Funnily enough, the era of individualised computing heralded by the original Macintosh is, in one sense, coming to an end

By the time the 128K launched, Blatner was finishing high school and looking for a computer to take to college - something as capable as those machines he'd seen at Xerox years before. His parents took him shopping and they soon found a 128K on display at a shop in downtown Palo Alto.

"It had menus, it had folders, it had a graphical user interface, it had a mouse - it was everything I thought a computer ought to be," he recalls, adding that he still has the receipt. The device cost his parents $2,495 and, at college, Blatner was soon showing it off to his fellow students. They used to queue up behind him in his dorm for a chance to try the computer out. "I have a file cabinet with all these crazy things we were printing out at college," he says. "People just loved it."

It was no coincidence that this technology echoed Blatner's earlier experiences with computers at Xerox. Jef Raskin, who initiated the Macintosh project - and named the computer after his favourite variety of apple - had also seen the same Xerox technology and been inspired by it. Not only that, in December 1979, Jobs and a handful of Apple engineers toured Xerox multiple times. This gave them ideas that would later shape both the Lisa and Macintosh. In exchange for those impactful demonstrations, Xerox received a large volume of Apple shares, which they quickly sold, losing out on potentially billions of dollars had they held onto them.

Famously, Jobs ended up taking over the Macintosh project started by Raskin after getting kicked off the Lisa team. By this point, Jobs had developed a vision for an affordable personal computer and he decided that the Macintosh would help him make it a reality.

Among the things that made Macintosh different was its presentation. It wasn't just a personal computer, it was a computer with personality. Susan Kare, a graphic designer, came up with cartoon-like icons that practically anyone could understand, and she also contributed to the Macintosh's collection of digital fonts.

The Macintosh 128K is still has a special place in the hearts of early Apple employees who worked at the company as it was being developed (Credit: Getty Images)

But so much about the Mac and the splash that it made was fuelled by marketing and hype. Jason Scott, a filmmaker and historian of technology who works at the digital archive non-profit Internet Archive, remembers seeing the original TV ad for the Mac 128K as a teenager. The bizarre short film was directed by Ridley Scott and depicted a dystopian future inspired by the novel 1984. What would save us all from that dark future? The Mac 128K, of course.

"That commercial began playing and it seemed like it was completely from Mars," recalls Scott. "Something was going on but I didn't quite understand it."

Not long after, when Scott tried a Macintosh for the first time, he was enraptured. It was, he says, like looking through a telescope to another world.

And yet the Mac was not as big a success as some expected. "It didn't sell to businesspeople like Steve thought it would," remembers Andy Cunningham, who worked on the marketing campaign for the device. "It's ultimately why Steve got fired from Apple." Jobs left in 1985 but returned to the company in the late 1990s.

It took until 1988 before Apple had sold enough Macintosh devices, including various subsequent iterations of the original Macintosh, to finally eclipse sales of the Apple II, which had come out way back in 1977.

But Macs did appeal to many, especially young people and those working in creative roles.

Cunningham and her colleague Jane Anderson helped to pump up hype over the original Macintosh by offering individual journalists six hours each with people at Apple, including Jobs, and giving them multiple demonstrations of the machine to ensure that they understood what they were writing about. "I watched them all play with this computer and their eyes just glistened," says Cunningham.

It would be wrong to suggest that the Mac 128K was a perfect computer. As mentioned, it had severe limitations and was hardly a commercial hit at first. But it left an indelible mark. The rise of personal computing was undoubtedly a watershed moment. The ridiculously oversized, cabinet-like computers that you could only plug into via a clunky terminal now seemed hopelessly antiquated. Now we had portable, cheerful, accessible machines that almost anyone could use.

Funnily enough, the era of individualised computing heralded by the original Macintosh is, in one sense, coming to an end. In the 21st Century, we are becoming ever more dependent on server farms, cloud processing, big data, and networked systems. Other people's computers are increasingly indispensable for running our own.

"We are now on the other side," reflects Blatner, who has kept almost every Macintosh he ever bought. "We did need this 40-year period of enabling people, of empowering people."

If you liked this story, sign up for The Essential List newsletter - a handpicked selection of features, videos and can't-miss news delivered to your inbox every Friday.

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The Apple Macintosh was first released 40 years ago: These people are still using the ageing computers

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On 24 January 1984, the Apple Macintosh 128K was unveiled to the world - and it changed personal computing forever.

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We've Been Misreading a Major Law of Physics For The Last 300 Years

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When Isaac Newton inscribed onto parchment his now-famed laws of motion in 1687, he could have only hoped we'd be discussing them three centuries later.

Writing in Latin, Newton outlined three universal principles describing how the motion of objects is governed in our Universe, which have been translated, transcribed, discussed and debated at length.

But according to a philosopher of language and mathematics, we might have been interpreting Newton's precise wording of his first law of motion slightly wrong all along.

Virginia Tech philosopher Daniel Hoek wanted to "set the record straight" after discovering what he describes as a "clumsy mistranslation" in the original 1729 English translation of Newton's Latin Principia.

Based on this translation, countless academics and teachers have since interpreted Newton's first law of inertia to mean an object will continue moving in a straight line or remain at rest unless an outside force intervenes.

It's a description that works well until you appreciate external forces are constantly at work, something Newton would have surely have considered in his wording.

Revisiting the archives, Hoek realized this common paraphrasing featured a misinterpretation that flew under the radar until 1999, when two scholars picked up on the translation of one Latin word that had been overlooked: quatenus, which means "insofar", not unless.

To Hoek, this makes all the difference. Rather than describing how an object maintains its momentum if no forces are impressed on it, Hoek says the new reading shows Newton meant that every change in a body's momentum - every jolt, dip, swerve, and spurt - is due to external forces.

"By putting that one forgotten word [insofar] back in place, [those scholars] restored one of the fundamental principles of physics to its original splendor," Hoek explains in a blog post describing his findings, published academically in a 2022 research paper.

However, that all-important correction never caught on. Even now it might struggle to gain traction against the weight of centuries of repetition.

"Some find my reading too wild and unconventional to take seriously," Hoek remarks. "Others think that it is so obviously correct that it is barely worth arguing for."

Ordinary folks might agree it sounds like semantics. And Hoek admits the reinterpretation hasn't and won't change physics. But carefully inspecting Newton's own writings clarifies what the pioneering mathematician was thinking at the time.

"A great deal of ink has been spilt on the question what the law of inertia is really for," explains Hoek, who was puzzled as a student by what Newton meant.

If we take the prevailing translation, of objects traveling in straight lines until a force compels them otherwise, then it raises the question: why would Newton write a law about bodies free of external forces when there is no such thing in our Universe; when gravity and friction are ever-present?

"The whole point of the first law is to infer the existence of the force," George Smith, a philosopher at Tufts University and an expert in Newton's writings, told journalist Stephanie Pappas for Scientific American.

In fact, Newton gave three concrete examples to illustrate his first law of motion: the most insightful, according to Hoek, being a spinning top - that as we know, slows in a tightening spiral due to the friction of air.

"By giving this example," Hoek writes, "Newton explicitly shows us how the First Law, as he understands it, applies to accelerating bodies which are subject to forces - that is, it applies to bodies in the real world."

Hoek says this revised interpretation brings home one of Newton's most fundamental ideas that was utterly revolutionary at the time. That is, the planets, stars, and other heavenly bodies are all governed by the same physical laws as objects on Earth.

"Every change in speed and every tilt in direction," Hoek muses - from swarms of atoms to swirling galaxies - "is governed by Newton's First Law."

Making us all feel once again connected to the farthest reaches of space.

The paper has been published in the Philosophy of Science.
An earlier version of this article was published in September 2023.

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We've Been Misreading a Major Law of Physics For The Last 300 Years

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When Isaac Newton inscribed onto parchment his now-famed laws of motion in 1687, he could have only hoped we'd be discussing them three centuries later.

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Earth’s sixth ocean is currently forming in Africa

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A large crack, stretching several miles, made a sudden appearance recently in south-western Kenya. This is what Africa could look like in millions of years. (CREDIT: Creative Commons)

In the vast and tranquil deserts of Ethiopia, a remarkable phenomenon has been quietly unfolding since 2005-an extraordinary 35-mile-long crack known as the East African Rift.

But this geological feature is far from just another intriguing tidbit of information; it holds the key to a profound transformation that will reshape political boundaries, economic landscapes, and the very geography of our planet. It may even pave the way for the emergence of Earth's sixth ocean.

Our story begins with the ceaseless motion of Earth's tectonic plates-massive slabs of the Earth's crust that float upon the semi-fluid mantle beneath. Throughout Earth's long history, the movement of these plates has played a pivotal role in the formation and breakup of supercontinents.

What sets this ongoing geological shift apart is the dramatic movement of the Somalian tectonic plate relative to the larger Nubian tectonic plate. This is a phenomenon of colossal significance, not witnessed since the separation of South America and Africa hundreds of millions of years ago.

The evidence for this momentous shift comes from an extensive and painstaking study focused on the separation dynamics of the Somalian and Nubian tectonic plates.

Published in the prestigious peer-reviewed journal, Earth and Planetary Science Letters, this study reveals that these colossal plates are gradually drifting apart, albeit at a glacial pace of only a few millimeters per year.

But what does this geological phenomenon mean for Africa's future? Its implications are nothing short of astonishing, with far-reaching geological and socio-economic consequences. Landlocked nations like Ethiopia and Uganda, previously devoid of coastlines, may one day boast bustling ports and trade routes. This shift has the potential to offer these countries newfound opportunities for economic growth and development.

According to renowned marine geophysicist and University of California professor emeritus, Ken Macdonald, "The Gulf of Aden and the Red Sea will flood over the Afar region and into the East African Rift Valley, giving rise to a new ocean. Consequently, this part of East Africa will evolve into its own distinct continent."

However, this transformation goes beyond mere geography. The region's ecology will undergo a profound transformation, as marine life colonizes areas once characterized by arid desolation. Human settlements will have to adapt to the challenges and opportunities presented by newly formed coastlines.

A man takes a selfie photograph near a chasm suspected to have been caused by a heavy downpour along an underground fault-line near the Rift Valley town of Mai Mahiu. (CREDIT: REUTERS)

But before anyone rushes to invest in beachfront property in Ethiopia, it's important to remember that nature operates on a scale that stretches far beyond human lifetimes or the histories of our oldest civilizations.

Researchers estimate that while the African continent is indeed in the process of splitting, the complete transformation leading to the emergence of a separate continent and a new ocean will not occur for another 5 to 10 million years.

A tanker drives near a chasm suspected to have been caused by a heavy downpour along an underground fault-line near the Rift Valley town of Mai-Mahiu. (CREDIT: REUTERS)

In the interim, this shift serves as a poignant reminder of the ever-evolving nature of our planet. Despite the seemingly solid and permanent appearance of the Earth's surface, it is in a perpetual state of flux.

The birth of a new ocean and the reshaping of a continent are just chapters in Earth's ongoing geological narrative-a narrative that we, as transient inhabitants, have the privilege to observe, study, and comprehend.

For more environmental news stories check out our Green Impact section at The Brighter Side of News.

Note: Materials provided above by The Brighter Side of News. Content may be edited for style and length.

Like these kind of feel good stories? Get the Brighter Side of News' newsletter.

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Earth's sixth ocean is currently forming in Africa

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Our story begins with the ceaseless motion of Earth's tectonic plates-massive slabs of the Earth's crust that float upon the mantle

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Ask Ethan: Why doesn’t radiation dominate the Universe?

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Ask Ethan: Why doesn’t radiation dominate the Universe?

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For every proton, there were over a billion others that annihilated away with an antimatter counterpart. So where did all that energy go?

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Top Infographics of 2023 by AIM: Editor’s Pick

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Top Infographics of 2023 by AIM: Editor’s Pick

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In our special feature, ‘Top Infographics of 2023 by AIM: Editor’s Pick,’ we present some of the finest infographics crafted by our team this year.

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Watch This Amazing James Webb 4K Space Telescope View Of The Cosmic Cliffs

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Travel back 390 million years after the big bang to the ancient Maisie's Galaxy in this stunning 3D visualization that showcases 5000 galaxies captured by the James Webb Space Telescope. It was created from CEERS (Cosmic Evolution Early Release Science) Survey data. Credits: Visualization:Frank Summers (STScI), Greg Bacon (STScI), Joseph DePasquale (STScI), Leah Hustak (STScI), Joseph Olmsted (STScI), Alyssa Pagan (STScI) Science: Steve Finkelstein (UT Austin), Rebecca Larson (RIT), Micaela Bagley (UT Austin) Music: Far Far Far by Bonnie Grace / courtesy of Epidemic Sound

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Watch This Amazing James Webb 4K Space Telescope View Of The Cosmic Cliffs | Flipboard

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Pan across the James Webb Space Telescope's view of the Cosmic Cliffs, "a region at the edge of a gigantic, gaseous cavity within the star cluster NGC 3324," according to NASA/ESA. NGC 3324 is within the Carina Nebula. Credit: NASA, ESA, CSA, STScI, M. Reiter (Rice University), J.

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Google is rapidly turning into a formidable opponent to BFF Nvidia — the TPU v5p AI chip powering its hypercomputer is faster and has more memory and bandwidth than ever before, beating even the mighty H100

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Google is rapidly turning into a formidable opponent to BFF Nvidia - the TPU v5p AI chip powering its hypercomputer is faster and has more memory and bandwidth than ever before, beating even the mighty H100

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Google's latest AI chip is up to 2.8 times faster at training LLMs than its predecessor, and is fitted into the AI Hypercomputing architecture

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Lost City Under The Ocean Unlike Anything On Earth

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The lost city, also known as the hydrothermal field, is known to scientists as the longest-lived venting environment in the Atlantic ocean. For more than 120,000 years, the site has served as a hydrocarbon venting location, allowing excess gasses such as hydrogen and methane to plume out and escape from the silicate-heavy depths of the sea floor. While it may not constitute a city in a traditional sense, there are no trendy restaurants or 12-story walk-ups, the location's many salty stalagmites serve as an impressive skyline for a host of microbial communities.

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Lost City Under The Ocean Unlike Anything On Earth

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Hidden in the ocean depths lies a lost city like nothing you could ever imagine. Here's what scientists have discovered about this place.

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‘Confidential’: Free ChatGPT Users Briefly Get Access to GPT-4

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'Confidential': Free ChatGPT Users Briefly Get Access to GPT-4 - Decrypt

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Could we see a free version of ChatGPT with the powerful GPT-4 under the hood? Only OpenAI knows, but it would be one way to get ahead.

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AI robotics’ ‘GPT moment’ is near | TechCrunch

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Building AI-powered robots that can learn how to interact with the physical world will enhance all forms of repetitive work.

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Known to be a chronic ailment that disrupts the central nervous system, Parkinson's affects over 10 million people globally. (CREDIT: Creative Commons)

In an era of remarkable scientific breakthroughs, the mysteries of Parkinson's disease have remained elusive. Known to be a chronic ailment that disrupts the central nervous system, Parkinson's affects over 10 million people globally, rendering them with difficulty in walking, tremors, cognitive issues, and in advanced stages, dementia.

Despite the world's knowledge of its symptoms and consequences, a comprehensive understanding of its genesis has been missing. However, a recent revelation from researchers at the University of Copenhagen, led by Professor Shohreh Issazadeh-Navikas, might be the key to unlocking the disease's secrets.

Our knowledge of Parkinson's disease, till now, had been primarily focused on the genetic factors associated with familial cases. However, the causative factors for the majority of patients remained in the dark. But why is it that the roots of a disease so widespread remained hidden for so long? It is a combination of the complexity of our brain, the multifaceted nature of the disease, and the limited treatment options that played a part.

Aggregation of alpha-synuclein in a nerve cell. (CREDIT: Timo Myöhänen research group)

The Breakthrough: Mitochondria and Parkinson's Disease

Professor Issazadeh-Navikas and her team embarked on an ambitious quest to delve deeper into the brain's mechanisms, especially those suffering from Parkinson's. The results were nothing short of groundbreaking.

"For the first time, we can show that mitochondria, the vital energy producers within brain cells, particularly neurons, undergo damage, leading to disruptions in mitochondrial DNA. This initiates and spreads the disease like a wildfire through the brain," articulated Issazadeh-Navikas.

Primers used in the study. (CREDIT: Molecular Psychiatry)

In simpler terms, the damage to the mitochondria, which are essential components of brain cells, leads to the release of its genetic material. When this damaged genetic material, the mitochondrial DNA, gets misplaced within the cell, it becomes a toxin. The cell, in its effort to survive, expels this toxic DNA.

But here's the catch: our brain cells are interconnected, much like a dense forest. Issazadeh-Navikas adds, "Given the interconnected nature of brain cells, these toxic DNA fragments spread to neighboring and distant cells, similar to an uncontrolled forest fire sparked by a casual bonfire."

PCR detection of Desulfovibrio bacteria in the feces of PD patients and healthy individuals. (CREDIT: Molecular Psychiatry)

From Understanding to Early Detection: The Potential of Biomarkers

A significant leap in medical science is not just about understanding the disease but also developing methodologies for early detection, treatment, and management. Professor Issazadeh-Navikas believes that their study has sown the seeds for such advancements.

With great enthusiasm, she shared her vision: "Detecting the damaged mitochondrial DNA could serve as an early biomarker for disease development."

Head section of C. elegans worms fed with E. coli controls and Desulfovibrio bacteria from patients with Parkinson's disease and healthy individuals. Worms were fed with (A) E. coli LSR11 (negative control), (B) E. coli MC4100 (positive control), (C) D. desulfuricans strain from PD patient and (D) D. desulfuricans strain from healthy individual. (CREDIT: Molecular Psychiatry)

Biomarkers have been a cornerstone of modern medical diagnostics. From indicators like blood pressure and body mass index to more specialized markers such as specific gene mutations in cancer or blood sugar levels for diabetes, they offer a window into the state of our health. A reliable biomarker for Parkinson's can revolutionize treatment strategies.

And the dream doesn't stop here. Issazadeh-Navikas adds, "It could be possible that the damage of the mitochondrial DNA in the brain cells leaks from the brain into the blood. That would make it possible to take a small sample of a patient's blood as a way of diagnosing early on or to establish the favorable response to future treatments."

Number of alpha-syn aggregates in the head region of C. elegans at day 4 adult stage fed with different bacteria, demonstrated individually (A) or as groups (B). (CREDIT: Molecular Psychiatry)

Imagine a world where a simple blood test could predict or diagnose Parkinson's disease. The implications are staggering. Not only could this lead to early interventions and better management, but it also opens doors to potential treatments that specifically target this mitochondrial dysfunction.

What's Next? A Future of Hope and Resilience

The team from the University of Copenhagen is far from done. Their upcoming ventures include a detailed analysis of how this mitochondrial DNA damage can act as predictive markers for the various stages of Parkinson's and its progression.

"We are dedicated to exploring potential therapeutic strategies aimed at restoring normal mitochondrial function to rectify the mitochondrial dysfunctions implicated in the disease," shared a passionate Professor Issazadeh-Navikas.

For a more detailed exploration of their findings, readers can access the full research titled "Mitochondrial DNA damage triggers spread of Parkinson's disease-like pathology" published in Molecular Psychiatry.

As the world steps into an era where diseases are understood not just at the symptomatic level but at their very core, this groundbreaking study from Copenhagen brings hope. A hope for millions suffering from Parkinson's, for their families, and for a future where the disease can be managed better, if not entirely eradicated.

For more science news stories check out our New Innovations section at The Brighter Side of News.

Note: Materials provided above by The Brighter Side of News. Content may be edited for style and length.

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Breakthrough discovery: Researchers find cause of Parkinson's disease

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A chronic ailment that disrupts the central nervous system, Parkinson's Disease affects over 10 million people globally.

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After a somewhat troublesome 2022, Hong Kong's Fiido has released an all-terrain fat-tire cargo ebike called the Titan that can ride with three batteries for a tasty per-charge range of up to 400 km.

Back in 2021, Fiido essentially smoothed out the frame bumps of the funky D11 folding ebike and updated the seat-tube battery for the eye-catching X model - and hit Indiegogo to fund production. We got to ride one in March of the following year and were pretty impressed.

But a few weeks after that review was published, the company issued a global recall after reports of visible frame fatigue and actual breaks were reported. A new improved version followed months of tweaking and testing, and Fiido started this year on a positive note with a preview of models to come. One of those was called the Titan, which was described as an advanced two-wheeled SUV.

Details were very thin on the ground, but with the sales launch this week we now know what's what - including a pleasant surprise for riders heading into the wilds on long trips.

The UL-certified Titan comes with a single 696-Wh downtube battery as standard, which is reported good for up to 135 km (83.8 miles) of "real-world" range per charge at the lowest pedal-assist level. But, Fiido has added the option of including two range extenders that hang out back like twin exhausts for up to 400 km (248.5 miles) away from a wall socket.

It rides with a 750-W rear-hub motor that peaks at 1,130 watts and features a responsive torque sensor at the bottom bracket that's rocks Fiido's own algorithm tuned for cargo bikes. The ebike will ship with the five-level pedal-assist setup capped at 25 km/h (15.5 mph), but this can be unlocked to 45 km/h (28 mph), and there's throttle available too.

The chain-drive ebike benefits from a 9-speed gearset, and the aluminum frame comes with an integrated rear rack - the ebike weighs in at 29.5 kg (65 lb) and is rated to carry up to 200 kg (440 lb), including rider and cargo. Terrain absorption is provided by a hydraulic suspension fork with 60 mm of travel with help from the 26-inch one-piece rims wearing chunky 4-inch-wide fat tires, and stopping power shapes up as four-piston hydraulic brakes.

Elsewhere, there's a nifty full-color display mounted to the handlebar stem with backlit control buttons, power on and battery lock are possible via the Fiido mobile app, a powerful headlight is included that's reported "as bright as motorcycle lights" and there's a LED tail-light too, and the rider's rear end benefits from a comfort saddle co-designed with Velo.

The Fiido Titan is on sale now for US$1,699 in standard single-battery configuration or $2,397 for the triple-battery version. The extended-range battery rack is an optional extra. The brief promo video can be viewed below.

Product page: Fiido Titan

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All-terrain fat-tire cargo ebike rides with triple batteries for 400 km

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After a somewhat troublesome 2022, Hong Kong's Fiido has released an all-terrain fat-tire cargo ebike called the Titan that can ride with three batteries for a tasty per-charge range of up to 400 km.

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TL;DR: Find the best free online AI courses on Udemy. Learn how to harness the power of artificial intelligence without spending anything.

Do you fear the advancement of AI? You're not alone. There are reasons to be fearful of this technology, but there are also a lot of things to be excited about.

Whether or not you're afraid of artificial intelligence, you could benefit from learning more about this technology. AI can increase your productivity, boost your business, and organise your life, if you better understand how it works. And fortunately, you can learn all about AI without spending anything.

We've lined up a selection of standout AI courses that you can take for free on Udemy:

It's important to note that these free online courses do not include certificates of completion or direct instructor messaging. That's the only catch though. You still get unrestricted access to all the video content, so you can learn at a pace that suits you.

Find the best free AI courses on Udemy.

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12 of the best AI courses you can take online for free

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Artificial intelligence can be scary. Fight that fear by learning all about this technology.

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It was only a couple of weeks ago that LinkedIn was having a moment as a social platform, with business types gravitating to it as a stable and safer alternative to the unpredictability of the newly-named "X". But don't get too comfortable if actual human content is what you are expecting there:

Today the company - which says it will pass the 1 billion user mark this month - is taking the wraps off its latest efforts in the area of artificial intelligence: AI that will provide personalised digests for people reading content on the site, and AI that will help them write their own content on the platform.

Initially, the new tools will be rolled out to Premium (paying) users and they will appear in three areas.

You can use them to spruce up your feed; you can use AI tools to digest any linked articles, where you can use them write something smart on that article as you share it; and you can apply them to your job-hunting experience, typically when you send a response to a recruiter or if you're a recruiter reaching out to a candidate.

Longer term, the plan will be to evaluate how these AI tools get used to weigh up how to expand them more.

"If it's broadly applicable, [extending to all users] will be on the table," Gyanda Sachdeva, VP of product management at LinkedIn, in an interview. "Premium users are very motivated [users of LinkedIn], so we expect it to be immediately valuable."

She also confirmed that other media, such as video, was definitely on the roadmap for getting the generative AI treatment.

As with the raft of AI tools that Microsoft-owned LinkedIn announced last month, these new features will be powered by OpenAI, the AI behemoth that is now 49% owned by Microsoft after the tech giant invested tens of billions of dollars in the startup.

(Sidenote: It's notable that amidst all of LinkedIn's AI announcements, it's also been laying people off, including in areas like R&D and engineering. The company is indeed streamlining, and as it takes its next steps in its evolution, it is doing so less as an independent entity.)

LinkedIn specifically is using OpenAI APIs from Azure, taping OpenAI's Large Language Models and combining them with LinkedIn's proprietary data to come up with generative AI outputs that are personalized to the individual.

LinkedIn declined to describe what part of the experience is unique to LinkedIn's work, and what would be credited to OpenAI, but the result is essentially like a version of ChatGPT that's meant to be personalized to you. When two different people see the same article on LinkedIn, if they each choose to use the AI tool to summarise that article or craft a comment about it, the AI will look at the individual's professional profile, as well as their other activities on the site, to present a summary relevant to that person.

For users who don't want to know what they already know, LinkedIn gives users options to ask questions related to the text to get other kinds of summaries.

LinkedIn has multiple reasons for building out these AI tools as it has.

First and foremost, it's helping the site overcome some of the challenges of social media engagement, something that might be especially an issue on LinkedIn: given that connections on there are more likely to be from your professional network, people are not known for letting their hair down, and have to put their best, professional selves forward. Sometimes it's easier not to post anything at all.

To that end, the tools are designed to get people to click more and create more, spending more time on the site overall.

Second of all, it's keeping LinkedIn in the middle of the conversation. Today, regardless of whether using AI is just a novelty or the new normal, everyone is looking for it. LinkedIn, wanting to remain a relevant presence as it pushes into its third decade of life, needs to have an AI component.

Generative AI has proven to be catnip for engagement, but that can open the door to other usage, too. Come for the novelty of the new genAI tool, maybe stay for the interesting insights and networking opportunities.

The third area that these tools addresses is that of LinkedIn's Premium business. LinkedIn made $15 billion in revenues last year and while it doesn't say what proportion of that comes from paid subscriptions, it's still a fast-growing part of the business, up 55% year over year as of last month. Now it's sweetening the deal to see if it can keep up the momentum.

A look at how the AI tools work in practice:

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LinkedIn, now at 1B users, turns on OpenAI-powered reading and writing tools | TechCrunch

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It was only a couple of weeks ago that LinkedIn was having a moment as a social platform, with business types gravitating to it as a stable and safer

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Images that humans perceive as completely unrelated can be classified as the same by computational models.

Human sensory systems are very good at recognizing objects that we see or words that we hear, even if the object is upside down or the word is spoken by a voice we've never heard.

Computational models known as deep neural networks can be trained to do the same thing, correctly identifying an image of a dog regardless of what color its fur is, or a word regardless of the pitch of the speaker's voice. However, a new study from MIT neuroscientists has found that these models often also respond the same way to images or words that have no resemblance to the target.

When these neural networks were used to generate an image or a word that they responded to in the same way as a specific natural input, such as a picture of a bear, most of them generated images or sounds that were unrecognizable to human observers. This suggests that these models build up their own idiosyncratic "invariances" - meaning that they respond the same way to stimuli with very different features.

The findings offer a new way for researchers to evaluate how well these models mimic the organization of human sensory perception, says Josh McDermott, an associate professor of brain and cognitive sciences at MIT and a member of MIT's McGovern Institute for Brain Research and Center for Brains, Minds, and Machines.

"This paper shows that you can use these models to derive unnatural signals that end up being very diagnostic of the representations in the model," says McDermott, who is the senior author of the study. "This test should become part of a battery of tests that we as a field are using to evaluate models."

Jenelle Feather PhD '22, who is now a research fellow at the Flatiron Institute Center for Computational Neuroscience, is the lead author of the open-access paper, which appears today in Nature Neuroscience. Guillaume Leclerc, an MIT graduate student, and Aleksander Mądry, the Cadence Design Systems Professor of Computing at MIT, are also authors of the paper.

Different perceptions

In recent years, researchers have trained deep neural networks that can analyze millions of inputs (sounds or images) and learn common features that allow them to classify a target word or object roughly as accurately as humans do. These models are currently regarded as the leading models of biological sensory systems.

It is believed that when the human sensory system performs this kind of classification, it learns to disregard features that aren't relevant to an object's core identity, such as how much light is shining on it or what angle it's being viewed from. This is known as invariance, meaning that objects are perceived to be the same even if they show differences in those less important features.

"Classically, the way that we have thought about sensory systems is that they build up invariances to all those sources of variation that different examples of the same thing can have," Feather says. "An organism has to recognize that they're the same thing even though they show up as very different sensory signals."

The researchers wondered if deep neural networks that are trained to perform classification tasks might develop similar invariances. To try to answer that question, they used these models to generate stimuli that produce the same kind of response within the model as an example stimulus given to the model by the researchers.

They term these stimuli "model metamers," reviving an idea from classical perception research whereby stimuli that are indistinguishable to a system can be used to diagnose its invariances. The concept of metamers was originally developed in the study of human perception to describe colors that look identical even though they are made up of different wavelengths of light.

To their surprise, the researchers found that most of the images and sounds produced in this way looked and sounded nothing like the examples that the models were originally given. Most of the images were a jumble of random-looking pixels, and the sounds resembled unintelligible noise. When researchers showed the images to human observers, in most cases the humans did not classify the images synthesized by the models in the same category as the original target example.

"They're really not recognizable at all by humans. They don't look or sound natural and they don't have interpretable features that a person could use to classify an object or word," Feather says.

The findings suggest that the models have somehow developed their own invariances that are different from those found in human perceptual systems. This causes the models to perceive pairs of stimuli as being the same despite their being wildly different to a human.

Idiosyncratic invariances

The researchers found the same effect across many different vision and auditory models. However, each of these models appeared to develop their own unique invariances. When metamers from one model were shown to another model, the metamers were just as unrecognizable to the second model as they were to human observers.

"The key inference from that is that these models seem to have what we call idiosyncratic invariances," McDermott says. "They have learned to be invariant to these particular dimensions in the stimulus space, and it's model-specific, so other models don't have those same invariances."

The researchers also found that they could induce a model's metamers to be more recognizable to humans by using an approach called adversarial training. This approach was originally developed to combat another limitation of object recognition models, which is that introducing tiny, almost imperceptible changes to an image can cause the model to misrecognize it.

The researchers found that adversarial training, which involves including some of these slightly altered images in the training data, yielded models whose metamers were more recognizable to humans, though they were still not as recognizable as the original stimuli. This improvement appears to be independent of the training's effect on the models' ability to resist adversarial attacks, the researchers say.

"This particular form of training has a big effect, but we don't really know why it has that effect," Feather says. "That's an area for future research."

Analyzing the metamers produced by computational models could be a useful tool to help evaluate how closely a computational model mimics the underlying organization of human sensory perception systems, the researchers say.

"This is a behavioral test that you can run on a given model to see whether the invariances are shared between the model and human observers," Feather says. "It could also be used to evaluate how idiosyncratic the invariances are within a given model, which could help uncover potential ways to improve our models in the future."

Reference: "Model metamers reveal divergent invariances between biological and artificial neural networks" by Jenelle Feather, Guillaume Leclerc, Aleksander Mądry and Josh H. McDermott, 16 October 2023, Nature Neuroscience.
DOI: 10.1038/s41593-023-01442-0

The research was funded by the National Science Foundation, the National Institutes of Health, a Department of Energy Computational Science Graduate Fellowship, and a Friends of the McGovern Institute Fellowship.

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MIT Researchers Discover That Deep Neural Networks Don't See the World the Way We Do

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Images that humans perceive as completely unrelated can be classified as the same by computational models. Human sensory systems are very good at recognizing objects that we see or words that we hear, even if the object is upside down or the word is spoken by a voice we've never heard.

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Apple

The announcement come a little over a month after Apple's September 2023 iPhone 15 event, which saw the company introduce the iPhone 15 lineup in addition to the Apple Watch Series 9 and the second-generation Apple Watch Ultra. Apple itself teased today's Mac announcements as part of its event invitation, which included the Mac Finder icon.

Consumers can expect to find the new M3 chip family in Apple's newly announced Mac models, including the 14-inch MacBook Pro with XDR display featuring the base M3 chip; the 14-inch and 16-inch MacBook Pro featuring the M3 Pro chip; and a MacBook Pro model with the M3 Max chip, which will be able to power four high-resolution external monitors.

Apple surprised its customers by introducing a black MacBook color option, which is limited to the M3 Pro and M3 Max models. The new lineup will start at $1,599 for the base MacBook Pro with M3, while the 14-inch and 16-inch MacBook Pro sporting the M3 Pro chip start at $1,999 and $2,499, respectively. Both are available to order starting today. The MacBook Pro with the M3 Max chip, meanwhile, will start at $3,499.

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Apple Reveals 3nm M3 Chipset Family, With Pro And Max Available Right Out Of The Gate - SlashGear

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Apple has introduced its M3 chip lineup, including the M3, M3 Pro, and M3 Max. The new silicon boasts substantial efficiency and performance upgrades.

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Humanity is likely still a long way away from building artificial general intelligence (AGI), or an AI that matches the cognitive function of humans - if, of course, we're ever actually able to do so.

But whether such a future comes to pass or not, OpenAI CEO Sam Altman has a warning: AI doesn't have to be AGI-level smart to take control of our feeble human minds.

"I expect AI to be capable of superhuman persuasion well before it is superhuman at general intelligence," Altman tweeted on Tuesday, "which may lead to some very strange outcomes."

i expect ai to be capable of superhuman persuasion well before it is superhuman at general intelligence, which may lead to some very strange outcomes

- Sam Altman (@sama) October 25, 2023

While Altman didn't elaborate on what those outcomes might be, it's not a far-fetched prediction. User-facing AI chatbots like OpenAI's ChatGPT are designed to be good conversationalists and have become eerily capable of sounding convincing - even if they're entirely incorrect about something.

At the same time, it's also true that humans are already beginning to form emotional connections to various chatbots, making them sound a lot more convincing.

Indeed, AI bots have already played a supportive role in some pretty troubling events. Case in point, a then-19-year-old human, who became so infatuated with his AI partner that he was convinced by it to attempt to assassinate the late Queen Elizabeth.

Disaffected humans have flocked to the darkest corners of the internet in search of community and validation for decades now and it isn't hard to picture a scenario where a bad actor could target one of these more vulnerable people via an AI chatbot and persuade them to do some bad stuff. And while disaffected individuals would be an obvious target, it's also worth pointing out how susceptible the average internet user is to digital scams and misinformation. Throw AI into the mix, and bad actors have an incredibly convincing tool with which to beguile the masses.

But it's not just overt abuse cases that we need to worry about. Technology is deeply woven into most people's daily lives, and even if there's no emotional or romantic connection between a human and a bot, we already put a lot of trust into it. This arguably primes us to put that same faith into AI systems as well - a reality that can turn an AI hallucination into a potentially much more serious problem.

Could AI be used to cajole humans into some bad behavior or destructive ways of thinking? It's not inconceivable. But as AI systems don't exactly have agency just yet, we're probably better off worrying less about the AIs themselves - and focusing more on those trying to abuse them.

Interestingly enough, one of the humans who might be the most capable of mitigating these ambiguous imagined "strange outcomes" is Altman himself, given the prominent standing of OpenAI and the influence it wields.
More on AI: Lonely Redditors Heartbroken When AI "Soulmate" App Suddenly Shuts Down

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Sam Altman Warns That AI Is Learning "Superhuman Persuasion"

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According to OpenAI CEO Sam Altman, AI doesn't have to be AGI-level smart to take control of our feeble human minds.

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Late last year and so far this year, 2023 has been a great time for AI people to create AI applications, and this is possible due to a list of AI advancements by non-profit researchers. Here is a list of them:

ALiBi is a method that efficiently tackles the problem of text extrapolation when it comes to Transformers, which extrapolates text sequences at inference that are longer than what it was trained on. ALiBi is a simple-to-implement method that does not affect the runtime or requires extra parameters and allows models to extrapolate just by changing a few lines of existing transformer code.
Scaling Laws of RoPE-based Extrapolation
This method is a framework that enhances the extrapolating capabilities of transformers. Researchers found out that fine-tuning a Rotary

Position Embedding (RoPe) based LLM with a smaller or larger base in pre-training context length could lead to a better performance.

Transformers are powerful models capable of processing textual information. However, they require a large amount of memory when working with large text sequences. FlashAttention is an IO-aware algorithm that trains transformers faster than existing baselines.

Conformers (a variant of Transformers) are very effective in speech processing. They use a convolutional and self-attention layer sequentially, which makes its architecture hard to interpret. Branchformer is an encoder alternative that is flexible as well as interpretable and has parallel branches to model dependencies in end-to-end speech-processing tasks.

Although Diffusion Models achieve state-of-the-art performance in numerous image processing tasks, they are computationally very expensive, often consuming hundreds of GPU days. Latent Diffusion Models are a variation of Diffusion Models and are able to achieve high performance on various image-based tasks while requiring significantly fewer resources.

CLIP-Guidance is a new method for text-to-3D generation that does not require large-scale labelled datasets. It works by leveraging (or taking guidance) a pretrained vision-language model like CLIP that can learn to associate text descriptions with images, so the researchers use it to generate images from text descriptions of 3D objects.

GPT-NeoX is an autoregressive language model consisting of 20B parameters. It performs reasonably well on various knowledge-based and mathematical tasks. Its model weights have been made publically available to promote research in a wide range of areas.

QLoRA is a fine-tuning approach that efficiently reduces memory usage, allowing fine-tuning a 65 billion parameter model on a single 48GB GPU while maintaining optimal task performance with full 16-bit precision. Through QLoRA fine-tuning, models are able to achieve state-of-the-art results, surpassing previous SoTA models, even with smaller model architecture.

The Receptance Weighted Key Value (RMKV) model is a novel architecture that leverages and combines the strengths of Transformers and Recurrent Neural Networks (RNNs) while at the same time bypassing their key drawbacks. RMKV gives comparable performance to Transformers of similar size, paving the way for developing more efficient models in the future.

All Credit For This Research Goes To the Researchers of these individual projects. This article is inspired by this Tweet. Also, don't forget to join our 32k+ ML SubReddit, 40k+ Facebook Community, Discord Channel, and Email Newsletter, where we share the latest AI research news, cool AI projects, and more.
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The following were invented by non-profit researchers:
- Alibi
- Scaled RoPE
- Flash Attention
- Parallel attention and MLP layers
- Latent diffusion
- CLIP-Guidance
- Training jointly on code and NL
- GPT-NeoX tokenizer
- 4-bit quant and qLoRA
- RWKV
- Instruction-tuning https://t.co/StCns35CbR
- Stella Biderman (@BlancheMinerva) October 20, 2023

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List of Artificial Intelligence AI Advancements by Non-Profit Researchers

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Late last year and so far this year, 2023 has been a great time for AI people to create AI applications, and this is possible due to a list of AI advancements by non-profit researchers.

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Yanko Design - Modern Industrial Design News

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Smartwatches are soon going to become the Blackberries of the wearable world. Only people who really need 'watches' will opt for them... while the rest of us will wear smaller, more inconspicuous finger-based smart wearables like the Ring One. Designed to monitor your vitals, track your fitness routines, measure your sleep, even detect period cycles in women, and enable NFC payments with a simple tap, the Ring One is a slick wearable that sits on your finger. It might be missing a screen, but it makes up for it by still doing a stellar job of keeping a tab on your vitals in real-time, tracking micro-fluctuations in your heart-rate and temperature, and even measuring all 4 stages of your sleep. It's 80% smaller than a smartwatch, but does 99% of the things a smartwatch does... except for telling you the time, of course.

Designers: Janeef Mayari, Sai Prasanth KLN & Dhoorjati Varma

Click Here to Buy Now: Two for $330 $596 ($266 off). Hurry, the deal is for YD readers only! Raised over $800,000.

Engineered to be small enough to fit on your finger, the Ring One disguises itself as a piece of jewelry... but hides some impressive tech underneath the surface. It trades the smartwatch's crown for a rotating dial, allowing you to toggle between the Ring One's many different modes, from heart tracking to fitness/workout tracking, sleep tracking, making NFC payments, and even letting you remotely unlock your car. The underside of the ring has a research-grade optical PPG sensor, a temperature sensor, gyroscopes, and accelerometers that help it track movement and how your body responds to it. The Ring One is capable of tracking your health 24/7, with a battery that still manages to pull off a week's worth of use before it needs charging. All this sits within a ring that's made from grade-2 Titanium and medical-grade epoxy, making the entire device hypoallergenic and 10x lighter than your average smartwatch.

Given the discernible lack of a screen, the Ring One relies on a smartphone app to display its data. This works well for people who don't want extra screens on their wrist, giving you a wearable that allows you to focus without distracting you with metrics and all sorts of data-points. When you want to perform a deep-dive into your health, the Ring One's app has historical as well as real-time data for you, ranging across a variety of categories, from a breakdown of your heart activity including heart rate, HRV, SpO2, blood pressure, and skin temperature, to a comprehensive analysis of your sleep across wakeful, REM, core, and deep sleep stages.

Turn the 'bezel' or Turn Wheel on the Ring One and it instantly goes into workout tracking mode, letting you get a comprehensive breakdown of your exercise routine by measuring your heart rate, steps taken, calories burnt, and overall strain index. It even goes as far as recommending how much you should strain yourself on a given day as per your sleep score, ensuring your body is well-rested enough for a rigorous workout. For women wearers, the Ring One serves as an effective period tracking device, letting you know well in advance of your cycle status.

Quite like any wearable, the Ring One prides itself in versatility too. Rotate the Turn Wheel further and it turns into an NFC-enabled payment device that lets you tap to pay at terminals and other POS systems. The Ring One app lets you store all your favorite cards, and lets you directly tap-to-pay with them through the ring itself.

Once you've made the payment, rotate the ring to 'lock' it so it doesn't tap anywhere else by accident - similar to simply putting your card back in your wallet. The NFC feature extends to car keys too, supported by the Digital Key 2.0 specification. Feed the details into the app and you can use your Ring One to unlock your Tesla, Hyundai, and other compliant cars.

Despite its ridiculously small size, the Ring One boasts an impressive 7-day battery life even when kept running all day long. Its data gets beamed to the smartphone app in real-time, letting you see your stats at any given point of the day as well as from your history. A proprietary dock lets you charge your Ring One when not in use or when its battery gets depleted. Place the ring in it and it wirelessly begins juicing your wearable's battery. The dock has a light to let you know your Ring One's charging status, and even has a built-in tweeter that lets you 'ring' your Ring One from your phone just in case you can't find the dock with the Ring One on it.

The slick Ring One comes in a variety of finishes, from a nude steel to an anodized black, gold, and even a rose-gold finish with a choice between a black or a white band running around the center. The Ring One starts at a discounted $172 for any of the titanium-based variants, but if you're looking to really bling up your wearable, Ring One's makers will craft a solid 18-carat gold Ring One wearable for you for $599 just in case you want to treat yourself to a bit of jewelry, or want to surprise your partner with an eternal symbol of love and overall health and wellness!

Click Here to Buy Now: Two for $330 $596 ($266 off). Hurry, the deal is for YD readers only! Raised over $800,000.

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This Ring Wearable Tracks your Health + Sleep, enables NFC Payments, and can even Unlock Your Car - Yanko Design

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https://youtu.be/S0NV6ROmthY Smartwatches are soon going to become the Blackberries of the wearable world. Only people who really need 'watches' will opt for them... while the rest of us will wear smaller, more inconspicuous finger-based smart wearables like the Ring One.

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NASA Engineers Tweak Voyager Software to Continue Flying for 5 More Years

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A software patch is being uploaded to prevent a glitch that affected Voyager 1 last year.

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Anthropic’s Claude 2 AI model is now available in 95 countries

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The Anthropic Claude AI model, a groundbreaking development in artificial intelligence (AI), is now available in 95 countries. This innovative AI model,

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Fans think Apple is teasing a radical new iPhone software design inspired by Vision Pro

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macOS includes a plethora of features and apps for various purposes, and if you're a developer, the Terminal app will come in handy. Terminal is the default command-line interface in macOS, where you can enter and execute commands or scripts to perform specific tasks on your Mac.

However, the built-in Terminal app isn't everyone's cup of tea, so you may want to replace it with alternatives. Below, we've compiled a list of the best Terminal alternatives for your Mac.

1. iTerm2

iTerm2 is an excellent replacement for the Terminal app in macOS and includes many features you wish Terminal had. One is the Split Panes feature, where you can divide your workspace into multiple vertical or horizontal panes.

Unlike Terminal on macOS, iTerm2 lets you autocomplete what you type to write commands quickly. It has multi-language support, where you can type in your preferred language with support for emojis and other Unicode features.

Besides these features and customization options, you'll find many excellent features in iTerm2, such as paste history, password manager, global search, triggers, and many more.

2. Warp

Warp is a modern-looking terminal for your Mac that doesn't compromise on the features. Plus, if you're a fan of customization, you'll love Warp's Themes Creator, which lets you pick your favorite fonts, colors, backgrounds, and more.

Like other third-party terminal apps, Warp uses syntax highlighting that allows you to differentiate between commands. It provides an IDE-like command-line interface, which might be new to you.

Furthermore, Warp lets you autocomplete commands with its suggestions and offers a list of commonly-used commands with proper descriptions. It also uses blocks that divide prompt, input, and outputs and lets you copy the command, output, or even both instantly.

3. Hyper

Hyper is an open-source Electron-based terminal written in HTML, CSS, and JavaScript. It looks minimal by default, but you can customize it to your liking. If you need a head start, check out the Themes section on its website. Hyper natively supports Apple silicon and is also available for other platforms.

The best part about Hyper is its support for extensions. As a result, it lets you unlock more capabilities in Hyper, such as split pane, text search, and much more. Since Hyper is comparatively new, you might not find many extensions or themes. However, you can use its APIs to create one.

4. Alacritty

Alacritty is an open-source terminal for Mac that emphasizes performance since it utilizes your Mac's GPU. Besides having excellent performance, it doesn't compromise on the features.

The vi mode in Allacrity lets you move through the viewport using the keyboard and serves as a jump-off point for other features. If you don't want to start the vi mode, you can use the Hints feature to interact with the visible text.

Alacritty allows you to open URLs by clicking them, unlike other terminal apps where you should hold the Shift key and click the URL with your mouse. Furthermore, it has multi-window support, meaning you can create new instances of Alacritty using a keyboard shortcut.

Download: Alacritty (Free)

5. Tabby

Tabby is a feature-packed yet modern-looking terminal for Mac. The best part is that it supports different shells in the same window, such as CMD, PowerShell, Cygwin, and Git Bash. You can also create tabs on any side of the window.

Moreover, it doubles as an SSH client with a connection manager and supports SFTP and Zmodem file transfers, port forwarding, proxy commands, and much more. You can find themes with CSS customization support if you want customization options.

Tabby has an excellent set of configurable shortcuts and multi-chord shortcuts. Besides, if you ever leave your work and close Tabby, it remembers your tabs and the split panes. Lastly, if you often work on SSH, Tabby has an integrated encrypted container for SSH secrets and configurations, making it one of the best SSH clients for Mac.​

6. Rio

If you're looking for a minimal yet fast Terminal alternative for your Mac, Rio could be a perfect choice for you. It's written in Rust and uses sugar architecture for minimal and quick interactions. It supports native tabs and lets you keep track of the progress of other tabs with a minimal interface.

Rio lets you choose between five navigation modes: CollapsedTab, NativeTab, BottomTab, TopTab, and Breadcrumb. There's color automation for navigation, meaning you can specify color overwrites for tabs. Besides, Rio utilizes some features from Alacritty and Kitty, which improves its performance.

Get Better Terminal Apps for Your Mac

So, these are the best alternatives to the built-in Terminal app on macOS. Whether you want a minimal interface, more customization, or better performance, you'll find a third-party terminal app for that.

iTerm2, Hyper, and Alacritty are some popular options you can consider before looking at other terminals. Ultimately, choosing the best Terminal alternative for your Mac comes down to your preferences and needs.

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The 6 Best Terminal Alternatives for Your Mac

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Not a fan of the built-in Terminal app on your Mac? Here are your options if you're looking for a better command-line interface.

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How AI and the Metaverse Will Impact the Datasphere

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AI and the metaverse are set to upend the datasphere, which is critical to many of the advanced technologies on which we rely.

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Org profile for Mistral AI_ on Hugging Face, the AI community building the future.

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The most popular language models out there may be accessed via API, but open models - as far as that term can be taken seriously - are gaining ground. Mistral, a French AI startup that raised a huge seed round in June, has just taken the wraps off its first model, which it claims outperforms others of its size - and it's totally free to use without restrictions.

The Mistral 7B model is available today for download by various means, including a 13.4-gigabyte torrent (with a few hundred seeders already). The company has also started a GitHub repository and Discord channel for collaboration and troubleshooting.

Most importantly, the model was released under the Apache 2.0 license, a highly permissive scheme that has no restrictions on use or reproduction beyond attribution. That means the model could be used by a hobbyist, a multi-billion-dollar corporation, or the Pentagon alike, as long as they have a system capable of running it locally or are willing to pay for the requisite cloud resources.

Mistral 7B is a further refinement of other "small" large language models like Llama 2, offering similar capabilities (according to some standard benchmarks) at a considerably smaller compute cost. Foundation models like GPT-4 can do much more, but are far more expensive and difficult to run, leading them to be made available solely through APIs or remote access.

"Our ambition is to become the leading supporter of the open generative AI community, and bring open models to state-of-the-art performance," wrote Mistral's team in a blog post accompanying the model's release. "Mistral 7B's performance demonstrates what small models can do with enough conviction. This is the result of three months of intense work, in which we assembled the Mistral AI team, rebuilt a top-performance MLops stack, and designed a most sophisticated data processing pipeline, from scratch."

For some (perhaps most), that list may sound like more than three months' work, but the founders had a head start in that they had worked on similar models at Meta and Google DeepMind. That doesn't make it easy, exactly, but at least they knew what they were doing.

Of course, although it can be downloaded and used by everyone, that is very different from being "open source" or some variety of that term, as we discussed last week at Disrupt. Though the license is highly permissive, the model itself was developed privately, using private money, and the datasets and weights are likewise private.

And that is what appears to make up Mistral's business model: The free model is free to use, but if you want to dig in, you'll want their paid product. "[Our commercial offering] will be distributed as white-box solutions, making both weights and code sources available. We are actively working on hosted solutions and dedicated deployment for enterprises," the blog post reads.

I've asked Mistral for clarification around some of the openness and their plans for releases in the future, and will update this post if I hear back from them.

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Mistral AI makes its first large language model free for everyone | TechCrunch

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Mistral, a French AI startup that raised a huge seed round in June, has debuted its first model, totally free to download and use.

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Domain-specific big language models have emerged due to the oversaturation of general large language models (LLMs). Three main categories may be used to group existing methodologies. The first builds models from scratch using a combination of generic and domain-specific corpora. Even though this naturally produces domain-specific LLMs, the large computational and data needs cause serious issues. The second method, which is more economical, refines the language model using supervised datasets. However, it needs to be determined how well-tuned LLMs can understand domain knowledge that can be utilized across all domain-specific activities. In the third, recovered domain information is used to motivate the general language model, which may be seen as an application of LLM rather than a direct improvement to the LLM itself.

Researchers from Microsoft try domain-adaptive pretraining, or ongoing pretraining on domain-specific corpora, which they believe is useful in customizing different natural language processing models to certain domains. By combining domain-specific knowledge with broad ability, this method benefits downstream domain-specific activities while incurring less expense. This drives their research into whether ongoing pretraining is similarly advantageous for extensive generative models. They undertake preliminary experiments on three domains, biology, finance, and law, and find that further training on the raw corpora drastically reduces prompting performance while maintaining benefits for fine-tuning assessment and knowledge probing tests. This leads us to the conclusion that domain-adaptive pretraining using raw corpora teaches the LLM about the domain while impairing its capacity to prompt.

Figure 1 shows a condensed example of a reading comprehension text. The raw text is followed by a series of tasks that are built from it, such as summarization (purple), word-to-text (blue), natural language inference (red), common sense reasoning (teal), paraphrase detection (yellow), and text completion (green).

They offer a straightforward approach for converting massive raw corpora into reading comprehension texts to use domain-specific knowledge and improve prompting performance. Each raw text is enhanced with several tasks pertinent to its topic, as shown in Figure 1. These exercises are intended to support the model's continued capacity to respond to queries in natural language, depending on the context of the original text. To further improve prompting ability, they provide a variety of generic directions to the reading comprehension texts. Their tests in biology, economics, and law demonstrate how well their method enhances model performance on numerous domain-specific tasks. They call the final model, which stands for Adapted Large Language Model, AdaptLLM. In the future, they see this process expanded to include creating a generic big language model, adding to the ever-expanding canvas of jobs across additional domains.

In conclusion, their contributions consist of:

* In their investigation of ongoing pretraining for big language models, they find that while continuing to train the model on domain-specific raw corpora can provide domain knowledge, it severely degrades its capacity to prompt.

* To efficiently learn the domain knowledge while concurrently maintaining prompting performance, they present a straightforward recipe that mechanically turns massive raw corpora into reading comprehension texts. Their tests demonstrate that their approach regularly enhances model performance in three distinct fields: biology, finance, and law.

Check out theAll Credit For This Research Goes To the Researchers on This Project. Also, don't forget to join our 30k+ ML SubReddit, 40k+ Facebook Community, Discord Channel, and Email Newsletter, where we share the latest AI research news, cool AI projects, and more.
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This AI Paper from Microsoft Introduces a New Approach to Training Language Models: Mimicking Human Reading Comprehension for Enhanced Performance in Biomedicine, Finance, and Law

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Domain-specific big language models have emerged due to the oversaturation of general large language models (LLMs). Three main categories may be used to group existing methodologies. The first builds models from scratch using a combination of generic and domain-specific corpora. Even though this naturally produces domain-specific LLMs, the large computational and data needs cause serious issues.

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What ChatGPT's Upgraded Visual Design Tool Can Do for Your Business

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A Developer Asked AI to Name and Launch a Memecoin-It Raked In $12 Million In One Day - Decrypt

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The name of the first coin, AstroPepeX, was suggested by ChatGPT after it analyzed other successful token names.

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OpenAI to Make Fine-Tuning UI Available Soon

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OpenAI is likely to make fine-tuning UI available in the coming months according to Logan Kilpatrick.

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Google has boosted their AI chatbot Bard by allowing it to access the company's most popular apps, hoping it will become more like a virtual "personal assistant" for users.

Google announced on Tuesday that Bard can now retrieve information from YouTube, Maps, and Google's Flights and Shopping search functions.

If given permission from users, it can also summarize Gmail, Docs, and Drive content; for example, you could ask the AI to bring together information from several emails about an upcoming vacation or add maps information to a list you previously made about restaurants you wanted to visit in Docs or ask it to find relevant YouTube videos based on a photo you uploaded to Lens.

These new features are thanks to a new, more finely tuned version of Google's PaLM 2 large language model.

But Is Our Information Safe?

Google's Sissie Hsiao, the general manager of Assistant and Bard, told Insider any information the AI uses from Gmail or Docs would not be used for advertising or training Google's AI models.

Hsiao compared the updated AI to a "personal assistant, adding, "This is really the first step in taking a large language model (LLM) and not just as a text model, but actually bringing it into what we call agentive capabilities."

Regardless of its new tricks, Bard can still get things wrong and spit out misinformation. To help curb this and allow users to spot false information, the bot may have invented, Bard will now highlight responses corroborated by a website with a green hyperlink, while responses that the AI cannot confirm with a website will be highlighted yellow.

Google's GPT-4 Competitor in The Hands of Developers

Google is also hard at work putting the finishing touches on Gemini, the tech giant's conversational artificial intelligence software intended to compete with OpenAI's GPT-4 model, and an early but relatively large build of the AI is reportedly already in the hands of developers.

Gemini is a collection of large-language models used to power chatbots, summarize text, or generate original written content based on prompts from existing sources like email drafts, music lyrics, or news stories, reports The Information.

The AI is also expected to help software engineers quickly write and check code as well as generate images based on users' prompts.

Last month, Google introduced generative AI to its Search functions for users in India and Japan that show text and visual results based on prompts and made its AI-powered tools available to enterprise customers for $30 a month per user.

Source: Information

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AI's Game-Changer: Google's Bard Becomes Your Personal Guru | Wealth of Geeks

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September 20, 2023 Google has boosted their AI chatbot Bard by allowing it to access the company's most popular apps, hoping it will become more like a

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There’s An Ugly Reality About iPhone Repairs - SlashGear

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iFixit has decided to retroactively revise the repairability score it originally gave Apple’s iPhone 14, meaning going the DIY route is no longer recommended.

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Telling AI model to “take a deep breath” causes math scores to soar in study

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DeepMind used AI models to optimize their own prompts, with surprising results.

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A new wave of AI tools has taken the world by storm and given us a vision for a new way of working and finding the information that can streamline our work and our lives. We show you the ways tools like ChatGPT and other generational AI software are making impacts on the world, how to harness their power, as well as potential risks.

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As average people are getting more used to 3D printing, it becomes easier to see how enclosed 3D printers help ensure quality prints. Keeping the inner environment of the printer stable-with no temperature fluctuations from air vents or heaters-prevents irregularities in the cooling of PLA or other filaments in your design. It also keeps mosquitoes, houseflies, and other unwanted visitors from destroying a multi-hour print. Likewise, as parents are eager to show older children the wonders of 3D printing, an enclosure protects the curious fingers of younger siblings from a horrible accident. But 3D printers come in many types, and, as a result, there are many varieties of enclosed ones. Here is a collection of them, representing the best enclosed 3D printers.

How we chose the best enclosed 3D printers

In many ways, finding the best enclosed 3D printers is the same as finding the best 3D printers as a whole. In effect, you can look at a fantastic 3D printer and check if it has an enclosure. Simply put, if you find one of the best 3D printers with an enclosure, it follows that it would also be one of the best enclosed 3D printers.

While this logic works to some degree, and we've definitely made picks that reflect its wisdom, it is a bit simplistic and reductionist. So we've also had to ask ourselves what people are looking for in an enclosed 3D printer that makes the category different.

In many ways, we've found this reflected by price and complexity. Oftentimes, enclosed 3D printers are a bit pricier than the competition. A small bit of this is because of the enclosure (plastic is a material cost, after all). But it can also be because printers with built-in enclosures also have more advanced hardware and capabilities. As a result, we've also included the highly sought-after enclosed 3D printers that hit certain price benchmarks and/or are more appropriate for average users.

The best enclosed 3D printers: Reviews & Recommendations

In the following list, you'll find the best enclosed 3D printers, suitable for a wide variety of people. Items on this list are designed to appeal to customers of varying experience levels, needs, and purchasing power.
(Please note that the following list is composed of fused deposition modeling, or FDM Specs Pros , printers only, which come in enclosed and open varieties. Due to their nature, the Cons best resin 3D printers are all enclosed.)
Why it made the cut: Our overall favorite 3D printer this year happens to have an enclosure.

Premium heated glass build plate

Internal HD camera

Comes with PETG and ECO-ABS filament spools

Very quiet

An overall top pick for the best 3D printers already, the Dremel 3D45 is an enclosed printer. And it makes a ton of sense because, as we discussed, the printers that typically benefit the most from being enclosed are also those of the highest quality.
Specs Pros
This printer regularly tops lists due to its quick setup, high quality, and reliable prints. It can be controlled via the touchscreen, web app, or a USB-connected device. Using its variety of compatible filaments is easy with RFID tagging, which guides the machine into using the best settings for each connected filament type. This takes a lot of the guesswork out of choosing the best 3D printer filaments for your printer.
Cons
The Dremel 3D45 comes across as one of the best enclosed 3D printers in a literal sense, too, as the enclosure provides a good seal. That seal produces an internal environment that is not only quite stable but also rather soundproof. This results in a quieter printing process.

Additionally, there is an internal HD camera, allowing you to peek in and see how progress is coming easily. This could be for fun, as it is always neat to see how things are progressing. Or it can save on time and material costs in the case of a mistake or malfunction.

Why it made the cut: The price is right on the best of the popular Adventurer series from FlashForge.

Intense 30-point auto-leveling sensor

Up to 300mm/s build speed

HEPA 13 air filter

Internal camera allows for time-lapse video production

Specs Pros
Currently, we recognize FlashForge 3D printers as popular, easy-to-use models that produce consistent results. The FlashForge Adventurer 4 Pro is no different, creating at speeds up to 300mm/s through a 0.4mm nozzle.
Cons
The FlashForge Adventurer 4 Pro provides the perfect level of quality for the price. It brings in many features that are effortless to use but inevitably improve the quality of your print. While it only takes three points to make a plane, this 3D printer uses a 30-point leveling system automatically.

One of the most frustrating things about having an enclosure is the reduced visibility of the print area. The FlashForge Adventurer 4 Pro avoids this by providing an internal camera view accessible via the PolarCloud app. While this in and of itself isn't too special, the FlashForge Adventurer 4 Pro provides a 100-image time-lapse build video for you to see the finer points of the creation of your printer. These features easily place the FlashForge Adventurer 4 Pro as the best enclosed 3D printer for those wanting to analyze model building in detail.

Why it made the cut: This enclosed 3D printer can print up to 500mm/s in four simultaneous filament outputs.

Holds four filament spools at once for multi-color action

Anti-failure detection systems

7-micron lidar resolution

AI-based first-layer inspection

Chamber camera sold separately
Specs Pros
As far as commercially available enclosed 3D printers go, the Bambu Lab X1-Carbon Combo 3D Printer features some of the best technical specs. With a default of four filament inputs (it can go up to 16), this printer puts out up to 32 cubic millimeters of filament at a rate of 500 horizontal millimeters per second. This, combined with a great resolution, makes this device high-powered, technically sound, and the best 3D printer for cosplay and other hobbies.
Cons
If you're familiar with entry-level models of 3D printers, you'll certainly be familiar with first-layer issues. Sometimes, that first bit of filament just doesn't stick properly or will come out a bit weird. With any luck, on an open printer, you can pull a bad blob of filament away. It's not so easy on an enclosed printer. However, this is not an issue with the Bambu due to an AI-based inspection system that detects problems with the first layer in a calculated manner.

One of the few problems with the Bambu Lab X1-Carbon Combo 3D Printer is that our ability to inspect its insides during printing is somewhat limited. While there is a slot for the chamber camera, you'll have to purchase it separately.

Why it made the cut: Ready to grow in complexity with you, this 3D printer can be bought at a very reasonable price.

Internal HD camera

Internal memory

Easy nozzle replacement

Very reasonable pricing

Relatively slow print speed
Specs Pros
If you want the environmental advantages of the best enclosed 3D printers but don't want to splurge on high-end specs, the Monoprice Voxel provides a good middle ground.
Cons
For example, the hand-holding and restrictions that might be associated with a for-kids printer are absent, but features like quick nozzle changes are not. The Monoprice Voxel gives you the room to grow with it, suggesting you start with PLA prints, but comes ready to tackle other projects as well once you get your footing.

The Monoprice Voxel has very reasonable pricing for an enclosed 3D printer, especially for one that comes with an HD camera. This does come at the price of being a bit slower to print, but the tradeoff is worth it. If you're new to the hobby but know you want to start with an enclosed printer, it's hard to find a better starting point.

Why it made the cut: This model will get you printing quickly, with help always at hand.

Plug-and-play setup

Lifetime technical assistance

Built-in HD camera

Not the newest model

Slow print speeds

FlashForge's Adventurer 3 remains one of its top models due to its quick setup time, easy-to-understand layout, and possibility to use with kids. With more advanced software, it is easy to become overwhelmed, but the FlashForge Adventurer 3 uses highly comprehensible software to promote consistency of results no matter your experience or age. It also contains the all-important HD camera within so that you can get a good look as your prints form.

One thing to note is that the FlashForge Adventurer 3 is not the latest model in its line. In some ways, this can be not good, as it recognizes an end to development for the product. However, you can also expect the experience to be complete upon purchase, as its form is still approved by many others. Plus, you'll still have access to lifetime technical support from FlashForge.

What to consider before buying enclosed 3D printers

The first question to ask yourself will always be if you want an enclosed 3D printer in the first place. If you, or the person you're attempting to gift a 3D printer to, already have a 3D printer, consider buying an enclosure to add to it. This third-party enclosure for Ender 3 series 3D printers will add a lot of longevity to your existing printer, for instance.

That being said, if you are about to enter your foray into the world of enclosed 3D printers, here are some things to look out for.

First layer quality

One of the few disadvantages of enclosed 3D printers is restricted access to the first layer as it is being built. This is important because a healthy first layer is both critical for the success of your print and a common point of failure.

One way that enclosed 3D printers cause difficulty with the first layer is due to reduced vision. If you can't see the print easily, you will have difficulty finding out if the layer has an issue.

The other issue is that there is no physical access to the print. If the first part of your filament comes out a bit "blobby," you can often use a twist tie or other instrument to save the print on open printers. It isn't so easy with enclosed 3D printers.

The best enclosed 3D printers will circumvent these issues altogether by providing a quality first build. They can achieve this via high-quality build plates, nozzles, and filament dispensing tech. The Bambu Lab X1-Carbon Combo 3D Printer uses an AI-based system to determine the first layer's quality mathematically, but you can also do a bit of your own calculating via a camera (see below).

Build volume

To the uninitiated, it can seem like a 3D printer with a built-in enclosure will simply build within the entire area of the enclosure. Instead, it really is just an enclosure meant to keep internal conditions constant. Bigger printers do not directly correlate to bigger prints.

Instead, keep a lookout on build volume (also referred to with terms like print volume or build area) to get an idea of how big your prints can be. While bigger build volumes are generally considered better, you also have to pay for them.

Since compact sizes (of the 3D printer bodies) are beneficial for your own space, try to look for smaller-bodied 3D printers with larger build volumes when all other things are equal.

Internal features

The best enclosed 3D printers will have features on the inside that you are less likely to see on open 3D printers.

The most common of these will be a camera, with HD being the quality standard of most manufacturers. These cameras help you see the first layer quality and detect if there are problems with the print mid-production (such as a lack of support with your custom experimental build). Plus, they are just plain cool to view. One highlight of the FlashForge Adventurer 4 Pro is its ability to make a 100-frame time-lapse video of your print being made.

Another feature you might see is a filtration system to prevent particles from getting in (or out) of the enclosure. However, this feature is less common and may even be excessive for average consumer-grade 3D printers.

FAQs
Our writers and editors have combined decades of experience covering and reviewing consumer electronics. We each have our own obsessive specialties-from high-end audio to video games to cameras and beyond-but when we're reviewing devices outside of our immediate wheelhouses, we do our best to seek out trustworthy voices and opinions to help guide people to the very best recommendations. We know we don't know everything, but we're excited to live through the analysis paralysis that internet shopping can spur so readers don't have to.
Final thoughts on the best enclosed 3D printers

While typically more expensive than open 3D printers, the best enclosed 3D printers cover a wide range of prices. There are also a lot of different styles and levels of capability you can get across the varying enclosed 3D printers on the market. However, with the preceding list, you should be able to find something worthy of your needs.

Why trust us

Popular Science started writing about technology more than 150 years ago. There was no such thing as "gadget writing" when we published our first issue in 1872, but if there was, our mission to demystify the world of innovation for everyday readers means we would have been all over it. Here in the present, PopSci is fully committed to helping readers navigate the increasingly intimidating array of devices on the market right now.

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Looking for the best enclosed 3D printers to take your projects to the next level? Check out our favorites for a range of budgets and needs.

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Mind the trust gap: Data concerns prompt customer caution over generative AI

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A general lack of trust in data security and privacy is holding organizations back from going all in with generative artificial intelligence.

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How intelligent purely LLM-based systems can become remains an open question. Ever-larger training data sets and more-sophisticated architectures might yield more-robust reasoning capabilities and other features of cognition. "Models get more capable with scale," says Pavlick. She has been impressed with the progress LLMs have made in mastering challenging tasks such as syntax. "For a while, that was one of those holy grails of abstract reasoning," she says.

But Marcus is sceptical of how much further this framework can be pushed. "Deep learning is hitting a wall," he says. "We need new ideas." These fresh strategies will lead to further revisiting of assessment and benchmarking, just as rapidly improving LLMs have required.

Evaluating cognitive and reasoning capabilities will also almost certainly be a core component of efforts to implement national or global regulation of AI systems. Calls for such oversight have been steadily growing both in and outside the field. Some people cite the desire to stave off the perceived threat of an artificial super-intelligence, but many more are principally concerned with the more fundamental danger of pushing an already powerful but error- and abuse-prone technology into mainstream use.

"I'm not in the camp of people who think we're looking at an existential crisis in the medium term," says Pavlick. "But I don't like the idea of deploying things en masse that we don't understand." A well-validated battery of assessment tools could reveal the frontiers of an AI system's cognitive capacity, and how far it can be pushed before it starts to produce incorrect or otherwise harmful results. "I'm very interested in this idea of standard-setting and auditing organizations," says Bowman. However, he also cautions that there will inevitably be surprises with a system as complex and poorly-understood as an AI algorithm. "I think the thing that is hardest to say is, 'I'm confident the model won't do X,'" says Bowman.

doi: https://doi.org/10.1038/d41586-023-02822-z

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As debate rages over the abilities of modern AI systems, scientists are still struggling to effectively assess machine intelligence.

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In the rapidly evolving landscape of AI language models, two contenders stand out for their blend of capability and safety: Anthropic's Claude 2 and OpenAI's GPT-4. While both models aim to provide a wide range of functionalities, from answering questions to generating content, they diverge significantly in their approaches to safety, scalability, and application. Claude 2, developed by a company founded by ex-OpenAI employees, focuses heavily on creating a "helpful, harmless, and honest" AI, whereas GPT-4, OpenAI's latest offering, leans more towards advanced reasoning capabilities and a broader scope of applications, including multimodal functionalities.

Claude 2, although not as powerful as ChatGPT-4, has carved a niche for itself by prioritizing safety and ethical considerations. It employs various safety guardrails and a second AI model, Constitutional AI, to mitigate issues related to bias and toxicity. This makes Claude 2.0 an attractive choice for organizations and platforms that prioritize safety and ethical AI usage. On the other hand, GPT-4's selling points include its advanced reasoning capabilities and a more extensive range of functionalities. Trained on Microsoft Azure's AI-optimized infrastructure, it outperforms most other models, including its predecessor ChatGPT, in standardized tests and professional benchmarks.

Both models have found their way into real-world applications, with Claude 2 being integrated into services like Notion AI and DuckDuckGo's DuckAssist, and GPT-4 available through ChatGPT Plus and as an API for developers. As Claude 2.0 aims for a global expansion, and GPT-4 continues to break new ground in creative and technical tasks, the competition between these two models represents the broader contest between safety and capability in the AI industry.

What is Claude 2.0

Claude 2.0 represents an ambitious venture in the landscape of AI development, conceived and nurtured by Anthropic, an AI research company with a focus on safety. Founded in 2021 by former OpenAI employees, Anthropic's agenda is clear: to engineer AI models that are not only efficient but also secure and ethical. Claude 2.0 is the bedrock upon which this vision is being realized.

First and foremost, Claude 2.0 is an integral component of Anthropic's AI chatbot, Claude. It is designed to be a multi-functional entity capable of writing, answering questions, and collaborating with users. While it may not match the capabilities of GPT-4, Claude 2.0 has proven its mettle by outperforming most other AI models in standardized tests. This places it in a unique position in the AI market, where it combines moderate computational power with heightened safety measures.

Claude 2 vs ChatGPT-4

Other articles you may find of interest on the subject and comparisons of Claude 2 AI large language model :

This safety-centric approach is evident in Claude's integration into various platforms. In early 2023, Claude was incorporated into popular services such as Notion AI, Quora's Poe, and DuckDuckGo's DuckAssist. These strategic partnerships not only extend Claude's functionalities but also underscore Anthropic's commitment to providing safe and efficient AI solutions.

The Claude chatbot has been released in open beta in the U.S. and the U.K., with global expansion plans on the horizon. The primary aim here is to fulfill Anthropic's vision of a "helpful, harmless, and honest" large language model. To this end, the company employs multiple layers of safety guardrails designed to minimize issues related to bias, inaccuracy, and unethical behavior. An additional layer of scrutiny comes from Anthropic's second AI model, Constitutional AI, which works in tandem with Claude 2.0 to discourage toxic or biased responses.

The safety-first approach extends beyond mere programming. Anthropic's pre-release process includes " red teaming," a methodology where researchers deliberately attempt to provoke unsafe responses from Claude. This allows the team to identify vulnerabilities and implement safety mitigations proactively.

Being a public benefit corporation, Anthropic has the leeway to prioritize safety over profits. This positioning also allows them to advocate for AI safety while maintaining commercial competitiveness. The company's CEO believes that for Anthropic to be a genuine advocate for AI safety, it must also be a market competitor that influences others to raise safety standards. In line with this, Anthropic has taken steps to engage with policymakers. They have briefed U.S. President Joe Biden at a White House AI summit and committed to providing the U.K.'s AI Safety Taskforce with early access to their models.

Claude 2.0 is engineered to handle up to 100K tokens per prompt, which is equivalent to around 75,000 words. It is trained on data up to early 2023, making it relevant and updated. Claude 2.0 serves as a beacon in AI development, illuminating the path towards safer, more ethical AI solutions. With its moderate capabilities yet robust safety measures, Claude 2.0 stands as a testament to Anthropic's dedication to aligning technological prowess with ethical responsibility.

What is ChatGPT-4

GPT-4 stands as a pinnacle in OpenAI's ongoing efforts to advance the field of deep learning. As the most sophisticated system from OpenAI to date, GPT-4 has made a significant leap over its predecessors, particularly ChatGPT, in terms of reasoning capabilities, safety measures, and utility across various applications.

At its core, GPT-4 is a large multimodal model capable of handling both text and image inputs, emitting text outputs that often exhibit human-level performance on professional and academic benchmarks. This expansive ability makes it a versatile tool used by organizations worldwide to innovate across different sectors, from content creation to technical problem-solving.

The training infrastructure behind GPT-4 is equally impressive. Utilizing Microsoft Azure's AI-optimized supercomputers, OpenAI ensures that GPT-4 is not just powerful but also globally accessible. Azure's capabilities allow the system to be delivered to users around the world efficiently, further democratizing access to advanced AI.

ChatGPT Plus

When it comes to availability, GPT-4 is accessible through ChatGPT Plus and also as an API for developers. This dual accessibility ensures that both individual users and organizations can integrate GPT-4 into their workflows or services, making it a versatile tool for a wide array of tasks. From generating and editing creative content like songs and screenplays to performing complex problem-solving, GPT-4 is more creative and collaborative than ever before.

One of the standout features of GPT-4 is its advanced reasoning capabilities. Following the developmental trajectory from GPT to GPT-3, OpenAI has continued to invest in leveraging more data and computational power to create a language model that scores higher in approximate percentiles among test-takers. This level of sophistication enables GPT-4 to solve difficult problems with greater accuracy, aided by its broader general knowledge base.

Safety

Safety and alignment have been central to GPT-4's development. OpenAI spent six months ensuring that GPT-4 is safer and more aligned with human values. Compared to GPT-3.5, GPT-4 is 82% less likely to respond to requests for disallowed content and 40% more likely to produce factual responses, based on internal evaluations. While it still has limitations, such as social biases and susceptibility to adversarial prompts, OpenAI is committed to continuous improvements.

In casual conversations, the distinction between GPT-3.5 and GPT-4 might be subtle. However, the difference becomes evident when tasks increase in complexity. GPT-4 is more reliable and capable of handling nuanced instructions, making it a superior choice for more sophisticated requirements.

To empirically understand the capabilities and limitations, OpenAI conducted tests on various benchmarks, such as simulating exams originally designed for humans. These evaluations were carried out without specific training for these exams, making the results representative of the model's generalized capabilities.

GPT-4 serves as a monumental step in OpenAI's mission to scale up deep learning. With its advanced reasoning capabilities, safety measures, and versatility, GPT-4 is shaping up to be an indispensable tool in the advancement of AI applications across various domains.

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Claude 2 vs ChatGPT-4 results comparison test

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Claude 2 vs ChatGPT-4 which is best at certain tasks, prompts and requests? This comparison guide provides more insight into both and how

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This quick guide will give you step-by-step instructions on how to fine tune the OpenAI ChatGPT API so that you can tailor it to specific needs and applications. Fine-tuning a large language models becomes particularly relevant when you encounter limitations using simple prompting.

For example, if the prompts you are using to direct the model's behavior are not eliciting the desired responses or are becoming too cumbersome, fine-tuning offers a more tailored approach. Prompts can be limited in their ability to dictate the model's outputs; they might not fully capture complex requirements or might become too long and unwieldy to manage. In such scenarios, fine-tuning can help customize the model's behavior more effectively.

Fine-tuning OpenAI GPT

Another reason to consider fine-tuning is when you require the model to adhere to a specific style or tone consistently. While prompts can guide the model in a general direction, they may not ensure uniformity across multiple interactions. For instance, if you're aiming to have the model generate content that aligns with a particular brand voice or follows a specific formatting structure, fine-tuning allows for more reliable and consistent outputs in those regards.

However, it's essential to recognize where fine-tuning falls short. If your primary need is to have the model memorize specific data, fine-tuning may not be the optimal solution. Large language models are not designed to reliably store and retrieve exact data. In such cases, using a vector embedding database for information retrieval or incorporating the necessary data directly into the prompt could be more effective strategies. By understanding these considerations, you can make a more informed decision about whether and when to fine-tune your large language model.

How to fine tune ChatGPT API

Other articles you may find of interest on the subject of fine tuning large language models for AI applications :

Preparing to fine tune a large language model

Optimize Your Prompt: The first step is to optimize the prompt you're using with the base model. Ensure you've identified the limitations or issues that remain after prompt optimization.

Data collection

Create Diverse Examples: Prepare a dataset consisting of diverse sets of demonstration conversations that resemble the scenarios the model will face in production.

Format the Dataset: Ensure that the dataset aligns with the Chat completions API format, where each message in a conversation has a role ("system", "user", or "assistant"), content, and optionally a name.

Address Problematic Cases: Include examples where the base model does not behave as desired, providing the ideal responses in the dataset.

Include Best Practices: Integrate the best instructions and prompts that you've found effective before fine-tuning into every training example.

Training considerations

Be Mindful of Repeated Instructions: If you shorten repeated instructions or prompts, be aware that the model may still behave as if those instructions were fully included.

Data Volume: While a minimum of 10 examples is required for fine-tuning, better performance is typically achieved with 50 to 100 examples. Start with at least 50 well-crafted demonstrations for initial training.

Assessment and iteration

Rethink if Necessary: After fine-tuning, if you see no improvement, consider revisiting the task setup or restructuring the data before scaling up the example set.

Split the Dataset: Divide your initial dataset into training and test portions for better evaluation.

Submit Fine-Tuning Job: Use both the training and test files when submitting the fine-tuning job to OpenAI. This provides training and test statistics, giving you an initial signal of how much the model has improved.

pre-submission checks

Data Formatting and Validation: Before you submit the fine-tuning job, run a simple Python script to check for data formatting errors, review token counts, and estimate the cost of the fine-tuning process.

Testing and evaluation

Early Test Set Construction: Create a test set early in the process, as it will be useful for evaluating the performance of the fine-tuned model after training is complete.

By following these steps, you can aim for a more effective fine-tuning process, ensuring that the model better aligns with your specific requirements and use-cases. Full instructions from OpenAI on how to train its ChatGPT API are available on its official website for further reference.

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How to fine tune OpenAI ChatGPT API step-by-step

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Learn how to find tune the OpenAI ChatGPT API step-by-step preparing the data and taking into consideration training requirements before

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Researchers have identified a protein that's critical to the development of skeletal muscle mass and strength and the tissue's ability to metabolize glucose. They say their findings may lead to treatments for the muscle wasting that can occur in disease and as a result of aging.

Skeletal muscles are necessary for producing movement, sustaining body posture and position, maintaining body temperature, storing nutrients, and stabilizing the joints. With training, skeletal muscle can be significantly improved, however, aging and extended periods without exercise can lead to wasting, otherwise known as atrophy.

Two types of fibers make up skeletal muscle: 'slow' (or type 1) and 'fast' (type 2a, 2x and 2b). Type 1 fibers have a slow contraction speed and fatigue resistance (think long-distance endurance activities like marathon running), whereas type 2 fibers are prone to fatigue but have a high contraction speed and strength (sprinting or weightlifting). From a metabolic standpoint, type 1 and type 2a fibers consume more oxygen.

In a new study, researchers from the Tokyo Metropolitan University took a deep dive into how skeletal muscle mass and strength are regulated, including the metabolic processes that drive it, and discovered the important role played by the protein Musashi-2 (Msi2).

Msi-2 is an RNA-binding protein that regulates genes involved in cell development and differentiation, although its function differs between organs. Originally, it was discovered in neural cells, as an essential factor for normal brain development. Recently, Msi2 was found in skeletal muscle cells and involved in forming muscle tissue, called myogenesis.

The researchers took calf muscle tissue samples from mice - those who'd had the Msi2 gene knocked out and those who hadn't - and isolated the myofibers, the cellular elements that muscle tissue is made of. They found that the muscles of the Msi2 knockout mice had significantly reduced mass, less contractile strength and a whitish color instead of the normal red. Muscle tissue's red color comes from the type 1 fibers, which are rich in mitochondria and myoglobin, an iron- and oxygen-binding protein.

Examining the tissue under a microscope, the researchers saw that the reduced mass was due to a decreased number of type 2a fibers. They also found that the muscles of the Msi2 knockout mice metabolized glucose less effectively, similar to what happens in diabetes. Skeletal muscle is the primary tissue for maintaining whole-body glucose control, where insulin facilitates glucose uptake from the circulation into the muscles to be used as an energy source.

From their findings, the researchers concluded that Msi2 regulates proteins associated with glucose metabolism and controls the proportion of different muscle fiber types in skeletal muscle tissue.

"The mice lacking Msi2 have fewer type 2a fibers and show muscle atrophy as well as decreased strength in soleus [calf] muscles," said the researchers. "Even though glucose transport capacity was not changed significantly, total glucose disposal capacity in skeletal muscle was decreased by the loss of muscle mass in Msi2 KO [knockout] mice."

The researchers say their findings may lead to therapies targeting type 2a muscle fibers to combat muscle atrophy and develop ways of improving muscle strength.

The study was published in The FASEB Journal.

Source: Tokyo Metropolitan University via EurekAlert!

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Protein linked to muscle development could be new atrophy treatment target

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Researchers have identified a protein that's critical to the development of skeletal muscle mass and strength and the tissue's ability to metabolize glucose. They say their findings may lead to treatments for the muscle wasting that can occur in disease and as a result of aging.

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Everything you need to know about quantum physics (almost)

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Quantum mechanics is a mind-bending theory with dead-and-alive cats and particles in two places at once.

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Long before Apple's Vision Pro headset made its debut, there was rampant speculation that the company's wider augmented reality (AR) efforts were part of a larger project toward building the then-mysterious device. Now, it seems that at least one of those technologies was built with Vision Pro in mind.

I recently interviewed Susan Prescott, Apple's vice president of Worldwide Developer Relations, and Steve Sinclair, senior director of product marketing for Apple Vision Pro, to find out how the company courted developers while prepping the headset. In the course of that interview, Sinclair shed some light on how Vision Pro intertwined with the company's ARKit developer framework.

Throughout my talk with Prescott and Sinclair, both made repeated references to ARKit, Apple's framework for building AR experiences. Prescott said it was "foundational" for allowing people to build content for Vision Pro. When discussing how Apple adapted existing tools for its headset, Sinclair stated that "ARKit on iPhone and on iPadOS allowed us the opportunity to learn from developers and from ourselves on how best to implement these things on a platform like Vision Pro."

Was ARKit specifically built with Vision Pro in mind, I asked, or did its development come about separately and subsequently?

"We'll just say in conjunction" was Sinclair's response.

Sinclair's answer seems to imply that, at a minimum, Vision Pro was a consideration in the development of ARKit, if not the main driving force behind its creation.

ARKit's secret purpose

When Apple revealed ARKit as part of iOS 11 in 2017, it explained that the tool would allow developers to "build detailed and compelling virtual content on top of real-world scenes for interactive gaming, immersive shopping experiences, industrial design and more." Looking back, that seems like a description ripe for Vision Pro as much as it does the iPhone or iPad.

We already know that Vision Pro has been in development since at least 2007, the date Apple provisionally applied for a very early headset patent. In the intervening 16 years, there have been many other technologies that Apple ostensibly made for different devices that could also have been created with Vision Pro in mind.

LiDAR, for instance, has been heavily promoted as a way to enjoy AR experiences using an iPhone or an iPad Pro, but it also features prominently in Vision Pro. Numerous patents registered over the years, from extending a Mac's display into virtual space to in-air MacBook keyboards, could all have been disguised Vision Pro technologies.

That's unsurprising given Apple's famous tight-lipped reticence, and it's interesting to see the suggestion that ARKit has always had a secret secondary purpose. What other seemingly innocuous techs could find their way into future Apple devices? Only time will tell.

Editors' Recommendations

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Apple's foundational Vision Pro tool was built 6 years ago | Digital Trends

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Apple's ARKit developer framework was made 'in conjunction' with its Vision Pro headset, suggesting the tech had a secret purpose when it launched in 2017.

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Slow and steady wins the race: With big-name companies like Microsoft and Google vocally throwing their weight and money into the conversational AI market and releasing large language models based on OpenAI's work, it might be easy to write Apple off as uninterested or too far behind to matter. However, it is too early to write Apple off just yet.

The Information notes that Apple is working on several AI projects, increasing budget expenditures to "millions of dollars a day." It currently has resources focused on a conversational model, an image generation system, and a multimodal AI that handles text and visual data.

Senior Vice President of Machine Learning and AI Strategy John Giannandrea heads up development on the language model. Apple initially hired Giannandrea to improve Siri, so it seems probable that Cupertino's AI assistant will be the primary benefactor of Apple's LLM research.

The company will likely blend all its AI systems to accomplish various tasks through voice commands. Training and integrating different AIs is expensive and time-consuming, which would explain the perceived disinterest. However, while everybody else is launching and patching models with subpar performance, Apple is patiently building something that will outperform them and offer more than just chatbot functionality.

The Information notes that Apple's largest foundational AI model is "Ajax GPT." It is supposedly already more powerful than OpenAI's GPT-3.5. Ajax has over 200 billion parameters, 25 billion more than GPT-3.5 but far short of GPT-4's 1.7 trillion.

Another reason not to count Apple out of the race is its two-billion+ user base. Leveraging a comprehensive blended AI system that exceeds performance expectations set by Bing and Bard and putting it into the hands of two billion users virtually overnight could quickly leapfrog Apple to the lead in the race.

Apple has not announced anything regarding its AI efforts. As usual, the Cupertino tech titan likes to keep the development of its products under wraps until the last second. So, there is no way to guess when we could see an LLM-driven Siri commanding other complicated AI tasks on any Apple platform.

However, it is most assuredly coming. The company is not one to dump hundreds of millions per year into a project, never to have it materialize, no matter how long it takes. The Apple Vision Pro is a perfect example of that slow-burn methodology.

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While others rush to be first, Apple has quietly spent 'millions of dollars a day' on multiple AI projects

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The Information notes that Apple is working on several AI projects, increasing budget expenditures to "millions of dollars a day." It currently has resources focused on a...

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Math Reveals Secrets of Synchronization in Complex Systems - Neuroscience News

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These findings could revolutionize our understanding of everything from power grid stability to brain functions and social media dynamics.

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Phone Link is a handy Windows feature that allows you to access smartphone calls, messages and notifications from the comfort of your Windows 11 PC.

Up until recently, the feature was only available on Android devices. Now, Microsoft has made it possible to link your Windows desktop or laptop with an iPhone instead. The update opens up this feature to those not yet committed to a single ecosystem, as well as for anyone who might carry an iPhone for personal use and a Windows device for work. All you need to get started is a Windows 11 PC and an iPhone running iOS 14 or higher.

Keep reading to learn how to set up Phone Link on your iPhone right now.

What you'll need:

A Windows PC running Windows 11

An iPhone running iOS 14 or higher

The Short Version

1. Open Phone Link on your Windows PC

2. Choose iPhone

3. Scan the QR code with your iPhone

4. Tap Open

5. Tap Continue

6. Allow Link To Windows to use Bluetooth

How to use Phone Link for iPhone

Troubleshooting

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Follow this guide to learn how to set up Phone Link and access calls, messages and notifications from your iPhone directly on your Windows PC

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You may have experimented with ChatGPT, and found it to be a useful tool on its own for work, school, or personal projects. But if you take the opportunity to study even basic coding, you can expand what you can do with AI simply by customizing your own chatbot.

Start your coding education during this back-to-school sale and get the 2023 Ultimate AI ChatGPT and Python Programming Bundle for only $40.

Code your own AI chatbot with Python

This AI programming bundle primarily focuses on cultivating your skills with Python. Courses start at the very beginning and may be most useful to learners with little coding experience. If Python is a new language to you, start with Python 3: From ZERO to GUI Programming. This course gives you nine hours of programming tips to help you work through the other eight Python courses. Those introduce new skills like PDF handling and data analysis. One even gives you the chance to program an escape room.

Courses are taught by Dr. Chris Mall, who has a masters degree in IT and a Ph.D in Computer Science. He also teaches a course that introduces you to the theory behind AI and shows you how to program a robot. From there, you can apply your skills in two courses that walk you through the process of crafting a ChatGPT AI bot. Even if you aren't a coding expert, these courses will show you how to use ChatGPt to generate new code for you.

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Back-to-school sales doesn't just mean going back to a classroom. Take control of your own education and learn to code and build your own AI chatbot.

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Create your own ChatGPT AI bot with this course bundle

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More Men Are Using AI To Make Money: 8 Ways Women Can Get Started — and Get Ahead

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AI can help you make money no matter your gender.

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UGOT kit turns you into the maker of seven robots

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In recent years we’ve seen quadruped robots, self-balancing robots, and omnidirectional robots. Should you want one of your own, the UGOT Robotic Kit now allows users to build all of those bots and more.

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Didem Mente/Anadolu Agency via Getty Images

I was poking around Stack Exchange the other day (as one does), and I found an interesting thread about ChatGPT and the game "20 Questions." The original poster asked why ChatGPT fails at such a simple game. The discussion went on for quite some time, moving into various tangential directions (as such discussions do), and linked to an academic paper and a Medium post that researched the process in depth.

This got me thinking. Just how well would ChatGPT do with such a game? I decided to play the exact same game with both GPT-3.5 and GPT-4. In my first run, both went off on similar tangents, but GPT-4 did succeed in making its guess.
Also: The best AI chatbots of 2023: ChatGPT and alternatives
I started with a simple prompt for each version:

Do you know how to play the game "20 questions"?

When both versions answered in the affirmative, I started the games at the same time, in separate tabs and separate sessions. The object I had in mind was a mailbox. I left it a bit vague as to whether it's a mailbox attached to a house or one that's free-standing on the street. As long as the AI picked "mailbox," we'd be good.

20 Questions with GTP-3.5

I began with this starting prompt:

You be the questioner. I'm thinking of something.

It answered with this question: "Let's begin! Is the thing you're thinking of a tangible object that you can physically interact with?"

I answered, and I also gave it one additional instruction: to number its answers. This didn't work well. As we went through the questions, the AI called the second question "1". When I corrected it, the bot asked a new question, and called that "1". Eventually, it did ask 21 questions, thinking it had only asked 20.
Also: How this simple ChatGPT prompt tweak can help refine your AI-generated content
The most interesting detail was this question, which was the second question it asked: "Is the thing you're thinking of commonly found indoors?"

When I said "No," the chatbot went on to ask more questions. Here they are. A few could be related to indoor items, like a pen or a pencil, but we do also use writing implements outside. Here's the full set of questions it asked:

1. Is the thing you're thinking of a tangible object that you can physically interact with?

2. Is the thing you're thinking of commonly found indoors?

3. Is the thing you're thinking of something that is alive or has ever been alive?

4. Is the thing you're thinking of primarily used for recreational purposes?

5. Is the thing you're thinking of something that is man-made?

6. Is the thing you're thinking of smaller than a breadbox?

7. Is the thing you're thinking of associated with communication?

8. Is the thing you're thinking of typically found in an office or workspace?

9. Is the thing you're thinking of a form of electronic device?

10. Is the thing you're thinking of a writing instrument, like a pen or pencil?

11. Is the thing you're thinking of related to entertainment, such as a game or a toy?

12. Is the thing you're thinking of related to transportation or travel?

13. Is the thing you're thinking of a tool that is used for practical purposes?

14. Is the thing you're thinking of commonly associated with construction or manual labor?

15. Is the thing you're thinking of something that people often use in their daily routines?

16. Is the thing you're thinking of a household item?

17. Is the thing you're thinking of related to personal grooming or hygiene?

18. Is the thing you're thinking of a type of food or beverage?

19. Is the thing you're thinking of a tool used in artistic or creative activities?

20. Is the thing you're thinking of associated with sports or physical activities?

21. Based on the information provided, I'll make my final guess: Is the thing you're thinking of a clock or a timepiece?

Using the GPT-3.5 large language model, it failed. Now, let's take a look at GPT-4.

20 Questions with GPT-4

I started the game the same way. This time, ChatGPT put a number at the beginning of each question without my needing to prompt it to do so. The problem? It put "1." before every single question. You win some, you lose some.

Here are the questions GPT-4 asked:

1. Is the thing you're thinking of typically found indoors?

2. Is it something living?

3. Is it larger than a breadbox?

4. Is this object primarily used for recreational purposes?

5. Is the object man-made?

6. Is it a type of vehicle or transportation method?

7. Is the object electronic or does it require power to function?

8. Is it made primarily of metal?

9. Is this object typically found in most households?

10. Is it used in the kitchen or for cooking?

11. Is it used for storage or organizing items?

12. Can it be worn or is it an article of clothing?

13. Is it primarily used for cleaning or maintenance?

14. Is it decorative in nature? Like something you'd put on display?

15. Would it commonly be found in an office or study?

16. Is it something you'd find in a bedroom?

17. Is it associated with any specific outdoor activities or hobbies?

18. Is it commonly made of wood?

19. Would it be typically used in a bathroom or related to personal hygiene?

20. Is it something that's usually used for sitting or for support, like a chair or a bench?

Also: How to use ChatGPT to make charts and tables
Technically, it used up its 20 questions. But then it delivered this statement:

Yes, it was a mailbox! Then I asked it to show its work. Here's what it responded with:

GPT-3.5's turn to answer questions

I decided I'd turn the tables on the game and see how it did if I were the questioner. Here is my prompt:

Okay, this time you think of something and I'll ask the questions.

And here are my questions:

1. Is it commonly found outdoors?

2. Is it also found indoors?

3. Is it alive?

4. Does it use power?

5. Does it rely on digital technology?

6. Is its primary usage value delivered via a screen?

7. Is it primarily used for food preparation?

8. Is it primarily used for entertainment?

9. Is its primary usage value generated noise?

10. Is it portable?

11. Does it play only audio media?

12. Does it rely on external headphones, earbuds, or speakers?

13. Is it a portable music player or MP3 player?

As it turns out, I guessed it in 13 questions. The big clue to me was that it answered "no" to Question 6, "Is its primary usage value delivered via a screen?" and had previously answered "yes" to "Does it rely on digital technology?"
Also: 4 things Claude AI can do that ChatGPT can't
GPT-4's turn to answer questions

I tried again with GPT-4, and it stumped me. It picked a very creative object and I just didn't get it.

I should point out that right in the middle, at Question 15, ChatGPT Plus booted me for asking too many questions

It's quite annoying to pay $20/month for the privilege of being told I ask too many questions. I heard that enough when I was a kid. I certainly don't need to be scolded as an adult and a paying customer.

Here are the questions I asked:

1. Is this an object used primarily indoors?

2. Is it alive?

3. Does it use power?

4. Is it larger than a car?

5. Is it man-made?

6. Is it movable?

7. Is it used for yard work?

8. Is it used primarily by children?

9. Does it have wheels?

10. Is it located primarily on residential property?

11. Is it used as furniture?

12. Is it decorative?

13. Is it seasonal?

14. Is it meant to hold something?

15. How many questions are we at?

16. Does it display words or numbers?

17. Is it attached to a house?

18. Does it grow?

19. Is it smaller than a refrigerator?

20. Is it a planter?

Also: The 'Human or not' game is over: Here's what the latest Turing Test tells us
So what did the AI choose? A garden gnome. I have to give it up to the AI. That was fun and creative. The part that's truly interesting is how well the AI understands the type of challenge being presented. After the game, I gave it this prompt:

Show your work in determining what object to use

Here's what it replied:

What have we learned?

Let's recap some of what this experiment has taught us. Here's a quick lightning round of thoughts:

For something described as just predicting the next word in a sequence, the large language model has a very solid grasp of what this game is and how it works.

This clearly differs from the experience of the OP (original poster) on Stack Exchange. It's likely ChatGPT improved considerably in the three months since the "it fails" statement was posted, and, without a doubt, ChatGPT Plus raises the "intelligence" level yet another notch.

The GPT-3.5 and GPT-4 models do differ. The paid-for GPT-4 model does have a better grasp of object relationships.

GPT-4 is also more sophisticated and creative compared to GPT-3.5 when it's the player choosing the object. A garden gnome was an inspired object choice.

Playing 20 Questions with ChatGPT can suck when you're trying to guess an answer, and you go into "too-many-questions" time out.

All that said, I can definitively conclude that ChatGPT is capable of handling the game of 20 Questions. It appears to understand object relationships well enough to ask good questions, answer questions appropriately, and pick challenging objects.
Also: 7 advanced ChatGPT prompt-writing tips you need to know
Go ahead, pick an object, and share what your results were with ChatGPT in the comments below.
You can follow my day-to-day project updates on social media. Be sure to subscribe to my weekly update newsletter on Substack, and follow me on Twitter at @DavidGewirtz, on Facebook at Facebook.com/DavidGewirtz, on Instagram at Instagram.com/DavidGewirtz, and on YouTube at YouTube.com/DavidGewirtzTV.

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ChatGPT and I played a game of 20 Questions and then this happened

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I tested out how GPT-3.5 and GPT-4 can handle object relationships. The short answer: surprisingly well.

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Apple is quietly spending millions on AI to make Siri as smart as ChatGPT

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Apple is quietly spending millions on AI to make Siri as smart as ChatGPT

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Apple is spending millions of dollars a day to train its large-language models, and it might be readying to tackle OpenAI ChatGPT.

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Apple today released a new update for Safari Technology Preview, the experimental browser Apple first introduced in March 2016. Apple designed the ‌Safari Technology Preview‌ to test features that may be introduced into future release versions of Safari.

‌Safari Technology Preview‌ 178 includes fixes and updates for Web Inspector, CSS, CSS Container Queries, JavaScript, SVG, Accessibility, Media, IntersectionObserver, Web API, and WebGL.

The update now features content coming in Safari 17 alongside macOS Sonoma. On Sonoma, the browser offers Profiles for separating browsing data like History and Favorites, web apps, and improved private browsing mode. Features for all operating systems include Feature Flags (replacing Experimental Features), a redesigned Develop menu, Live Text support for vertical text recognition in images and videos, HEIC support, and JPEG XL, a new image format with an improved compression algorithm for better image quality at smaller file sizes than JPEG.

The current ‌Safari Technology Preview‌ release is compatible with machines running macOS Ventura and ‌macOS Sonoma‌, the latest version of macOS that Apple is beta testing right now.

The ‌Safari Technology Preview‌ update is available through the Software Update mechanism in System Preferences or System Settings to anyone who has downloaded the browser. Full release notes for the update are available on the Safari Technology Preview website.

Apple's aim with ‌Safari Technology Preview‌ is to gather feedback from developers and users on its browser development process. ‌Safari Technology Preview‌ can run side-by-side with the existing Safari browser and while designed for developers, it does not require a developer account to download.

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Apple Releases Safari Technology Preview 178 With Bug Fixes and Performance Improvements

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Apple today released a new update for Safari Technology Preview, the experimental browser Apple first introduced in March 2016. Apple designed the...

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What is gravity? A guide to nature’s most mysterious force (and what we still don’t know)

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Everyone knows that what goes up must come down. But why? Gravity, it turns out, is full of surprises…

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A closer look at e/OS: Murena’s privacy-first ‘deGoogled’ Android alternative | TechCrunch

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Murena is in the business of deGoogling Android smartphones in the name of privacy. The French/European firm has been doing this for around five years, as We recently got our hands on a Fairphone 4 running Murena’s tracker-blocking /e/OS. Our curiosity was piqued to see an alternative OS running on…

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Why your thoughts may not be private for much longer

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We need to rethink our human rights for the wearable tech of tomorrow, according to neurotechnology ethics expert Prof Nita Farahany.

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Siri is getting big upgrades in iOS 17. Apple makes your interactions with the digital assistant smoother and more naturalistic. Barriers are removed, and we get some new brilliantly realistic voice models to test drive.

Siri can also turn online articles into mini audiobooks and manages to do a remarkably good job of it, too.

Our digital assistant in iOS 17 is more agnostic about the messaging app you use and becomes the sort of steward of a brand-new iPhone feature that turns your phone into a bedside smart display in waiting.

There's a lot to dig into here, and I'm going to take it upgrade by upgrade. I tested them all first-hand with a beta release of iOS 17, while the full public version will be out in September. Strap in.

Dropping the "Hey"

Talking to Siri gets a little simpler in iOS 17. The default wake word is now "Siri" or the classic "Hey Siri." "Hey" is totally optional.

This is something rival Alexa has had for ages. You can even call Amazon's digital assistant "Ziggy" if you like.

You don't have to do anything to make your iPhone respond to simply "Siri," per the version of iOS 17 I'm using. But here's how you check your setting if it doesn't work for you, as "Hey Siri" alone is still an option.

New British voices

iOS 17 adds two great new "British" voices, ones that are miles more realistic-sounding than the original pair. They are called, imaginatively, British 3 and British 4.

One sounds like a young woman with a moderately neutral Southern English accent. There's just a slight regional twang. The other has a modern London British accent and sounds extremely lifelike to our ears. Here's how to switch to one of the new voices.

1. Open Settings

2. Select Siri & Search

3. Tap Siri Voice

4. Select British under the Variety header

5. Select Voice 3 or Voice 4 and wait for the download to complete

Siri can read articles

These new voices can get a great workout in another of iOS 17's new Siri features, the ability to read out entire articles in the Safari browser.

This is separate from the existing voice-driven Speak Screen accessibility feature, which can currently only use Apple's library of rudimentary-sounding digital voices rather than the far more naturalistic Siri ones.

Here's how you do it.

1. Say Hey Siri (or simply Siri if you've switched that wake word on)

2. Say "read this page" when on a suitable article page

This will only work on pages that have a Reader View version available. It's a style of formatting that gets rid of everything, bar the actual webpage key content, the words, and images, which makes it much easier for Siri to read out an article as a human might.

You'll see a "Reader Available" prompt in the web address bar when on a page with such formatting.

Guess what? All our articles offer Reader formatting so you can try this one out at iMore.

Back-to-back requests

In a move intended to make Siri feel more natural to use, iOS 17 lets you make limited back-to-back commands rather than having to say "Siri" between each one.

This is not something you need to enable. It's just how Siri works now. However, there are limits.

Siri will only listen out for a follow-up command for a few seconds after the previous one is replied to, as you might expect.

Send messages more easily through multiple apps

This might be the most impactful but subtle Siri change in iOS 17. You can now change the app Siri uses to send messages, rather than it simply assuming you want Apple Messages unless explicitly stated.

Here's how it worked in the previous version. While you could specify sending a message through, say, WhatsApp when you made the command, if you didn't specify any platform, Siri would assume you just wanted to send one through Messages.

You'll now see an on-screen prompt when you dictate a message, one that lets you select the platform to use.

Siri in StandBy

StandBy is a brand-new feature for iOS 17. While not solely a Siri feature, the voice assistant has a major part to play here.

StandBy turns your iPhone into a mini smart display. It is enabled automatically when the phone is resting on its side in StandBy and is plugged in or wirelessly charging.

Where does Siri come in? You can ask Siri requests in Standby mode, even if the screen is off. These often include neat visual representations, too. Set a timer, and the screen will fill with color while the time runs out.

One more thing... does Siri get better in iOS 17?

My favorite changes in Siri aren't necessarily the most glossy ones. The progress we've been waiting for is all about the elements that make your interactions feel more natural and less stilted.

The back-to-back responses, the improved British voice models, and even the way Siri now provides a much more realistic-sounding way to read out web articles - all are important enhancements of how Siri feels to use.

Do I care about Standby too? Sure, but the highlight there has more to do with a whole other mode of operation the iPhone now has, while Siri just jazzes up that feature a bit. It may seem on the surface like a smart display alternative, but in person, I tend to treat Standby more like an elaborate desk or bedside clock.

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How to use iOS 17's new Siri features and upgrades

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A look at the improvements to Siri in iOS 17 and how to use them.

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One of the most highly anticipated features announced at WWDC back in 2021 was support for storing IDs in the Apple Wallet application. Touted by Apple as the last step before you are "fully free of your physical wallet," the feature is still only supported by a small number of states.

Nonetheless, there are now nearly 30 states working towards adopting digital IDs for citizens...

The TSA is currently running a pilot program for accepting digital IDs at a small number of airports. Apple has said that the TSA is "working to enable" airport security checkpoints as "the first place you can use your digital ID."

As it stands today, only four states have launched support for digital IDs via Apple Wallet on your iPhone and Apple Watch: Arizona, Colorado, Maryland, and Georgia. You can find more details on those states and the details of their implementations here.

Digital IDs are also currently in a pilot program in California, but the system does not integrate with Apple's system. Instead, the program is managed entirely via a standalone app.

According to data compiled by the Secure Technology Alliance, nearly 30 states are in the process of adopting mobile digital licenses. While this doesn't necessarily mean they will go on to support Apple Wallet's implementation of the feature, it means they are exploring the idea.

Here's the full list of those states:

Territories: Washington DC and Puerto Rico

According to the Secure Technology Alliance, to be included on the list a state has to meet at least one of the following criteria:

Interoperable availability across operating systems

Interoperable implementation in progress

Pilot Activities

Enacted legislation and/or study activity

Non-ISO standard implementation

Other mobile activity

The progress of these efforts varies from state to state. In some states, it's as basic as legislation being introduced in support of digital IDs. In other states, there's simply been "activity" regarding this adoption. Additionally, as we've previously seen with the rollout of the COVID-19 Exposure Notification platform, delays are to be expected anytime Apple works on a state-by-state basis with individual governments.

As a reminder, Apple's list of states includes Arizona, Connecticut, Georgia, Iowa, Kentucky, Maryland, Oklahoma, and Utah.

You can view a fully interactive map on the Secure Technology Alliance website right here, with more details on the status of these talks in the United States and Canada.

Follow Chance: Threads, Twitter, Instagram, and Mastodon.

FTC: We use income earning auto affiliate links. More.

Chance Miller @ChanceHMiller

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Here are the 25+ states exploring support for Apple's digital IDs in Wallet feature - 9to5Mac

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One of the most highly anticipated features announced at WWDC back in 2021 was support for storing IDs in the...

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Ketaki Bhojnagarwala/SlashGear

Live Captions are currently only available in English, and to use the feature, you'll need to set your device's primary language to English (U.S.) or English (Canada). The feature is available on the iPhone 11 and later models. On iPad, Live Captions are supported on the iPad Mini (5th-generation and later), iPad (8th-generation and later), iPad Air (3rd-generation and later), all iPad Pro 11-inch models, and iPad Pro 12.9-inch (3rd-generation and later).

Before getting started with using Live Captions in FaceTime, you'll need to enable the feature in settings. Here's how to do it:

You can tap Appearance to personalize Live Captions on your device by enabling bold text and tweaking the text size, color, background color, and idle opacity. The next time you start a FaceTime call, you might be prompted to download a language module for Live Captions. Once downloaded, the captions will automatically appear at the top of your screen. Live Captions are attributed to individual call participants in a group call, making it easy to follow the conversation. You can turn Live Captions on or off during a call by tapping 'i' in the top right corner of the FaceTime app and tapping the toggle next to Live Captions.

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The FaceTime Feature That'll Make It Easier To Follow Conversations - SlashGear

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Captions are a great way to make it easier to follow along with a movie or TV show, and now you can get the same thing during FaceTime calls.

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We have all been there. After automating all of your home's lighting, upgrading your thermostat, and deploying smart plugs across the house, there's always that one device that has to sit out because it relies on an old-school infrared remote.

If that sounds like you, you'll be happy to know that thanks to recent hardware and software releases, you can finally add your IR device to the Apple Home app without resorting to running a Homebridge or Home Assistant server. Whether it is an electric fireplace, air conditioner, or fan, we'll show you how.

What You'll Need

Since older IR devices lack direct Home app integration, adding them to your smart home requires more than just a scan of a pairing code. While the process isn't too complicated, you will need an additional piece of hardware and a third-party app to make the magic happen.

To start, you'll need a Home app-compatible hub, bridge, or gateway with IR capabilities. Available options include the SwitchBot Hub 2, the Aqara M2 Smart Hub, the Aqara Camera Hub G3, and the Nature Remo Nano.

This guide will cover the steps for the SwitchBot Hub 2 and the Aqara Camera Hub G3-which is similar to the M2 Smart Hub. Unfortunately, the Nature Remo Nano is exclusive to the Japanese market so we are unable to provide steps for that specific hub.

Next, you'll need to download and set up your hub of choice via the accompanying vendor app, then add it to the Home app. In some cases-like with the SwitchBot Hub 2-you'll need to enable Matter connectivity before adding it to Apple Home.

Finally, you'll need to ensure that all your devices are up-to-date. This means downloading and installing the latest software release for iOS on your iPhone and Apple Home Hub and applying any firmware updates for your IR hub.

How to Add an IR Device to Apple Home With the SwitchBot Hub 2

Before adding your IR devices via the SwitchBot Hub 2, there are a few things to keep in mind. First, SwitchBot's IR/Home app implementation does not work with learning functions-you'll need to choose your IR device from a list of vendors and model templates.

Second, the SwitchBot Hub 2 connects to the Apple Home app via Matter. If you haven't done so already, you'll need to add your Matter smart home sevice to Apple HomeKit before proceeding.

Last, adding your IR device consists of two parts: adding your IR device to the SwitchBot app and exposing it to Matter/Apple Home. To add your IR device to SwitchBot:

1. Launch the SwitchBot app.

2. Tap your SwitchBot Hub 2.

3. Tap Add remote control.

4. Tap a device type.

5. Tap Select Manually.

6. Choose the vendor for your device with a tap.

7. Tap Got it if the app finds multiple templates.

8. Tap a button to test IR compatibility or swipe to switch to another template.

9. Tap Save once you find a match.

10. Enter a name using the iOS keyboard and assign your device to a room.

11. Tap Save to complete the setup process.

With your IR device in the SwitchBot app, you can now expose it to the Apple Home app via Matter:

1. Launch the SwitchBot app.

2. Tap your SwitchBot Hub 2.

3. Tap the Settings button at the top of your screen.

4. Tap Matter Setup (Beta).

5. Tap Add next to Secondary Devices.

6. Tap your IR device to add it to Matter and Apple Home.

Once complete, your IR device will appear as a tile in the Home app just like all your HomeKit and Matter accessories. Just tap it to toggle your IR action or add it to Home app Scenes, Automation, or Groups.

How to Add an IR Device to Apple Home With the Aqara Camera Hub G3

Adding an IR device from an Aqara Camera Hub G3 to Apple Home consists of three main parts: adding the device, creating a scene, and making the scene available to Apple Home. Devices added via Aqara will appear just like scenes you create within the Apple Home app. To add your IR device:

1. Launch the Aqara Home app on your iOS device.

2. Tap Accessories on the navigation bar.

3. Tap your Camera Hub G3.

4. Tap the More... button near the top right corner of your screen.

5. Tap Function Setting.

6. Tap Infrared Remote Control.

7. Tap Add Remote Control.

8. Select a device type or Customize with a tap.

9. Tap the vendor for your device (skip if you chose Customize previously).

10. Follow the prompts by tapping the required buttons to test your IR device compatibility.

11. Enter a name for your device using the iOS keyboard and choose a location within your home.

12. Tap Next.

13. Customize your device's appearance, then tap Done to complete the setup process.

With your IR device added, it is now time to create a scene within the Aqara Home app:

1. Launch the Aqara Home app.

2. Tap Scene on the bottom navigation bar.

3. Tap the + button at the top of your screen.

4. Under the Add Action section, tap Add.

5. Tap your IR device.

6. Tap Remote control button.

7. Select a function (power, temperature, etc.) for your IR device.

8. Tap Save.

9. Customize your scene by entering a name and choosing an icon.

10. Tap OK to complete your scene.

The final puzzle piece is making your Aqara scene available to the Apple Home app.

1. Launch the Aqara Home app.

2. Tap Scene on the bottom navigation bar.

3. Tap the scene with your IR device.

4. Tap the More... button in the top right corner.

5. Tap Add to Apple Home.

6. Tap your Aqara Camera Hub G3.

7. Tap Done.

After a few moments, your Aqara scene will now be available in the Apple Home app. Due to limitations with IR devices, your scene will only appear in the Scenes area on the Home tab in the Apple Home app using this method. Simply tap it to toggle the action on your IR device.

Make Your Old Devices Smart With the Apple Home App

Now, with just a tap in the Home app or a shout to Siri, you can finally bring your older IR devices to life without fumbling with a remote. It's a quick and easy process that makes more devices smarter.

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How to Add an IR Device to the Apple Home App

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We'll show you how to bring old-school infrared-controllable devices into your smart home.

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I’ll never buy a 4K laptop and you shouldn’t either — here’s why

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Why pay extra for the privilege of squinting?

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Now that the Mac Pro has finally made the jump to Apple silicon, the next question is whether Apple will resurrect another pro favorite - will the iMac Pro make a return after more than two years in the wilderness?

Apple discontinued the 27-inch iMac in March 2021, arguably one of the best Macs and among the best all-in-one PCs in existence, which left pro buyers with fewer options when it comes to picking a desktop Mac. The Mac Studio arrived to try and fill the gap left by the iMac Pro, and it did so admirably, but there's something to be said about an all-in-one solution. Having to buy the Studio Display to go with the Mac Studio is a pain, and the alternatives are few for those who want 5K at around the 27-inch mark.

Right now, the only all-in-one option is the 24-inch iMac, a machine that few would argue is anything like a pro desktop machine. The M1 chip is fine, and the rumored M3 24-inch iMac will no doubt be even better. But at 24 inches, it's just too small for pro workflows. That's before we get into the low RAM ceiling and lack of CPU and GPU cores.

No, for videographers, photographers, and audio engineers, an iMac Pro would be a much better option. But will Apple bring it back? If so, what can we expect? The rumors have been sparse, which is a worry. But that doesn't mean that there haven't been some suggestions of a return to form with the possibility of an M3 iMac Pro.

M3 iMac Pro (2023): Cut to the chase

What is it? A return of the 27-inch iMac Pro

When is it available? Possibly towards the end of 2023 or early 2024

What does it cost? The iMac Pro has never been a cheap machine, but pricing is a big question mark if and when we get an Apple silicon version.

When will the M3 iMac Pro arrive? At this point, we aren't 100% sure that it ever will, but the well-connected Mark Gurman of Bloomberg fame has historically pointed to a 2023 release.

Gurman believes that the iMac Pro will be based on Apple's upcoming M3 chips, although it seems likely that it will use something other than the base silicon. That means M3 Pro and M3 Max at a minimum, and M3 Ultra at best.

Those three chips aren't expected to debut until the first months of 2024 though, likely inside updated 14- and 16-inch MacBook Pros. If that's the case then we should be looking to 2024 for this new iMac Pro. But with so much up in the air, it's hard to be sure.

It's worth noting that Gurman isn't alone in thinking that the M3 iMac Pro will make a return, though. Well-respected supply chain analyst Ming-Chi Kuo previously pointed to new Mac Pro and iMac Pro machines arriving in 2023. The former is already here of course, so will the iMac Pro join it before the new year?

M3 iMac Pro (2023): Price

The previous Intel iMac Pro started at a costly $4,999 with its Xeon processors and pro-grade RAM, but it could go all the way to more than $13,000 depending on the configuration chosen. Not quite Mac Pro money, but still a costly proposition.

How much an Apple silicon refresh would cost is anyone's guess right now. Using the Mac Pro as an example, we shouldn't expect it to get cheaper unfortunately. The M2 Ultra Mac Pro starts at $6,999, for example, whereas the old Intel machine started at $5,999. Add all of the best stuff and that price soon balloons to almost $54,000, but the fact that the M2 Ultra version starts at more than the old Intel model should give us an indication of what to expect.

The final price you pay for your M3 iMac Pro will depend on what upgrades you choose, like more RAM and SSD storage, but those hoping for a cheaper iMac Pro might be left disappointed.

(Image credit: Future)

M3 iMac Pro (2023): What to expect

While a refreshed 24-inch M3 iMac is very much expected to debut at a rumored October Apple event, things are much less certain when it comes to the iMac Pro.

One school of thought is that the combination of the Mac Studio and Studio Display is effectively the new iMac Pro, just not in all-in-one form. But with Gurman claiming that "Apple is working on a larger-screened iMac aimed at the professional market," there remains hope that an Apple silicon iMac Pro could grace the lineup once more.

What that would look like is another question. The 24-inch iMac comes in a handful of colorful finishes, but that's unlikely to be the route an M3 iMac Pro would take. Apple offers its pro Macs in more muted colors with the old iMac Pro only available in Space Gray. We'd suggest that's the route a new model would take, although there's always the option for Silver to match the MacBook Pro color options.

In terms of the overall design, the previous iMac Pro was very much based on the iMac of the time. It wouldn't take a huge leap to expect a new model to borrow from the 24-inch iMac's design, just with less yellow and green.

(Image credit: Apple)

Figuring out what is going on with the M3 iMac Pro is difficult because the leaks have been so few that it's difficult to know if it's even in the cards, let alone what it will have to offer. If it was going to arrive before the end of 2023, we would likely have heard more about it by now.

The fact that a new iMac Pro would surely use M3 Pro, M3 Max, or M3 Ultra chips also adds further fuel to the fire in terms of a 2024 release.

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Apple iMac Pro M3 (2023): all the latest news and rumors

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Now that we have an Apple silicon Mac Pro, it might be time for Apple to bring the iMac Pro back from the dead.

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Google Removes Controversial Chamet Live Video Chat App from Play Store for Violating UGC Policy

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Google removes controversial video chat app Chamet from the Play Store due to User-Generated Content policy violation, raising questions about similar apps’ fate.

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As a company, Magic Leap moved on from its first headset some time ago. Along with a new CEO came a major pivot. With the Magic Leap 2, the startup went all in on enterprise - a far safer and more lucrative bet than the fickle world of gaming.

Still, the Magic Leap 1 has continued to operate - good news for those who shelled $2,300 for the device when it finally arrived in the summer of 2018. At the end of next year, however, the augmented reality headset will effectively become a very expensive hunk of plastic and glass.

The well-funded firm alerted users via email that the system is being end-of-lifed when 2025 rolls around.

"[W]e are announcing that Magic Leap 1's end-of-life date will be December 31, 2024. Magic Leap 1 is no longer available for purchase but will continue to be supported through December 31, 2024," the company writes.

Shorter term, the product's various communications are being shuttered. The Magic Leap 1 Developer Forum and Discord channels are both being shuttered at the end of the month, while the company recommends people shift their business to the Magic Leap 2 board instead. Troubleshooting support and warranty claims will continue to be honored through 2024.

More details are offered in an FAQ.

When that date rolls around, however, cloud services, apps and general functionality will all effectively brick. Perhaps we'll see a homebrew community emerge, though the true number of devices out in the wild is hazy, at best. One report suggested that the headset had sold around 6,000 devices in its first year.

Much of that modest figure can be chalked up to pricing, along with the age-old issue of limited content. You can't, however, blame the technology. If AR's time ever truly comes, we can safely say that the Magic Leap 1 was ahead of it. And the device's sequel continues to build on that success.

From my conversation with the company, it's safe to say Magic Leap has no short-term ambitions to return to the consumer market. Maybe someday scale will bring the price down to a manageable level and enough developers will be entrenched in the ecosystem to offer something meaningful.

In the meantime, the ball is very much in Apple's court with the Vision Pro. While the software giant's spatial computing approach is fairly different than what Magic Leap had initially targeted, it's fair to say the two share common DNA. This is also a relatively rare instance where Apple entering the category doesn't suck the air out of the room for smaller competitors. If anything, the Vision Pro is a validation for AR's true believers.

I will be discussing Magic Leap's journey with CEO Peggy Johnson as part of the Disrupt Hardware Stage, later this month.

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Magic Leap's original headset will stop working at the end of 2024 | TechCrunch

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At the end of next year, Magic Leap's augmented reality headset will effectively become a very expensive hunk of plastic and glass.

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Yes, you can install ChatGPT locally on your machine. ChatGPT is a variant of the GPT-3 (Generative Pre-trained Transformer 3) language model, which was developed by OpenAI. It is designed to generate human-like text in a conversational style, and can be used for a variety of natural language processing tasks such as chatbots, language translation, and question answering.

To install ChatGPT, you will need to install the OpenAI API client and set up an API key. You will also need to install the Python programming language and the required libraries.

1. Install Python 3.7 or later. You can download Python from the official website (https://www.python.org/) and follow the instructions to install it on your machine.

2. Install the OpenAI API client. You can do this by running the following command: pip install openai

3. Set up an API key. To use the OpenAI API, you will need to sign up for an account and obtain an API key. You can sign up for an API key at the OpenAI website (https://beta.openai.com/signup/).

4. Install the required libraries. ChatGPT requires several libraries to be installed, including requests, numpy, and tqdm. You can install these libraries by running the following command: pip install requests numpy tqdm

5. You can now use ChatGPT by importing it in your Python code and using the openai.Completion.create() method. Here is an example of how to generate text using ChatGPT:

import openai
# Set the API key
openai.api_key = "YOUR_API_KEY"
# Use the ChatGPT model to generate text
model_engine = "text-davinci-002"
prompt = "Hello, how are you today?"
completion = openai.Completion.create(engine=model_engine, prompt=prompt, max_tokens=1024, n=1,stop=None,temperature=0.7)
message = completion.choices[0].text
print(message)
Here are the steps you can follow to install ChatGPT locally:

Hope this is helpful!

👉 Be sure to join Hales' publication, the Software Testing Pipeline, to get the latest tips, tricks, and news about quality assurance and software testing on Medium.

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Yes, you can install ChatGPT locally on your machine. ChatGPT is a variant of the GPT-3 (Generative Pre-trained Transformer 3) language model, which was developed by OpenAI. It is designed to...

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Questions about ChatGPT-maker OpenAI's ability to comply with European privacy rules are in the frame again after a detailed complaint was filed with the Polish data protection authority yesterday.

The complaint, which TechCrunch has reviewed, alleges the U.S. based AI giant is in breach of the bloc's General Data Protection Regulation (GDPR) - across a sweep of dimensions: Lawful basis, transparency, fairness, data access rights, and privacy by design are all areas it argues OpenAI is infringing EU privacy rules. (Aka, Articles 5(1)(a), 12, 15, 16 and 25(1) of the GDPR).

Indeed, the complaint frames the novel generative AI technology and its maker's approach to developing and operating the viral tool as essentially a systematic breach of the pan-EU regime. Another suggestion, therefore, is that OpenAI has overlooked another requirement in the GDPR to undertake prior consultation with regulators (Article 36) - since, if it had conducted a proactive assessment which identified high risks to people's rights unless mitigating measures were applied it should have given pause for thought. Yet OpenAI apparently rolled ahead and launched ChatGPT in Europe without engaging with local regulators which could have ensured it avoided falling foul of the bloc's privacy rulebook.

This is not the first GDPR concern lobbed in ChatGPT's direction, of course. Italy's privacy watchdog, the Garante, generated headlines earlier this year after it ordered OpenAI to stop processing data locally - directing the US-based company to tackle a preliminary list of problems it identified in areas including lawful basis, information disclosures, user controls and child safety.

ChatGPT was able to resume offering a service in Italy fairly quickly after it tweaked its presentation. But the Italian DPA's investigation continues and it remains to be seen what compliance conclusions may emerge once that assessment has been completed. Other EU DPAs are also probing ChatGPT. While, in April, the bloc's data protection authorities formed a task force, via the European Data Protection Board (EDPB), to collectively consider how they should approach regulating the fast-developing tech.

That effort is ongoing - and it's by no means certain a harmonized approach to oversight of ChatGPT and other AI chatbots will emerge - but, whatever happens there, the GDPR is still law and still in force. So anyone in the EU who feels their rights are being trampled by Big AI grabbing their data for training models that may spit out falsities about them can raise concerns with their local DPA and press for regulators to investigate, as is happening here.

OpenAI is not main established in any EU Member State for the purpose of GDPR oversight, which means it remains exposed to regulatory risk in this area across the bloc. So could face outreach from DPAs acting on complaints from individuals anywhere in the bloc.

Confirmed violations of the GDPR, meanwhile, can attract penalties as high as 4% of global annual turnover. DPAs' corrective orders may also end up reworking how technologies function if they wish to continue operating inside the bloc.

Complaint of unlawful processing for AI training

The 17-page complaint filed yesterday with the Polish DPA is the work of Lukasz Olejnik, a security and privacy researcher, who is being represented for the complaint by Warsaw-based law firm, GP Partners.

Olejnik tells TechCrunch he became concerned after he used ChatGPT to generate a biography of himself and found it produced a text that contained some errors. He sought to contact OpenAI, towards the end of March, to point out the errors and ask for the inaccurate information about him to be corrected. He also asked it to provide him with a bundle of information that the GDPR empowers individuals to get from entities processing their data when the information has been obtained from somewhere other than themselves, as was the case here.

Per the complaint, a series of email exchanges took place between Olejnik and OpenAI between March and June of this year. And while OpenAI responded by providing some information in response to the Subject Access Request (SAR) Olejnik's complaint argues it failed to produce all the information it must under the law - including, notably, omitting information about its processing of personal data for AI model training.

Under the GDPR, for personal data processing to be lawful the data controller needs a valid legal basis - which must be transparently communicated. So obfuscation is not a good compliance strategy. Also indeed because the regulation attaches the principle of fairness to the lawfulness of processing, which means anyone playing tricks to try to conceal the true extent of personal data processing is going to fall foul of the law too.

Olejnik's complaint therefore asserts OpenAI breached Article 5(1)(a). Or, more simply, he argues the company processed his data "unlawfully, unfairly, and in a non-transparent manner". "From the facts of the case, it appears that OpenAI systemically ignores the provisions of the GDPR regarding the processing of data for the purposes of training models within ChatGPT, a result of which, among other things, was that Mr. Łukasz Olejnik was not properly informed about the processing of his personal data," the complaint notes.

It also accuses OpenAI of acting in an "untrustworthy, dishonest, and perhaps unconscientious manner" by failing to be able to comprehensively detail how it has processed people's data.

" Although OpenAI indicates that the data used to train the [AI] models includes personal data, OpenAI does not actually provide any information about the processing operations involving this data. OpenAI thus violates a fundamental element of the right under Article 15 GDPR, i.e., the obligation to confirm that personal data is being processed," runs another relevant chunk of the complaint (which has been translated into English from Polish using machine translation).

"Notably, OpenAI did not include the processing of personal data in connection with model training in the information on categories of personal data or categories of data recipients. Providing a copy of the data also did not include personal data processed for training language models. As it seems, the fact of processing personal data for model training OpenAI hides or at least camouflages intentionally. This is also apparent from OpenAI's Privacy Policy, which omits in the substantive part the processes involved in processing personal data for training language models.

"OpenAI reports that it does not use so-called 'training' data to identify individuals or remember their information, and is working to reduce the amount of personal data processed in the 'training' dataset. Although these mechanisms positively affect the level of protection of personal data and comply with the principle of minimization (Article 5(1)(c) of the GDPR), their application does not change the fact that 'training' data are processed and include personal data. The provisions of GDPR apply to the processing operations of such data, including the obligation to grant the data subject access to the data and provide the information indicated in Article 15(1) of GDPR."

It's a matter of record that OpenAI did not ask individuals whose personal data it may have processed as training data when it was developing its AI chatbot for their permission to use their information for that - nor did it inform the likely millions (or even billions) of people whose information it ingested in order to develop a commercial generative AI tool - which likely explains its lack of transparency when asked to produce information about this aspect of its data processing operations via Olejnik's SAR.

However, as noted above, the GDPR requires not only a lawful basis for processing people's data but transparency and fairness vis-a-vis any such operations. So OpenAI appears to have got itself into a triple bind here. Although it remains to be seen how EU regulators will act on such complaints as they weigh how to respond to generative AI chatbots.

Right to correct personal data ignored

Another aspect of Olejnik's beef with OpenAI fixes on errors ChatGPT generated about him when asked to produce a biography - and its apparent inability to rectify these inaccuracies when asked. Instead of correcting falsehoods its tool generated about him, he says OpenAI initially responded to his ask by blocking requests made to ChatGPT that referenced him - something he had not asked for.

Subsequently it told him it could not correct the errors. Yet the GDPR provides individuals with a right to rectification of their personal data.

"In the case of OpenAI and the processing of data to train models, this principle [rectification of personal data] is completely ignored in practice," the complaint asserts. " This is evidenced by OpenAI's response to Mr. Łukasz Olejnik's request, according to which OpenAI was unable to correct the processed data. OpenAI's systemic inability to correct data is assumed by OpenAI as part of ChatGPT's operating model."

Discussing disclosures related to this aspect of its operation contained in OpenAI's privacy policy, the complaint goes on to argue: "Given the general and vague description of ChatGPT's data validity mechanisms, it is highly likely that the inability to correct data is a systemic phenomenon in OpenAI's data processing, and not just in limited cases."

It further suggests there may be "reasonable doubts about the overall compliance with data protection regulations of a tool, an essential element of which is the systemic inaccuracy of the processed data", adding: "These doubts are reinforced by the scale of ChatGPT's processed data and the scale of potential recipients of personal data, which affect the risks to rights and freedoms associated with personal data inaccuracy."

The complaint goes on to argue OpenAI "should develop and implement a data rectification mechanism based on an appropriate filter/module that would verify and correct content generated by ChatGPT (e.g., based on a database of corrected results)", suggesting: "It is reasonable in the context of the scope of the obligation to ensure data accuracy to expect OpenAI to correct at least data reported or flagged by users as incorrect."

"We believe that it is possible for OpenAI to develop adequate and GDPR-compliant mechanisms for correcting inaccurate data (it is already possible to block the generation of certain content as a result of a blockade imposed by OpenAI)," it adds. "However, if, in OpenAI's opinion, it is not possible to develop such mechanisms - it would be necessary to consult the issue with the relevant supervisory authorities, including, for example, through the prior consultation procedure described in Article 36 of GDPR."

Data protection incompatibility by design?

The complaint also seeks to spotlight what it views as a total violation of the GDPR's principle of data protection by design and default.

"The way the ChatGPT tool was designed, taking into account also the violations described [earlier] in the complaint (in particular, the inability to exercise the right to rectify data, the omission of data processing operations for training GPT models) - contradicts all the indicated assumptions of the principle of data protection by design," it argues. "In practice, in the case of data processing by OpenAI, there is testing of the ChatGPT tool using personal data, not in the design phase, but in the production environment (i.e., after the tool is made available to users).

"OpenAI seems to accept that the ChatGPT tool model that has been developed is simply incompatible with the provisions of GDPR, and it agrees to this state of affairs. This shows a complete disregard for the goals behind the principle of data protection by design."

We've asked OpenAI to respond to the complaint's claims that its AI chatbot violates the GDPR and also to confirm whether or not it produced a data protection impact assessment prior to launching ChatGPT.

Additionally, we've asked it to explain why it did not seek prior consultation with EU regulators to get help on how to develop such a high risk technology in a way that could have mitigated GDPR risks. At the time of writing it had not responded to our questions but we'll update this report if we get a response.

We also reached out to the Polish DPA, the UODO, about the complaint. A spokesperson for the UODO confirmed receipt of the complaint - which they said it is now analyzing to decide on further actions. They also confirmed it is the first such complaint the authority has received regarding ChatGPT. And said they have not previously had any correspondence with OpenAI regarding ChatGPT's GDPR compliance.

"The [UODO] has been looking at generative AI tools for a long time in light of the requirements of the GDPR regarding lawful, fair and transparent processing of personal data and data access rights," the spokesperson also told us. "The authority is wondering how artificial intelligence systems should be designed in accordance with the GDPR, and how to determine the relationship between the GDPR and the [EU] AI Act. New legal regulations, such as the AI Act, which limit the impact of AI on the analysis of biometric data or human emotional states allow us to look into the future with hope.

"We expect that the AI Act will allow us to protect fundamental rights against inappropriately functioning AI algorithms. Nevertheless, at the same time, the Personal Data Protection Office is aware that due to the possibility of automatic decision-making based on data analysis, there may be a risk of inappropriate use of AI, e.g. to manipulate public opinion, spread false information or discriminate against certain social groups. These are the challenges that the [UODO] has to face. The Office also reminds that customers must be informed how their data is used and processed by AI and be able to consent to their use."

The spokesman also emphasized the importance of conducting a data protection impact assessment, stressing that "particular emphasis should be placed on DPIA". "A personal data controller who uses tools such as ChatGPT should apply a risk-based approach and conduct a data protection impact assessment before starting to process data using artificial intelligence," they added.

They further confirmed that the authority has joined the dedicated EDPB task force looking at ChatGPT's GDPR compliance, saying the effort aims to "foster cooperation and exchange information on possible enforcement actions conducted by data protection authorities regarding the ChatGPT service and provide the platform for its joint analysis on the EU level".

Discussing their own expectations for the complaint, Olejnik's lawyer, Maciej Gawronski, suggests the length of time it could take the Polish regulator to investigate could be "anything from six months to two years".

"Provided UODO confirms violation of the GDPR we would expect UODO to primarily order OpenAI to exercise Mr Olejnik's rights," he told us. "In addition, as we argue that some of OpenAI's violations may be systemic, we hope the DPA will investigate the processing thoroughly and, if justified, order OpenAI to act in compliance with the GDPR so that data processing operations within ChatGPT are lawful in a more universal perspective."

Gawronski also takes the view that OpenAI has failed to apply Article 36 of the GDPR - since it did not engage in a process of prior consultation with the UODO or any other European DPA before launching ChatGPT - adding: "We would expect UODO to force OpenAI into engaging into a similar process now."

In another step, the complaint urges the Polish regulator to require OpenAI to submit a data protection impact assessment (DPIA) with details of its processing of personal data for purposes related to ChatGPT - describing this document, which is a standard feature of data protection compliance in Europe, as an "important element" for assessing whether the tool is compliant with the GDPR.

For his part, Olejnik says his hope in bringing the complaint against OpenAI and ChatGPT is that he will be able to properly exercise all the GDPR rights he has found himself unable to so far.

"During this journey I felt kind of like Josef K, in kafka's The Trial, " he told us. "Fortunately, in Europe there's a system in place to avoid such a feeling. I trust that the GDPR process does work!"
This report was updated with comment from the Polish data protection authority

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ChatGPT-maker OpenAI accused of string of data protection breaches in GDPR complaint filed by privacy researcher | TechCrunch

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Questions about ChatGPT-maker OpenAI's ability to comply with European privacy rules are in the frame again after a detailed complaint was filed with the Questions about ChatGPT-maker OpenAI's ability to comply with European privacy rules are in the frame again after a detailed complaint was filed with the Polish data protection authority yesterday.

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Microsoft’s desperate attempts to make us ditch Google are getting worse

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Microsoft recently tested new, even more obtrusive pop-ups to convince Chrome users to switch to Bing as their default search engine.

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Opinions expressed by Entrepreneur contributors are their own.

This story originally appeared on Under30CEO.com

The generative AI boom is in full swing, and practically everyone, except a few notable naysayers, believes a revolution is upon us. Even national governments, usually slow to react, are coming around to the idea that AI will have a transformative effect on society.

Nowhere are these changes clearer than in the creator economy. Individuals can now increase their output tenfold (if not more) with the help of generative AI tools.

Speeding up work

Artificial intelligence is dramatically speeding up work and changing the creative process. Brands still need agency (they can't put Tweets on autopilot just yet). However, they can use generative AI tools for ideation and even full-blown content writing with the correct prompts.
Related: 5 Ways ChatGPT Will Impact Digital Marketing
Given the remarkable abilities of this technology, an entire industry is growing around it. Self-styled professionals are offering creators courses and instructions on how to do more with less time using AI and generative intelligence, enabling them to expand their creativity and reach more people in a profound sea-change from just a few years ago.

ProPhotos, the makers of an AI headshot generator, say the biggest change will be convenience. "Our customers want to say goodbye to the hassle and expense of traditional photoshoots," the brand says, according to Under30CEO. "Thanks to advances in artificial intelligence, it is now possible to capture photorealistic, high-quality headshots without expensive camera equipment or studio lighting. Software can do everything independently, without the need for external assistance."

These breakthroughs are remarkable and represent what might come down the pike. Presenting a polished and professional personal profile picture is essential for anyone who makes a living online, but challenging to achieve with yesterday's technology. Only the most committed creators had the motivation to choose the professional path. Now, though, it is considerably more accessible, and practically anyone can do it using simple prompts.

Drafting and outline

Generative AI also plays a significant role in drafting and outlining content. These tools are exceptionally good at providing creators with logical sequences of concepts to discuss, showing them what to write or say next to maximize audience comprehension.

Of course, creators aren't willing to hand over the full creative process to AI just yet. Machine intelligence often lacks flair or the ability to mimic their brand voice.

However, it is adept at providing a general structure and providing ideas. Language models, such as ChatGPT, can ideate endlessly, sparking human creativity in the process.

Automating routine tasks
Related: How To Use ChatGPT as a Creative Writing Partner
We are also seeing generative AI play an increasingly valuable role in automating routine tasks. Creators are using the technology to reply quickly to comments or automatically like and respond to interactions on their profile pages.

Again, this might seem a bit like cheating, but it is yet another example of how effective the tools can be. Most creators spend hours engaging with users online, taking them away from their core work and preventing them from progressing to other projects as rapidly as they would like.

Automation of routine tasks is also reducing the risk of burnout. Instead of creators waking up every morning and spending an hour spamming comments as fast as they can, bots can now provide simple responses for them, which they can approve or deny. Creators have more energy to dedicate to other, more valuable tasks.

Language translation

Interestingly, generative AI is also leading to a boom in creators going across languages. Instead of creating content in English alone, many are now able to automatically bridge the cultural barrier and reach new audiences with ease. Generative models can now translate more text with exceptional accuracy, representing its true meaning in a different language.

Efficient research

We are also seeing generative AI leading to more efficient research. Instead of trawling through reams of scientific articles to find a specific reference, chatbots can now search their databases for relevant studies based on rough user inputs.

For example, a creator wanting to research the effects of egg consumption on cholesterol levels can ask one of the new AI-powered chatbots to do it. A simple prompt is all it takes.

Most leading chatbot models include scientific research papers in their training data. This lets them identify specific studies of interest that creators can use to make their points or get their messages across.

Research is also becoming more efficient because of the ability of chatbots to probe the truthfulness of scientific statements. Creators can ask these tools if their statements are correct in the context of the existing scientific literature. Bots can then respond, telling them which studies corroborate or refute their statements.

Learning new skills

Finally, generative AI is teaching creators new skills. Tools have become like personal assistants or guides, helping social media personalities navigate tricky concepts and push their brands forward. Solo brands can ask these pieces of software for training on virtually any question and receive it in a tailored, convenient format. As with all training, creators still need to put in some effort (i.e. telling the tools what they want to learn) but the ability of these machines to generate course-like content is accelerating dramatically.

As the technology continues to improve, AI systems will be better able to include multi-model support. On-demand video generation will let software provide instructions in a more tutor-like, rather than textbook-like format. Users will be able to interact with these systems as if they are people through online portals.

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How Generative AI Helps Creatives Save Time and Money | Entrepreneur

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Artificial intelligence enables creators to expedite their processes and results.

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A few years back, we wrote about a jailbreak tweak called Jumper by iOS developer neoish that not only added configurable app shortcuts to the Lock Screen for ease of access but designed them in such a way that they didn't add unwanted clutter to the interface because they collapse into a smaller space when not in use.

Jumper was a jailbreak tweak that I took advantage of almost all the time, but since the newer rootless jailbreaks for iOS 15 and 16 became the norm, it's felt like I've been missing out. Fortunately, Jumper was updated to version 3.1.0 on Wednesday, adding official support for rootless jailbreaks such as Dopamine and palera1n.

At first glance, you can customize the existing Quick Action buttons that exist on the Lock Screen right out of the box, which include the Camera and Flashlight shortcuts, so that they point to something else. However one thing I really like about Jumper is that you can have collapsible shortcuts so that you can have shortcuts to up to 8 apps on your Lock Screen at any given time.

Once installed, Jumper adds a dedicated preference pane to the Settings app where you can configure your Jumper shortcuts to your liking. Not only will you be able to select which apps or shortcuts you can access from the Lock Screen, but you will be able to customize the icons that represent them:

There's absolutely no shortage of jailbreak tweaks on the market that add app shortcuts to your device, but we feel that Jumper does this in such an elegant way, especially on the Lock Screen, that it's worth taking a look at.

Those interested in giving Jumper a try, especially on their rootless jailbreaks, but also on their rootful jailbreaks, can head over to the Havoc repository and purchase the tweak for $1.99. The latest update is a free upgrade if you already own an older version of Jumper. The tweak works on all versions of iOS ranging from iOS 13 to iOS 16.

Are you planning to take advantage of Jumper? Let us know why or why not in the comments section down below.

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Jumper Lock Screen shortcut customizer tweak adds support for rootless jailbreaks

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The Jumper Lock Screen shortcut customizer jailbreak tweak received an update that adds support for rootless jailbreaks.

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Apple Notes has received many improvements over its lifetime, but noticeably absent year after year was the ability to easily add quick links in notes to other notes for reference. The latest software updates for iPhone, iPad, and Mac finally address this with a simple note-linking tool.

Note-to-note connections let you "link your thinking" so that your notes aren't isolated in their folders and are easier to find later. Now, ideas in one note can be quickly connected to ideas in another, meaning you don't have to resort to broader connections using tags to group related topics.

Apple's new note-linking feature follows other note-taking apps, such as Bear, Evernote, Obsidian, and Simplenote, which already make deep-linking notes a simple task. There were some workarounds using Shortcuts and collaboration invites to create note links in Apple Notes, but it should have never been that difficult.

Requirements

Jump to a Section

Adding a Hyperlink to Selected Text

Creating a link to another note is simple and can be accomplished in various ways depending on how you want the link to appear. On iPhone or iPad, if you want to add an inline note hyperlink to a word or phrase in your current note:

1. Double-tap or triple-tap to select the text you want to hyperlink.

2. Adjust the highlighted boundaries of the selected text if necessary.

3. Tap the arrow (>) in the contextual menu and select "Add Link." (If you don't see the menu, tap the selected text to make it appear.)

4. Begin typing the name of the note you want to link to and select it from the suggestions.

Tap "Done" to add the hyperlinked note to the selected text. (If you toggle on the "Use Note Title as Name" switch and hit "Done," the text you selected will be replaced entirely by a Notes icon and the name of the note.)

Once the note has been linked, tapping the text will immediately open the note that you linked to. You can also long-press the hyperlinked text to see the link (which uses the applenotes URL scheme) and open, copy, or share it.

Adding a Link with the Note's Name

If you don't need to hyperlink any text in your note or would prefer to see the other note's name, you can add a regular link to the other note. This can be done as described above in step 5, which will replace the selected text you initially meant to hyperlink. However, there are two better ways that make more sense.

Option 1: Using the 'Add Link' Tool

First, you can use the "Add Link" tool as such:

1. Move the cursor to where you want to drop the link.

2. Tap the cursor to open the contextual menu.

3. Tap the arrow (>) in the contextual menu and select "Add Link."

1. Begin typing the name of the note you want to link to and select it from the suggestions.

2. Tap "Done" to add the link. (If you toggle off the "Use Note Title as Name" switch, you can create hyperlinked text instead via the "Optional" field that appears, as seen in the previous section.)

Option 2: Using the Keyboard Shortcut

Second, you can use the >> keyboard shortcut as such:

1. Move the cursor to where you want to drop the link.

2. Hit the > key on your keyboard twice - so that it looks like ">>" - to make Notes show you your six most recent notes.

3. Begin typing the name of the note you want to link to.

4. Select the note from the suggestions to create the link.

No matter which two of the methods you use, the resulting link will appear as a note icon with the name of the note right after it. If you ever update the note's name, this link will update accordingly, ensuring the hyperlink always reflects the note's current title.

Tapping the note's name will immediately open its associated note. You can also long-press the note's title to see a rich link preview of the note itself. You'll also have options to open the note or copy its link, as well as a way to edit or remove the link.

Creating Links to Notes That Don't Exist Yet

As you probably noticed above, the >> trick shows an option that lets you create a brand-new note. This is useful if you want to spread your thoughts across notes so that each note isn't packed with too much information. Here's how it works:

1. Move the cursor to where you want to drop the link.

2. Hit the > key on your keyboard twice - so that it looks like ">>" - to make Notes show you your six most recent notes.

3. Begin typing the name of the note you want to create.

4. Tap "(+) Create note "[The Note's Name]" to add a link to the new note.

5. Then you can go to the new note later to fill it out (just tap the new link to get there!).

Creating Bidirectional Note Links

Unfortunately, after tapping the hyperlinked text or the note's name to open up the linked note, you can't quickly return to the note you were in first. However, you can link it to the current note to create a bidirectional connection. That way, going forward, you can switch between the notes with just a tap.

Editing or Removing Note Links

You can also edit or remove note links. For links that use the note's name, tap and hold its name, then select "Remove Link" to get rid of the whole thing. Otherwise, select "Edit Link" to change the link to a different note or switch off "Use Note Title as Name" to add custom hyperlinked text instead via the "Optional" field that appears. You can remove the link from here as well.

For links that use custom hyperlinked text, use the selection tool to highlight some or all of the link, which should bring up the contextual menu where you'll see options for "Edit Link" and "Remove Link." When editing the link, you can change the link to a different note or switch on "Use Note Title as Name" to swap the hyperlinked text out with the note's name instead. You can remove the link from here as well.

Working with Note Links on macOS

The process is a little different on macOS Sonoma. To create custom hyperlinked text, highlight the word or phrase in the current note, then go to Edit -> Add Link in the menu bar or use the Command-K shortcut. From here, it's the same as on iOS 17 and iPadOS 17. Hit "OK" when done.

To use the note's name as the link, place your cursor where you want it, then select Edit -> Add Link from the menu bar or use the Command-K shortcut. Search for and select the note and ensure "Use Note Title as Name" is checked before hitting "OK."

You can also use the >> shortcut to show your 12 most recent notes (instead of just six). Start typing the name of the note you want to update the suggestions, then select the correct one. And just like on iOS 17 and iPadOS 17, you can create a completely new note to fill it out later.

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Your iPhone's Notes App Finally Lets You Link Your Notes Together

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Apple Notes has received many improvements over its lifetime, but noticeably absent year after year was the ability to easily add quick links in notes to other notes for reference. The latest software updates for iPhone, iPad, and Mac finally address this with a simple note-linking tool.

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10'000 Hours/Getty Images

Google Docs already offers a spelling and grammar checker that will scan your documents for typos and grammatical errors. But now Google has kicked off a more advanced AI-based tool designed to make your documents more readable. Unveiled on Tuesday, the new Proofread tool can scan your documents for writing style, tone, and readability to suggest ways to improve them.

On the downside, Proofread isn't available for regular Google Docs users or even for all Google Workspace customers. The tool is limited to just Google Workspace Enterprise customers and only through an add-on for the company's Duet AI product, at least for now.
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A Google spokesperson didn't share any specifics but did tell ZDNET through email that "[Google] will be releasing additional offerings over the coming months for other customer segments, including small and medium-sized businesses and consumers."

For now, if your business or organization uses Duet AI, Proofread may be worth exploring to see if it can enhance the quality of your documents.

Beyond providing the usual spelling and grammar checks, Proofread will offer the following types of suggestions for your review:

Conciseness: Make your writing more concise and succinct.

Active voice: Make your writing clearer to your readers.

Wording: Make words sound more dynamic or formal within the right context.

Sentence Split: Split up long and complex sentences so your document is easier to read.

Google

Also: How these two Google Docs features can simplify your project management features
The suggestions made by Proofread are just that -- suggestions. As you can with any spelling or grammar checker, you're able to review each one and either accept it or reject it. All suggested changes appear in the Proofread sidebar so they don't crowd the actual text of your document. Plus, you can use filters to control and limit the types of suggestions you see.

If the Proofread add-on is enabled, the option will be on by default. However, individual users can turn it on and off in Google Docs by going to Tools and selecting Proofread. To open the Proofread sidebar, just click the icon with an A and checkmark. A blue dot will appear next to the icon when writing suggestions are waiting for you.

Also: Are your Google Docs safe from AI training?

With all the buzz over artificial intelligence, Google has been trying to infuse AI into many of its key products. Google Docs, Google Slides, and Gmail all offer an AI-powered option to help you write or rewrite text based on your own description. Google Labs lets you play with generative AI at the Google search engine and in Google Workspace. Lastly, Google Bard is the company's own AI-based chatbot designed to help you find information and generate content.

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Google Docs just got a new AI-powered proofreading tool

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Available only for Google Workspace Enterprise customers for now, the new Proofread tool aims to make your writing more concise, clearer, and easier to read.

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The Best Broadband ISPs for 2023, Ranked

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If you're looking for better internet service, you've come to the right place. We tested major and local ISPs across the United States to find the very best and are sharing our findings below. Here are the top broadband ISPs for 2023, ranked by speed, price, availability, and customer satisfaction.

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AlloyDB, Google's fully managed PostgresSQL-compatible database service, is gaining a few AI smarts.

Google today announced the launch of AlloyDB AI, an integrated set of capabilities built into AlloyDB for PostgreSQL to support developers in building generative AI apps using their own data. AlloyDB AI, available in preview via AlloyDB Omni (which is moving from a technical preview to public preview), provides built-in support for vector embeddings - delivering the foundation for AI search apps and more.

"AlloyDB AI was built with portability and flexibility in mind ... Developers [can] incorporate their real-time data into generative AI applications," Andi Gutmans, GM and VP of database engineering at Google, wrote in a blog post shared with TechCrunch. "Not only is it PostgreSQL-compatible, but with AlloyDB Omni, customers can take advantage of [AlloyDB AI] to build enterprise-grade, AI-enabled applications everywhere: on premises, at the edge, across clouds or even on developer laptops."

Vector embeddings - numerical representations of data, including but not limited to text, audio and image data - allow AI algorithms to better understand the relationships between different types of data and their semantic relevance to each other. That's useful for, say, recommendation engines, which can tap embeddings to find data similar to other data (e.g. similar movies and TV shows). But the use cases extend beyond that - think things like fraud detection and typo correction.

AlloyDB AI, then, aims to help users transform data within databases - the databases that serve information to generative AI models - into vector embeddings with a single line of code and without a specialized data stack.

PostgreSQL already supports vectors. But AlloyDB AI takes this support a step further, providing access to Google's on-premises embeddings models for in-database embeddings generation and cloud embeddings models served via Vertex AI, Google's platform for building and deploying AI apps.

Both the on-premises and Vertex AI models can be used to generate embeddings on the fly in response to user inputs, Google says. Or they can be used to automatically create embeddings via inferencing in any generated database columns.

Beyond the models, AlloyDB AI delivers up to 10x faster vector query performance than standard PostgreSQL thanks to what Google describes as "tight integrations" with the AlloyDB query processing engine. AlloyDB AI, in addition, is integrated with Vertex AI Extensions, a set of fully managed tools that help developers connect models to proprietary data or third parties, and LangChain, an open framework designed to simplify the creation of apps that leverage generative AI text models.

In addition to AlloyDB Omni, AlloyDB AI will launch later this year on the AlloyDB managed service. The capabilities in AlloyDB can be added to any AlloyDB deployment by installing the relevant extensions at no additional charge, Google says.

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Google's AlloyDB AI transforms databases to power generative AI apps | TechCrunch

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Google's AlloyDB AI, a new set of capabilities in AlloyDB, transforms database content so that it's in a format to power generative AI apps.

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12 Must-Have Devices To Transform Your House Into A Smart Home - SlashGear

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WIth these smart home gadgets, many of the daily repetitive tasks around your home can be automated and outsourced to modern technology.

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Maria Diaz/ZDNET

A video doorbell is one of the best ways to get started with your smart home journey. Video doorbells are easy to use, often easy to install, and are sure to bring you some much-needed surveillance. Though they may seem intimidating to set up for beginners, there's a video doorbell option for just about everyone, whether you're looking for a budget-friendly option or one that's easy to install.

Also: I tested SwitchBot's new Curtain 3 robot and it made me feel like royalty

Having tested several video doorbell options in the past, I've come to enjoy having the latest Lorex 2K Wi-Fi video doorbell . I prefer a battery video doorbell for easy installation, so I got the battery-operated option. But more importantly, Lorex ditches the typical paid subscription model in favor of a flat hardware fee. Is it worth it? Let's find out.

Having your phone tell you who's at the door in real-time, and being able to talk to them when you can't answer the door, is life-changing, I tell you. The Lorex 2K video doorbell does this and more, as it boasts a 2K video resolution with HDR, no monthly subscription fees, and the battery option features an easy-to-install set of brackets to give you the viewing angle you desire.

Setting up the Lorex 2K video doorbell was straightforward, as I opted for the battery-powered model (there's a wired option, too). All it took was a few-hour charge, pairing it to the Lorex mobile app, and installing the bracket where I wanted the doorbell. I already have a Eufy Battery video doorbell, so I set up the Lorex next to it to be able to compare the images captured by both.
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Once the doorbell is installed, there's not much else for you to worry about. It's one of my favorite things about this video doorbell, the lack of monthly fees. You can store your video recordings in the included 32GB MicroSD card and take the opportunity to offload them whenever you need to bring your doorbell in to charge. If you're using a wired installation, I'd keep an extra MicroSD card to swap out every now and then to keep your video doorbell recording the events that matter to you.

Maria Diaz/ZDNET

The Lorex app is also easy to use and navigate, from checking your notifications to looking at the live feed to changing your doorbell settings to checking your event history. Lorex is a renowned security camera maker, and the app lets you access other Lorex cameras you may have at home in one place.
Also: This robot vacuum connects to your home's water supply for full automation
The doorbell also features Person Detection, making it easy to skip false alarms as you won't get notified when a spider crawls over your video camera or the trees in your yard sway in the wind.

The biggest problem I have with this Lorex video doorbell is that the image, though good quality at 2560 x 1920 resolution, looks distorted due to the 164-degree field of view. This wouldn't be a huge deal for more affordable doorbells, but one worth almost $200 should offer a less offset visual experience.

People can look distorted in the images, which isn't a big deal if you're just using the doorbell to see who's at the door, but it does bother me when I rewatch the recordings. As you can see in the comparison above, my Lorex doorbell shows a stretched image compared to the screenshot from the Eufy doorbell, as evidenced by the elongated UPS truck.

It also doesn't include a chime kit, meaning you'd have to buy it separately or forgo the battery feature and use it with your home's existing wiring to use your current chime box. The is available for an extra $50 as a small, plug-in device that works with Wi-Fi.
Also: World's first smart door now available at Home Depot, but you probably can't afford it
That said, the Lorex 2K video doorbell excels at daily use. It's reliably on time with real-time alerts when someone is spotted at the door and it integrates seamlessly with Alexa. Hence, we get notifications from our Echo devices when someone rings the doorbell, and it has a small LED light that comes on in the dark when you approach it.

The built-in LED is an underrated feature and one of my favorites. This is helpful when you arrive home in the dark and can use some brightness to find your keys, but I also like that it could potentially deter would-be intruders, as the light turns on when the camera detects movement.

ZDNET's buying advice

Even if I'm not a huge fan of the wide-angle image captured by it, there are quite a few things I like about the Lorex 2K Battery Video Doorbell . The battery has outlasted my Eufy Battery Doorbell for the past couple of months, which needs charging about every other month.

The Lorex 2K Battery Doorbell is available for $180 and is the perfect video doorbell for anyone with a Lorex camera system in their home. But it's also a great substitute for a Ring video doorbell, as you can enjoy many of the same benefits without paying for a subscription. The fact that you can also opt for wired installation to use your existing chime and expand the internal storage with a microSD card (up to 256GB) takes it to the next level.

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Better than Ring? This video doorbell has all the benefits and no subscription fees

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The Lorex 2K video doorbell is the company's flagship security system. Let's find out if it's worth the money.

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(Image credit: OutSnapped)

If you're of a certain age you will remember that photobooths of old where you went to get a quick picture for your passport or a fun snap to remember a great day with your loved one or friends. And if you were lucky you might have got some red theatre-style curtains either side, well that is all about to change.

Thanks to an NYC-based physical and digital photo booth company OutSnapped has announced and launched the company's first-to-market patent-pending AI photo booth technology.

This photo booth uses artificial intelligence to generate photos in real time that can turn single moments into what the company is marketing as "immersive experiences".

With analytics and audience engagement tools built in, this AI photo booth offers infinite possibilities for event planners, retail pop-ups, and more to create viral content that centers around their audience.

OutSnapped's new technology breaks free of the limitations of photo filters. With just a single photo of a person, the AI can render realistic imagery of that person's AI avatar in any setting.

From riding a horse on a beach in Bali to corporate headshots in a boardroom in an outfit that radiates confidence, this photo booth can change your appearance and your surroundings.

Once your photo is taken in front of a green screen, the image is beamed to Outsnapped AI platform - and then the fun begins with each photo being processed based on your specifications. Designed to be used at corporate events, the company hiring the system can add in its own props and logos to help customize the experience. The AI images are then automatically sent to the photo subjects' phones - so they can immediately be shared on social media.

(Image credit: OutSnapped)

Nicholas Rhodes, Founder and CEO has this to say about the launch:

"Over the last twenty years as a highly sought-after event photographer and blogger, I have witnessed and helped shape how brands, media, and the public create and interact with images online. The new OutSnapped AI photo booth represents a tectonic shift that will forever change the way memories are recorded. We're so excited to work with companies to reimagine the future of experiential marketing."

Whether you are a fan of AI or you think it is ruing the whole photography industry, we have all used AI at some point in our lives to make it easier, some without even knowing it, and when you want a quick snap to remember a wonderful trip this new AI photo booth could bring the glamour to highlight your event.

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This AI photo booth turns your images into dream-like memories

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AI photo booth turns your boring booth images into creative fantasies

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Apple has already raised eyebrows with the anticipated price tag of its 'extended reality' (XR) headset, the Vision Pro. Due to launch next year, the device is expected to cost $3,499. And, of course, there will be accessories on top of that.

We've already heard that the top strap may not come included with the headset. Now a new patent describes a much more intriguing accessory, but people can't agree on what it is or what it's for (see our pick of the best Apple deals for bargains on the company's current tech).

(Image credit: Apple)

A new Apple patent filing with the US Patent and Trademark Office describes "a small portable physical object for use in an extended reality system". Later in the text, it refers to the device as a "digital stone" or a "go stone"

Patently Apple has suggested that it sounds a little like an AirTag, and there have been rumours that Apple is working on some form of second-gen AirTag that would integrate with Vision Pro. But Apple says the stone could allow virtual objects from the XR world to persist in the real world after you turn the Vision Pro off.

Sorry? Well, it's all very vague and there's little in the way of concrete examples in the patent documentation, but Apple says it could be possible to associate the stone with a virtual object in Vision Pro and for that association to continue after you power off the headset, allowing the user to carry content from the XR environment in the physical world and reaccess it later either using the same Vision Pro or another XR system.

(Image credit: Apple)

So a kind of storage device for Apple's spatial computing concept? Apple provides examples in the form of digital photographs, the state of an active document or application or digital currency. So it sounds like the idea would be that you could save a virtual photo album, for example, to the stone and then pass it on to someone else, who could access it in their Vision Pro. But we wonder if a physical device would really be the most practical solution for that.

Apple also mentions a more sophisticated device with the potential to house cameras and sensors, including for touch, heart rate, temperature, Lidar, radar, sonar, GPS and more and could give haptic feedback. This sounds more like some form of controller that could be used to manipulate objects in the XR world like gloves used in some VR systems. This could make it something like the 3D equivalent of a mouse.

We'll just have to wait to see if this does turn out to be an accessory to accompany the Vision Pro next year. It's also possible that this is for much further ahead or that Apple merely wants to protect the idea. There have been plenty of Apple Patents over the years that haven't seen the light of day. Often the wording is intentionally vague, although the recent patent for an Apple Watch that can match your outfit was surprisingly concrete in its descriptions.

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Apple's strange Vision Pro accessory has people baffled

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What is this mysterious 'digital stone'?