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Refik Anadol, a Turkish AI artist, uses machine learning to create stunning, interactive art installations that captivate global audiences. Anadol specializes in transforming architectural spaces and building facades into monumental canvases for his AI-powered artwork. Recently, he crafted an innovative video-art piece for the Los Angeles Philharmonic by utilizing machine learning and years of archived footage. This resulted in a dynamic and ever-changing projection displayed on the building's exterior.

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Memo Akten, a London-based artist, researcher, and self-proclaimed "philomath," employs AI to explore human understanding of the world. His impressive portfolio is wide-ranging and profound, with one standout piece being "Deep Meditations." In this hour-long immersive film, Akten trained a neural network to visualize core human concepts. He provided the AI with a collection of images labeled with fundamental themes like world, universe, space, and mountains, then allowed it to craft its own interpretations. The resulting imagery, best experienced firsthand, is nothing short of extraordinary.

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Memo Akten | Mehmet Selim Akten | The Mega Super Awesome Visuals Company

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Information

2018
Immersive, large-scale video and sound installation.
3 or 5 channel 4K video. Stereo audio.
Duration: 60 minute seamless loop.
Technique: Custom software, generative video, generative audio, Artificial Intelligence, Machine Learning, Deep Learning, Generative Adversarial Networks, Variational Autoencoders.

Arguably the world's first film constructed in and told entirely through the latent space of a Deep Neural Network, with meaningful human control over narrative.
Update: To see studies for a new (2020) incarnation please see here. "It feels like the machine is trying to tell me something..." - audience member
Deep Meditations: A brief history of almost everything in 60 minutes is a large-scale video and sound installation; a multi-channel, one hour abstract film; a monument that celebrates life, nature, the universe and our subjective experience of it. The work invites us on a spiritual journey through slow, meditative, continuously evolving images and sounds, told through the imagination of a deep artificial neural network.

We are invited to acknowledge and appreciate the role we play as humans as part of a complex ecosystem heavily dependent on the balanced co-existence of many components. The work embraces and celebrates the interconnectedness of all human, non-human, living and non living things across many scales of time and space - from microbes to galaxies.

What does love look like? What does faith look like? Or ritual? worship? What does God look like? Could we teach a machine about these very abstract, subjectively human concepts? As they have no clearly defined, objective visual representations, an artificial neural network is instead trained on our subjective experiences of them, specifically, on what the keepers of our collective consciousness thinks they look like, archived by our new overseers in the cloud. Hundreds of thousands of images were scraped (i.e. autonomously downloaded by a script) from the photo sharing website flickr, tagged with these words (and many more*) to train the neural network. The images seen in the final work are not the images downloaded, but are generated from scratch from the fragments of memories in the depths of the neural network. Sound is generated by another artificial neural network trained on hours of religious and spiritual chants, prayers and rituals from around the world, scraped from YouTube.

The abstract narrative of the film takes us through the birth of the cosmos, formation of the planets and earth, rocks, and seas, the spark of life, evolution, diversity, geological changes, formation of ecosystems, the birth of humanity, civilization, settlements, culture, history, war, art, ritual, worship, religion, science, technology.

" We are all connected. To each other, biologically. To the earth, chemically. To the rest of the universe atomically."
- Neil deGrasse Tyson

" The cosmos is within us. We are made of star-stuff. We are a way for the universe to know itself."
- Carl Sagan

" How can we think in times of urgencies without the self-indulgent and self-fulfilling myths of apocalypse, when every fiber of our being is interlaced, even complicit, in the webs of processes that must somehow be engaged and repatterned? Recursively, whether we asked for it or not, the pattern is in our hands.
...
It matters what ideas we use to think other ideas with. It matters what matters we use to think other matters with. It matters what knots knot knots.
It matters what thoughts think thoughts. It matters what worlds world worlds"
- Donna Haraway

Meaning

So the film really is a brief history of almost everything. But of course, ultimately, what you see depends on who you are. The piece is intended for both introspection and self-reflection, as a mirror to ourselves, our own mind and how we make sense of what we see; and also as a window into the mind of the machine, as it tries to make sense of its observations and memories. But there is no clear distinction between the two, for the very act of looking through this window projects ourselves through it. As we look upon the abstract, slowly evolving images conjured up by the neural network, we complete this loop of meaning making, we project ourselves back onto them, we invent stories based on what we know and believe, because we see things not as they are, but as we are. And we complete the loop.

Data

* The artificial neural network is trained on images tagged with the words everything, (and many more) scraped from the photo sharing website Flickr. However, given such a diverse dataset, the artificial neural network is not given any labels regarding the data it is exposed to. It is not provided the semantic information required to be able to distinguish between different categories of images (or sounds), between small or large; microscopic or galactic; organic or human-made. Without any of this semantic context, the network analyses and learns purely on surface aesthetics. Swarms of bacteria blend with clouds of nebula; oceanic waves become mountains; flowers become sunsets; blood cells become technical illustrations.

Panels

The multiple panels of video represent related but slightly varied journeys, happening simultaneously. These journeys affect each other, but they have different characteristics. Some are slower and steadier, focusing on more long term goals, while others are quicker, more exploratory, curious, seeking shorter term rewards. Other channels represent the same journeys, but at different points of the networks training history, shedding light on how slightly more exposure to certain types of stimulus can cause the network to reinterpret the same inputs as visually and compositionally related, but with semantically vastly varying results. All of the journeys are still somehow in sync, branching and spiralling around each other.

Latent Storytelling & Narrative

The work is also an exploration into the use of Deep Generative Neural Networks as a medium for creative expression and story telling with meaningful human control over narrative. While the explorations of these so-called 'latent spaces' in generative neural networks are typically random, here, precise journeys are carefully constructed in these high dimensional spaces to create a narrative.

Research

I presented some of the techniques used for the creation of this work at the 2nd Workshop on Machine Learning for Creativity and Design at the Neural Information Processing Systems (NeurIPS) 2018 conference (one of the most prestigious academic conferences on artificial intelligence).

More information can be found here.

paper: https://nips2018creativity.github.io/doc/Deep_Meditations.pdf

code: https://github.com/memo/py-msa-kdenlive

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Deep Meditations: A brief history of almost everything (2018)

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"It feels like the machine is trying to tell me something..." - audience member Deep Meditations: A brief history of almost everything in 60 minutes is a large-scale video and sound installation; a multi-channel, one hour abstract film; a monument that celebrates life, nature, the universe and our subjective experience of it.

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Sougwen Chung is an innovative artist who creates compelling artwork through a unique collaboration with AI and robots. An award-winner recognized by aiartists.org, Chung combines personal craftsmanship with technological elements to investigate the intricate relationship between human and machine communication. As a former researcher at MIT Media Lab, she later embraced her artistic aspirations fully by becoming an Artist in Resident at Bells Labs and the New Museum of Contemporary Art in New York. The result is a body of work that is not only visually captivating but also stimulates deep thought about our evolving connection with technology.

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AI technology is beginning to shake things up in the world of food. Major companies are trying to gather all the knowledge of world food experts into an AI algorithm that can create new foods and improve existing recipes. Take, for example, IBM's AI labs working with McCormick & Company. They have been using AI to develop food products, which they hope will hit the shelves soon. The AI system takes into account data from market research and can generate flavors and formulas that humans might not think of, potentially revolutionizing the food industry.

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FlavorBot

You may not think that Tuscan chicken's creamy, garlicky flavor is due for a high-tech upgrade, but advanced artificial intelligence is on the case all the same. An AI algorithm is about to analyze and improve that and other classic recipes before designing some brand-new foods as well.

And if it goes well, we can expect AI to play a bigger role in developing the foods we eat every day. Right now, some big names are working to amass the expertise of all the world's food experts, head chefs, and flavor scientists into a single artificial intelligence algorithm that concocts new foods better and faster than any mere human.

The smartest algorithms aren't quite there, but some big names are working on it. IBM's artificial intelligence labs, famous for its Jeopardy-winning and cookbook-writing AI algorithm, Watson, have been collaborating with seasoning seller McCormick & Company's food developers and researchers for the past four years. The team's first AI-generated food products will hit the shelves later this year, according to an IBM blog post published in early February, and if all goes well, every McCormick developer will be collaborating with the AI system by 2021.

"It takes about probably ten to 15 years or so, sometimes 20 years, to become a top-notch product developer," Hamed Faridi, chief science officer at McCormick, told Futurism. "So my vision was 'how can I help the entire organization be able to develop products as good as the best developer we have in the world?'"

The end result will be AI-generated foods, flavors, and mixtures based on a deep knowledge of flavor profiles so complex that no human expert could match it.

"We have hundreds of thousands of formulas in our system," Faridi said. "Each product developer has several thousands of formulas that they use. We are collecting all of them."

Slow and Steady

Faridi explained that currently, it can take weeks or months before a new food product goes from concept to final, market-ready product.

When McCormick develops a new food product, the job, along with specific details like whether it has to be kosher or halal, and a target cost, will go to one of several hundred developers - chefs, chemists, psychologists, and other experts in food and flavor - scattered around the world. They'll then go and grab the formula for a similar product, add and remove ingredients as necessary, and test out their new idea before coming back to tweak it even more.

IBM's algorithm takes the same approach. But because it contains a broader knowledge of food and flavor than an individual expert, Faridi says the system can design a shelf-ready product in a fraction as many iterations as a person could.

A formula can go through as many as 150 iterations before ever reaching the shelf; a developer with decades of experience might be able to do it in 50. But with IBM's new AI, even less-experienced developers could do it in 50 tries as well.

"We started formulating on a serious basis with the system about a year ago, so we only have one year of data," Faridi told Futurism. "But so far it shows that we can easily take 70 percent of the work out."

Digital Values

IBM's AI system can do more than speed up the development process - it can also generate flavors and formulas that a human might not have considered.

Each human developer comes with biases. That's not necessarily a bad thing; they may simply have favorite or go-to ingredients, like particular spices, that are over-represented in their formulas. But because IBM's AI, largely comprised of a massive neural network, is trained on decades of McCormick data, the system is able to consider alternatives outside of a particular expert's wheelhouse.

The algorithm also absorbed contextual data from decades of market research - the neural net processed data on people's preferences based on factors like their culture, location, and moods.

"You want to take the context into account - once you take those into account it can generate formulas that are unique, that have never been generated before," Richard Goodwin, principal research scientist at IBM, told Futurism. "And those formulas are likely to be valued by people."

For now, the AI-generated foods set to hit shelves later this year - seasoning mixes for Tuscan chicken, bourbon pork tenderloins, and New Orleans-style sausage - are more of updated classics than anything truly groundbreaking. But Goodwin and Faridi said that they plan to push the envelope further and further in coming years as the program takes off.

"To some extent, coming up with just an odd combination of things may not be that hard, but showing that you can actually come up with something that people are a little familiar with, but come up with a very good version of it, speaks to the strength of the collaboration of the people and the machine," said Goodwin.

Robot Apprenticeship

Faridi expects that this human-machine collaboration will completely change the way foods are developed. And perhaps most importantly, he predicts that it will continue to be a collaboration where human employees are central to the process rather than automating it altogether.

Goodwin said that he envisions a future where the AI system captures the knowledge-based part of the process so that humans can focus on creating creative new products. For instance, the neural net could take away the technical side of the process, which can include determining all of the minute differences between ingredients that work well together, which ones can replace one another, and which specific form of each ingredient to choose. Goodwin gave the example that the machine would know to choose flaked garlic over powdered or diced garlic in a given recipe and would even be able to choose the correct flake size.

"The system learns these things like the apprentices who learn as they go," Goodwin said.

As the new system takes off and his team works out the kinks, Faridi expects other major players in the food industry to follow suit - he doesn't expect the deployment of AI to remain exclusive just to McCormick.

"I believe 20 years down the road, this will be the system," Faridi said. "There is no other way of making new products. We are changing the course of the industry just like the electric car. In 20, 30 years, people will look back and say, 'how did people use a gas-guzzling car?'"

READ MORE: Using AI to Develop New Flavor Experiences [ IBM Newsroom]
More on food: Edible Coating can Keep Food Fresh Longer and Cut Down on Waste

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AI trained on decades of food research can concoct better recipes

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IBM and food developer McCormick & Co developed a new AI platform that can create new foods better and faster than human experts.

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In a groundbreaking experiment, data scientists from CableTV have used a neural network to generate new lyrics based on Taylor Swift's songs, producing an impressively Swift-like song after about 50 tries.

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Poor TSwift wasn't only victimized by Kanye with the infamous "Yo, Imma let you finish," artificial intelligence is coming after her throne too. Or, depending on your perspective, allows her to get some rest and maybe invest more time in her relationships.

A team of data scientists from CableTV fed all of Taylor Swift's lyrics into a neural network in order to create new Swift lyrics, then assembled the results into a song. Not even Google Assistant's human conversation with a hairdresser surprised us as much as these results. The Taylor Swift AI managed to retain the feel of its human counterpart.

However, AI is not quite that poetic yet, as the Cable TV scientists admitted they tried for about 50 times to get a coherent result.

You can head here to listen to the one that actually pulled a convincing Taylor Swift impression. Does it remind you of starry-eyed hipsters?
Also read: ✍An AI Composed And Produced An Entire Music Album✍

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Neural Network Managed to Write a Better Taylor Swift Song - TechTheLead

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Poor TSwift wasn't only victimized by Kanye with the infamous "Yo, Imma let you finish," artificial intelligence is coming after her throne too.

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MuseNet is a deep neural network that has been created to generate four-minute musical compositions with the use of 10 different instruments, and it can combine various styles, from country to Mozart to the Beatles. Rather than being explicitly programmed with an understanding of music, MuseNet has discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of MIDI files. It utilizes the same unsupervised technology as GPT-2, which is a large-scale transformer model trained to predict the next token in a sequence, be it audio or text.

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We've created MuseNet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of MIDI files. MuseNet uses the same general-purpose unsupervised technology as GPT-2, a large-scale transformer model trained to predict the next token in a sequence, whether audio or text.

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We've created MuseNet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles. MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of MIDI files.

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The end of Halloween doesn't mean the end of the spookiness, thanks to MIT's latest creation - Shelley, the world's first AI that co-writes horror stories! After feasting on over 140,000 eerie tales from Reddit, Shelley now cooks up her own, serving the opening lines on Twitter and passing the baton to humans to carry the story forward.

Shelley isn't just another AI writer, she's a collaborative story-spinner, weaving hair-raising narratives with her human counterparts. The variety of stories range from short, intense 8-tweet exchanges to sprawling 77-tweet sagas, with Shelley adding her chilling touch at every turn.

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Halloween's over and you're probably left with too much candy and a face of make-up. But that's not all; thanks to MIT, you also have the chance to experience the magic of A.I. for more than one night. Shelley, the world's first collaborative A.I. horror writer, came to life on this occasion but its spooky stories are just getting good #machinemagic

With October 31st in mind, the Massachusetts Institute of Technology trained the neural network "on over 140,000 horror stories on Reddit's popular r/nosleep subreddit, and is able to generate random snippets based on what she learned, or continue a story given a text. " They let it loose on Twitter, under the name of Shelley after the horror story writer, Mary Shelley.

This is not the first A.I. writer but it is the first that comes up with horror stories with the help of humans. Using its Twitter account, Shelley shares the beginning of a story with its followers every hour. This is always accompanied by the hashtag #yourturn, so human fans know they're invited to continue it.

And they actually do. There are threads ranging from 8 tweets and 3 participants to those containing 77 tweets and 7 participants. And after each input, the A.I. comes with another one of its own. Needless to say, Shelly is slowly but surely becoming a social media star.

All in all, MIT says their artificial intelligence has co-authored over 100 stories to date and is likely to write much, much more. Last year, for Halloween, MIT used neural networks to produce scary images.

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Meet Shelley, The World's First Collaborative A.I. Horror Writer - TechTheLead

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Halloween's over and you're probably left with too much candy and a face of make-up. But that's not all; thanks to MIT, you also have the chance to experience the magic of A.I. for more than one night. Shelley, the world's first collaborative A.I.

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Consider this crazy thing called Deep Nostalgia AI. It's like Harry Potter magic in our world, bringing old still photos to life by turning them into animated videos. It's like doing an iPhone Live Photo backward - instead of choosing the best shot from a short video, this program takes a single, old-school portrait photo and gets it moving!

And that's not all. There's another super cool way AI is jazzing up old pictures - by splashing them with color. A team of geniuses trained an AI to play the role of a digital artist, filling in the colorless parts in a way that lets us see what the world looked like in the past. Ever wanted to know the real colors of Abraham Lincoln's suit, Albert Einstein's hair, Frida Kahlo's attire, or Bertrand Russell's eyes? Now you can! The results are honestly mind-blowing!

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Wow! This ‘Deep Nostalgia’ AI Turns Old Photos Into Video Animations

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Online genealogy company MyHeritage took Twitter by storm with this Deep Nostalgia AI tool, which turns old family pictures into animated videos. The service creates videos from still photos, kind of like a reverse iPhone Live Photos – instead of taking a video to let you pick the best photo later o…

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In an experiment conducted by researchers from Rutgers University, Facebook, and the College of Charleston, participants rated computer-generated artwork as more novel, complex, and surprising than human-made art. The research aimed to determine whether artificial intelligence (AI) can generate art that is indistinguishable from that made by people, posing a sort of artistic Turing test for creativity. The researchers were surprised when participants often attributed the AI-generated art to humans, not computers. Despite this, the debate about whether computers can be truly creative remains, as they are programmed by humans. However, computers have made art more accessible to many people, with the lines between programmers and artists becoming increasingly blurred. The rise of AI in art has led to the development of computational creativity, a field dedicated to exploring creativity through the use of computer tools. However, the interpretation and valuation of such AI-generated art is subjective and remains a point of contention.

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Computers take art in new directions, challenging the meaning of “creativity” | Proceedings of the National Academy of Sciences

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Computers take art in new directions, challenging the meaning of “creativity”

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Stanford University researchers have developed a generative AI model called Editable Dance GEneration (EDGE), which can choreograph human dance animations to match any piece of music. The tool is designed to assist choreographers in designing sequences and visualizing 3D dance sequences. With its unique feature of editability, EDGE can seamlessly generate an entire body movement from a specific limb position designated by an animator. In the future, users could input their own music and demonstrate moves for the system to learn from.

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Stanford University School of Engineering

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AI-powered EDGE dance animator applies generative AI to choreography

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AI analyzes the music’s rhythmic and emotional content and creates realistic dances that are also physically plausible — a real dancer could perform them.

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Exploring the Future of Architecture with AI: How Artificial Intelligence is Transforming the...

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Artificial Intelligence (AI) is revolutionizing the field of architecture by aiding in creating detailed digital models of buildings, generating innovative designs, and facilitating smart, adaptive features in structures. It's also streamlining construction by enhancing collaboration, minimizing errors, and boosting efficiency, leading to quicker, more cost-effective projects.

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Artificial Intelligence (AI) is rapidly changing the way we design, build, and manage our built environment.

From creating more energy-efficient buildings to streamlining the construction process, AI is transforming the architecture and construction...

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Exploring the Future of Architecture with AI: How Artificial Intelligence is Transforming the...

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Artificial Intelligence (AI) is rapidly changing the way we design, build, and manage our built environment. From creating more energy-efficient buildings to streamlining the construction process, AI...

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Generative AI is revolutionizing filmmaking by transforming content generation, visual effects, post-production, budgeting, audience engagement, and creative inspiration. This technology enables autonomous generation of scripts, storyboards, and scenes, creating realistic CGI and enhancing post-production workflows. AI can also optimize budgets by analyzing production costs, box office performance, and audience behavior, offering insights for more cost-effective strategies. Furthermore, it can provide creative inspiration by generating art, music, and other elements to aid in storytelling and character development. This AI-driven revolution is reshaping filmmaking from independent productions to major studios, suggesting a transformative future for the industry.

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Computers and humans are learning how to adapt to this new era of filmmaking.

Generative AI, powered by machine learning algorithms, is revolutionizing the filmmaking industry, from independent productions to major studios.

This cutting-edge technology is changing the way films are conceptualized, developed, and produced. With its ability to generate content, create visual effects, optimize budgets, and enhance post-production workflows, generative AI is transforming the filmmaking process and providing new opportunities for creative expression.

It's sweeping Hollywood. We've been seeing it everywhere at NAB 2023 as people from every background are experimenting with it.

So let's look at what its effect on cinema has become.

How is Generative AI Changing Filmmaking From Indies to Studios?

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From Indies to Studios, Generative AI Is Changing Filmmaking

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Computers and humans are learning how to adapt to this new era of filmmaking.

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Firmenich, a Swiss flavor and fragrance company, is utilizing artificial intelligence (AI) to develop plant-based meat substitutes, aiming to tap into a market that could reach $200bn by 2030. The AI, named Sam, works with a team of flavorists, including renowned French chef Nicolas Maire, and uses machine learning to understand and combine flavors, quickly generating new formulas that help create plant-based foods that accurately mimic the taste of their animal counterparts.

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Nicolas Maire has accumulated 18 Michelin stars during his career

Nicolas Maire is the model of a professional French chef with years of experience and 18 Michelin stars under his belt, a man who dominates his kitchen dispensing nuggets of culinary wisdom as he prepares food for his guests.

Today, this kitchen is buried inside a sprawling corporate HQ on the outskirts of Geneva. Mr Maire works for Firmenich, a business with a perfume industry pedigree stretching back to 1895.

Firmenich's nose for a new market saw it diversify into food ingredients as the public appetite for alternatives to meat led to a scramble to put plant-based food on supermarket shelves.

The company says there is a global market for plant-based meat substitutes of $25bn (£19bn) and believes this will grow to $200bn by 2030.

To help perfect the flavours of these innovative foods, Mr Maire has a new sous-chef in the form of Sam, an artificial intelligence (AI) robot.

New plant-based foods have raised demand for flavouring

Along with a team of flavourists, Sam helps blend a huge array of flavours for clients.

In humans the sense of taste stems from multiple receptors that are primed to alert our brains to the nature of any possible food we encounter.

Sam lacks this sense of taste, but it has been trained on a database of ingredients gathered over 60 years at the company.

Using a technique called machine learning, it has raced through examples of flavour combinations and has learnt its own definitions, maturing over 18 months into today's AI robot.

Eric Saracchi runs the digital side of Firmenich: "Flavours are more complex than perfumes," he says, and Sam had to understand what a strawberry is, or how grilled beef hits the tongue, before finding matches between tastes and plant foodstuffs.

The robot is primed with so many ingredients it is known internally as "a piano with 5,000 keys".

That piano is played by the company's team of human flavourists.

The top tasters are the master flavourists, and out of some 30 in the world six work at Firmenich.

Creators of flavours are so rare, "you can't replace them, you can only enhance them," says Mr Saracchi.

Patrick Salord is principal flavourist at Firmenich

Flavourists are at the heart of Firmenich, and Patrick Salord is its principal flavourist.

"Being a flavourist is a combination of art and science. I took a masters degree in chemistry before I began this career. We train to pick the best ingredients to achieve the flavour we want. We evaluate and describe them and compare them."

He uses certain aromas and tastes to mask "off-notes" such as acidic tastes while giving a formula the right texture. He talks of the tonality of food, how removing one tiny ingredient can change the overall taste.

Sam takes the knowledge of flavourists and generates new formulas in minutes, a fraction of the time Mr Salord and his team take using their own skills. "It suggests a formula that is in line with our senses."

One big advantage of an AI robot is that it has no cognitive bias. This lack of human prejudices helps Firmenich to get past any unconscious leanings of the flavourists.

The objectivity of Sam, devoid of influences that can sway even the most professional of flavourists, allows it to work at speed. "It adds value by combining the knowledge of all the other flavourists here," says Mr Salord.

The machine rapidly gives an indication of how a flavour can be created and how much of an ingredient should be included. And Sam can hold the line between Mr Salord's team of flavourists and public tastes, refereeing decisions when the flavourists' view differs from that of a consumer panel.

But the finished product needs more - and that's what Mr Salord's team bring to the tasting party, which belongs to the start of the day.

"We try to taste in the morning before we have coffee. By the afternoon your sense of taste becomes tired and affected by lunch. So we leave the afternoon for work on the computer."

More technology of business:

Back in Mr Maire's kitchen the cross-fertilisation between flavourist and robot is coming out of the frying pan. He is accustomed to hosting business clients, searching for a specific taste they can drop into foodstuffs on supermarket shelves.

The flavourists remain his close colleagues, even though AI is "a powerful, beautiful tool." And he rates the taste of UK consumers highly. "It's an advanced market with many vegan people." Firmenich is betting big on the rest of the world changing their food habits in line with the British.

He concedes that this marriage of science and culinary arts has its critics. "When you say chemicals it's not sexy for gastronomy."

His triumphant retort is to brandish thick slices of a pale juicy meat that tastes like a good cut of chicken but springs from Sam's recipe for vegetable protein, resembling a paste. "The essence of what we do is innovation, for me molecules are another flavour."

Mr Maire maintains he is ready to whip up Christmas turkey and more from plant-based ingredients. "We are only at the beginning of what can be done. We have the competency to make Christmas pudding flavours too."

His beef burger is less appealing, in the mouth sausage seems to be a dominant taste rather than beef. Sam and the flavourists have more work to do.

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AI: Why chefs are turning to artificial intelligence

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How a robot is being used in the highly specialised business of creating flavours.

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A portrait generated by artificial intelligence, created by the French art collective Obvious, sold at Christie's auction house for $432,500, over 40 times its initial estimate, outpacing works by renowned artists like Andy Warhol and Roy Lichtenstein. This marked the first time an AI-generated portrait was put up for auction, sparking debate within the art community about the originality and future of AI in art.

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AI Art at Christie’s Sells for $432,500 (Published 2018)

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A portrait produced by artificial intelligence sold for more than 40 times Christie’s initial estimate of $7,000-$10,000.

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In this video, the speaker explores the exciting potential of AI Artistry, particularly focusing on the platform, Midjourney, which allows users to generate images from text prompts. The 20 showcased prompts are designed to inspire creativity and include a range of styles from vintage and modern photography to surrealism, sketches, and iconic art inspired by the masters. The speaker emphasizes the platform's versatility, as it allows users to personalize the prompts and experiment with different artistic styles. They also encourage users to try these prompts in other AI image generators like Leonardo or Sea Art for varied results. Furthermore, the video provides insights into creating abstract, fantasy, and emotionally driven pieces, leveraging the unique features of AI-powered art creation.

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TOP 20 Midjourney Prompts That Will BLOW YOUR MIND

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Draw to Art is an innovative tool that uses machine learning to match user's sketches to famous paintings, drawings, and sculptures, offering a unique way to explore hundreds of thousands of artworks worldwide. Developed in collaboration with Google Creative Lab London and the Google Arts & Culture Lab in Paris, this experiment aims to utilize cutting-edge machine learning technology to provide a simple, yet magical, experience enabling everyone to explore the diverse collection on Google Arts & Culture through their own doodles.

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Every great work of art started as a sketch, but what if your sketches could help you discover great works of art?

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When Google Arts & Culture Lab integrated artificial intelligence with acclaimed choreographer Wayne McGregor's extensive archive, it resulted in "Living Archive," a creative tool that allows anyone to draw inspiration from McGregor's work to craft their own dance choreography. Leveraging U-MAP, the platform organizes nearly half a million moments of movement from McGregor's 25-year archive based on visual similarity, enabling users to choose and connect various poses to design their unique dance piece. Additionally, the platform offers an adventurous feature where users can strike a pose with their camera to find the closest matching pose within the archive.

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Explore thousands of movements from Wayne McGregor's 25-year archive of choreography #LivingArchive @WayneMcGregor @GoogleArts

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Assisted Melody allows users to create melodies in the unique styles of classical maestros Mozart and Beethoven for World Music Day. In addition to composing on the maestros' favorite instruments, such as Mozart's harpsichord, users can also hear their compositions played on a variety of modern instruments, ranging from the flute to the synthesizer.

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Create melodies with the help of maestro composers.

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Paint With Music is an interactive tool that merges painting and music composition, using machine learning from Magenta's DDSP library to convert brush strokes into musical notes played by a selected instrument. It offers a variety of sensorial canvases, such as the sky or ocean, each providing unique sound effects to enhance the user's composition.

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Paint With Music is an interactive experience which connects two major forms of artistic expressions: painting and musical composition. With the help of machine learning powered by Magenta's DDSP library (Differentiable Digital Signal Processing), the movement of your brush strokes is translated into musical notes performed by an instrument of your choice.

A wide range of sensorial canvases, from the sky to the ocean, are ready to take your composition to the next level by incorporating special sound effects unique to each ambiance.

Try it now on your desktop or Android device.

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Paint with Music by Artists in residence at Google Arts & Culture Lab: Simon Doury, Caroline Buttet - Experiments with Google

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Since 2009, coders have created thousands of amazing experiments using Chrome, Android, AI, WebVR, AR and more. We're showcasing projects here, along with helpful tools and resources, to inspire others to create new experiments.

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Blob Opera is a fun, interactive machine learning experiment created by David Li in partnership with Google Arts and Culture. This project allows anyone to create beautiful opera music using four virtual opera voices in real time, without needing any singing skills. It was made by training a machine learning model called a Convolutional Neural Network on 16 hours of singing from four opera singers. However, the sounds produced aren't their actual voices but rather the model's interpretation of opera singing. Users can control the pitch and vowel sounds of the virtual singers by dragging the blobs up, down, forwards, or backwards, and another machine learning model allows these blobs to harmonize based on your input.

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Create your own ML-powered opera song! by David Li with Google Arts & Culture

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Giga Manga is an online tool that uses machine learning to help users create unique manga characters from simple sketches and colors, offering suggestions based on a model trained on over 140,000 high-resolution images. Additionally, the tool utilizes the Adeleine colorization model to color drawings based on user's inputs, and leverages CLIP, OpenCV, and the ANNOY library to find the closest match to the created character in the Google Arts & Culture manga collection.

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XYZ Toy is an interactive word guessing game where each tile holds a letter, created using a font generated by Google AI, that provides visual clues for the winning word. Developed based on Google AI's image generation research and with special recognition to Irina Blok of Google Research, players are given five chances to guess the word by examining the unique typography details and tapping into the empty tiles.

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XYZ Toy is a word guessing game and the clue is in the typography. Each tile contains a letter in a font generated by Google AI which reveals visual clues on the winning word.

Zoom in to each letter to see the details of the typography and make your guesses by tapping into the empty tiles. You have five chances before the game is over.

XYZ Toy has been inspired by Google AI image generation research.

Special thanks to Irina Blok, Google Research

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XYZ Toy by Gael Hugo, Artist in Residence at Google Arts & Culture Lab - Experiments with Google

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Since 2009, coders have created thousands of amazing experiments using Chrome, Android, AI, WebVR, AR and more. We're showcasing projects here, along with helpful tools and resources, to inspire others to create new experiments.

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Da Vinci Stickies is an interactive, 21st-century inspired session that uses Google AI tools to allow users to combine and manipulate sketches from Leonardo da Vinci's codices, encouraging them to explore and generate innovative ideas in a manner reminiscent of the Renaissance master.

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Da Vinci Stickies - Google Arts & Culture

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Step a little further into the imagination and notebooks of Leonardo Da Vinci, and dream up new ideas with the help of Google AI.

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Haiku Imagined is a poetry project featuring AI generated visual and audio elements, bringing classic and modern haiku poems to life in a unique and interactive way. It's like a blend of poetry, art, and tech, offering a fresh and engaging way to experience these timeless poems.

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Take a pause: experience traditional and modern haiku lovingly illustrated and animated with AI generated music, fonts, and video.

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POEMPORTRAITS is a unique AI project where you donate a word to generate a two-line poem, which then illuminates a portrait of your face. Created by Es Devlin in collaboration with Google Arts and Culture, this project blends poetry, AI, and interactive selfie filters to create an evolving collective poem and push the boundaries of technology.

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POEMPORTRAITS by Es Devlin. Donate a word to become part of a collective poem and create your own POEMPORTRAIT. A collaboration with Google Arts and Culture and Ross Goodwin.