# data[].attributes.attachment_link.readable_text
There are more artworks by dead men stored in museums than can be exhibited. What remains is the virtual, imaginary area, with it's almost infinite amount of room.

Instead of continuing the current trend of art as "temporary intervention", we use the space between the worlds as a self-determined, permanent and experimental playground, with the goal to reawaken imagination and collaboration in public space.

We challenge the status quo and redefine the concept of the museum, rethinking the questions:

# data[].attributes.attachment_link.description
There are more artworks by dead men stored in museums than can be exhibited. What remains is the virtual, imaginary area, with it's almost infinite amount of room. Instead of continuing the current trend of art as "temporary intervention", we use the space between the worlds as a self-determined, permanent and experimental playground, with the goal to reawaken imagination and collaboration in public space.

# data[].attributes.attachment_caption
Abb. 1: Standardisierte Current Source Density Power (CSD) einer Versuchsperson im Wachen mit geschlossenen Augen (oben), während des luziden Traums (Mitte) und

# data[].attributes.body
https://www.researchgate.net/publication/311734175_Neuronale_Grundlagen_des_luziden_Traumens

# data[].attributes.body
https://www.luciddreamer.com/learn-more/how-to-lucid-dream/

# data[].attributes.attachment_link.readable_text
The basics of tACS

Transcranial Alternating Current Stimulation (tACS) is a device that applies a low-intensity sinusoidal electrical current to the brain through electrodes on the scalp. The technique can be painless and is thought to boost the brain's own oscillations, which can be used to treat disease or enhance brain function. In many ways tACS is similar to tDCS as a neuromodulatory technique, but instead of applying a direct electrical current, tACS oscillates a sinusoidal current at a chosen frequency to interact with the brain's natural cortical oscillations. Generally, a large electrode is placed over an area of interest which applies stimulation while a reference electrode is placed in a neutral location. When a single, low frequency (< 100 Hz) frequency is applied the exogenous oscillation can synchronize with the brain's endogenous frequency. This is typically what tACS is. When several oscillations are pulsated, desynchronization of cortical oscillations can occur. As such, tACS effects are contingent on the frequency, amplitude, and phase applied. tACS applied in the EEG frequency range (0.1-80Hz) can entrain neural oscillations, augmenting them. In higher ranges (1-5 kHz), oscillation interaction is unlikely to occur, but cortical excitability has been suggested ¹. tACS has recently become more popular with more clinical trials and even consumer devices, but it has a history that dates back decades ².

How does transcranial Alternating Current Stimulation (tACS) change the brain?

The exact mechanisms of action tACS are still unclear, but the effects are thought to relate to the manipulation of brain oscillations. ³ Brain oscillations (or brain rhythms) are always happening in the brain and impact how we think, feel, and relate to brain disease. To change brain oscillations with tACS, is a way to tap into and control brain functions.

What is transcranial Alternating Current Stimulation (tACS) used for?

tACS has been tested in human trials to both treat brain disease and to enhance brain function in health individuals ⁴ Some areas tACS is currently being explored include: Depression ⁵, Parkinson's, Schizophrenia, tumor retardation, cognitive enhancement, Tinnitus ⁶ , and motor performance. But the regulatory (approval) status of tACS varies depending on the jurisdiction and what it is used for.

Is transcranial Alternating Current Stimulation (tACS) FDA approved?

tACS is not FDA approved for medical use in the USA. This does not mean the USA FDA has any decision on the efficacy or safety of transcranial Alternating Current Stimulation for any use. In the US tACS for medical use is therefore considered "Investigational". The FDA also does not regulate the practice of medicine, meaning they don't regulate doctors. For this reason many doctors can provide tACS treatments "off-label" provided they follow all other regulations that apply to their practice. The FDA regulated medical use, for tACS for "wellness" can fall outside any FDA regulation. ⁷ Wellness could be things like generally feeling better, thinking better.

What are the side effects of tACS?

According to clinical trials, the side effects of tACS are relatively mild and short lasting ⁸. They include itching, tingling, and redness under the electrodes and also light flashes of light called phosphenes. All these effects go away after the tACS is turned off. There are other side-effects that have been reported following tACS such as headache but these can occur at the same rate as sham (sugar pill) stimulation, which means they may just randomly happen and so are not a result of tACS.

Is transcranial Alternating Current Stimulation (tACS) safe?

Transcranial Alternating Current Stimulation (tACS) is considered by clinicians and researchers as safe, in the sense that it does not produce any lasting harm.The term Serious Adverse Event is used in clinical trials to describe an unsafe effect, such as one that requires a trip to the hospital. Based on current testing, tACS does not produce serious adverse events.

Is transcranial Alternating Current Stimulation (tACS) and Cranial Electrotherapy Stimulation (CES) the same?

If tACS and CES are the same depends on definitions ⁹. If tACS is defined as using a basic sinusoidal current and CES is a more complex mix of waves, then they are not the same. But if both tACS and CES are defined as stimulating the head with a current of a few mA intensity that oscillates back and forth, then they are the same.

Where can I get tACS?

Getting tACS will depend on where you live and what you want to use it for. There are consumer devices for tACS that can be purchased directly, and there are medical tACS devices that only a doctor or a researcher can use.

References

1. Antal, A., Boros, K., Poreisz, C., Chaieb, L., Terney, D., & Paulus, W. (2008). Comparatively weak after-effects of transcranial alternating current stimulation (tACS) on cortical excitability in humans. Brain stimulation, 1(2), 97-105. 2. Guleyupoglu B, Schestatsky P, Edwards D, Fregni F, Bikson M. Classification of methods in transcranial Electrical Stimulation (tES) and evolving strategy from historical approaches to contemporary innovations. Journal of Neuroscience Methods 2013; 219: 291-311 3. Reato D, Rahman A, Bikson M, Parra LC. Effects of weak transcranial Alternating Current Stimulation on brain activity - a review of known mechanisms from animal studies. Frontiers of Human Neuroscience 2013; doi 10.3389/fnhum.2013.00687 4. Lang S, Gan LS, Alrazi T, et al. Theta band high definition transcranial alternating current stimulation, but not transcranial direct current stimulation, improves associative memory performance. Sci Rep 2019;9:8562. 5. Alexander ML, Alagapan S, Lugo CE, et al. Double-blind, randomized pilot clinical trial targeting alpha oscillations with transcranial alternating current stimulation (tACS) for the treatment of major depressive disorder (MDD). Transl Psychiatry. 2019;9(1):106. Published 2019 Mar 5. doi:10.1038/s41398-019-0439-0 6. Claes L, Stamberger H, Van de Heyning P, De Ridder D, Vanneste S. Auditory cortex tACS and tRNS for tinnitus: single versus multiple sessions. Neural Plast. 2014;2014:436713. doi:10.1155/2014/436713 7. Bikson M., Grossman P., Thomas C., Zannou A. L., Jiang J., Adnan T., et al. (2016). Safety of transcranial direct current stimulation: evidence based update 2016. Brain Stimul. 9 641-661. 10.1016/j.brs.2017.07.001 8. Matsumoto, Hideyuki, and Yoshikazu Ugawa. Adverse Events Of Tdcs And Tacs: A Review. 2020. 9. Guleyupoglu B, Schestatsky P, Edwards D, Fregni F, Bikson M. Classification of methods in transcranial Electrical Stimulation (tES) and evolving strategy from historical approaches to contemporary innovations. Journal of Neuroscience Methods 2013; 219: 291-311

Find top tDCS doctors in your area

Neuromodec offers a free unbiased search tool that helps connect patients with top tDCS specialists in their area

Ad

Ad

Ad

# data[].attributes.attachment_link.title
What is transcranial Alternating Current Stimulation (tACS)?

# data[].attributes.attachment_link.description
Transcranial Alternating Current Stimulation (tACS) is a device that applies a low-intensity sinusoidal electrical current to the brain through electrodes on the scalp. The technique can be painless and is thought to boost the brain's own oscillations, which can be used to treat disease or enhance brain function.

# data[].attributes.body
https://de.wikipedia.org/wiki/Stephen_LaBerge

# data[].attributes.headline
LUCID DREAMING AS A LEARNABLE SKILL: A CASE STUDY

# data[].attributes.subject
LUCID DREAMING AS A LEARNABLE SKILL: A CASE STUDY

# data[].attributes.body
STEPHEN P. LA BERGE
Stanford University

# data[].attributes.body
https://en.wikipedia.org/wiki/Lucid_dream

# data[].attributes.attachment_link.readable_text
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen
Engineering, Design, Product, and Prototyping
Jeff Belgum, Dave Cummings, Jonathan Gordon, Chris Hallacy, Shawn Jain, Joanne Jang, Fraser Kelton, Vishal Kuo, Joel Lehman, Rachel Lim, Bianca Martin, Evan Morikawa, Rajeev Nayak, Glenn Powell, Krijn Rijshouwer, David Schnurr, Maddie Simens, Kenneth Stanley, Felipe Such, Chelsea Voss, Justin Jay Wang
Comms, Policy, Legal, Ops, Safety, and Security
Steven Adler, Lama Ahmad, Miles Brundage, Kevin Button, Che Chang, Fotis Chantzis, Derek Chen, Frances Choi, Steve Dowling, Elie Georges, Shino Jomoto, Aris Konstantinidis, Gretchen Krueger, Andrew Mayne, Pamela Mishkin, Bob Rotsted, Natalie Summers, Dave Willner, Hannah Wong
Acknowledgments
Thanks to those who helped with and provided feedback on this release: Sandhini Agarwal, Sam Altman, Chester Cho, Peter Hoeschele, Jacob Jackson, Jong Wook Kim, Matt Knight, Jason Kwon, Anna Makanju, Katie Mayer, Bob McGrew, Luke Miller, Mira Murati, Adam Nace, Hyeonwoo Noh, Cullen O'Keefe, Long Ouyang, Michael Petrov, Henrique Ponde de Oliveira Pinto, Alec Radford, Girish Sastry, Pranav Shyam, Aravind Srinivas, Ilya Sutskever, Preston Tuggle, Arun Vijayvergiya, Peter Welinder

# data[].attributes.attachment_link.description
DALL·E 2 is an AI system that can create realistic images and art from a description in natural language.

# data[].attributes.attachment_link.readable_text
The original idea comes up to me when I was bored from live shows. I do love music, but actually, I feel boring to play visuals now, even live. I feel a lack of sense in this process rather than entertain people. So, I quit for a while with visual live shows. And I always more interesting in a pure algorithmic output rather than me staying there and controlling knobs and parameters. You will often see me in the crowd during my live set just enjoying the flow of the machine.

So it`s not a surprise that AI-generated visuals get my attention. recent year lot of interesting things and research happen in that field, but I did n`t saw much cross-field adversarial networks. I decide to do a small experiment by myself to generate images based on the audio input without human intervention in the process.

Pix2Pix, why?

For my experiment I choose Pix2Pix. Why? It is an interesting way to teach machines to find a relationship and convert one image into another. From the similarity of style, day-to-night image, or drawing to photo. It also shows himself with quite fast training and appropriate result.

You can find more info and examples on Pix2Pix on this guide.

I think some of you already saw this video that can be a good example

more examples and Memo Akten works you can find http://www.memo.tv/works/gloomy-sunday/

So, the decision was made.

For this project, I choose this repository based on PyTorch (after a few test I think it works faster and more stable than TensorFlow version). You can follow the instruction in the repo to train your own model or use already pretrained.

But, how? I want to transform an audio signal into an image. To train and implement the Pix2Pix model I need to have an image as input and output. Let`s see how we can trick it.

Training model

We are living in the information age where most of the information represented in the digital format. As long its a digital - it doesn`t matter anymore what type it is. Video, Audio, text, everything became just a sequence of numbers.

When I started my media/digital experiments it was one of the biggest insights that always help me with projects. From conceptual to optimization side.

# data[].attributes.attachment_link.description
The original idea comes up to me when I was bored from live shows. I do love music, but actually, I feel boring to play visuals now, even live. I feel a lack of sense in this process rather than...

# data[].attributes.headline
David O Reilly - The Infinite Art Scenario

# data[].attributes.subject
David O Reilly - The Infinite Art Scenario

# data[].attributes.attachment_link.readable_text
Consider how the following scenario might play out: you train an AI with your own particular likes and dislikes, and every consideration you could put into your work. Eventually it takes over and makes everything for you so you can slack off.

It can enable you to work in all forms, creating films, books, albums, designing fashion, sculpture, architecture - each can have your personality and style. It can then go further and tweak your work for every member of your audience depending on their preferences.

Then it keeps going after you die, simulating new inspiration, and imagining how you'd incorporate changes in the world from beyond the grave.

Of course, you're not actually needed in this equation at all. The AI can generate its own compelling artists and invent hundreds of new genres every second, differentiating each appropriately, and providing everyone with an endless, ever-updating array of original media, all tailored to their interests and aesthetic tastes.

In the Infinite Art Scenario, there's no need for artists, because everyone is completely satisfied by what's generated for them.

This feels within the realm of possibility.

I can think of at least 3 reasons it will not play out. I may be proven wrong on all, but I'll share them anyway.

1. Large companies will continue to control these technologies, and all are extremely risk averse. They will limit expression within safe bounds, and produce volumes of bland, inoffensive content. Over time, we'll find it all boring and crave whatever is being censored.

2. Whatever we perceive as being produced automatically, we don't value as much as what we know was difficult. Seeing a self-playing-piano and an accomplished pianist are vastly different experiences, though the music may be identical.

3. AI may become associated with manipulation and control, and provoke repulsion and disgust from humanity. We may relegate it to specific use cases with human-readable inputs and outputs.

Delving a little deeper into these.

The problem with creative-AI is analogous to the dilemma many creators now face; how to be expressive in public without getting canceled.

Dall-E censors a vast amount of prompts without telling the user what word or phrase is off limits. Google has shown off its Dall-E competitor, but are holding it back on the grounds that it's too offensive.

there is a risk that [it] has encoded harmful stereotypes and representations, which guides our decision to not release [it] for public use without further safeguards in place. source.

Dall-E's solution to this problem was to secretly add "woman" and "black" to prompts.

This reveals a few things. When AI's outputs are problematic, the company will be held responsible, not whoever entered the prompts. Imagine a pencil manufacturer being sued for a racist drawing or bad words it wrote. This is why this species of AI does not fit neatly into the idea of a tool. Its entire value is built on massive amounts of indiscriminately harvested creative material, which nobody signed up for.

Uncensored versions of these technologies will become available, but by then the corporate ones will have moved further on - into motion, storytelling and interactivity. It's possible that the cutting edge of AI will always be creatively castrated.

The idea that censorship leads audiences to other domains is already evident. Streaming services dump tons of algorithmically aligned content online, but it seems hard to find anything worth watching. It all seems so fake. We are more likely to listen to an individual voice to tell us the truth than we are a business or hyperintelligent being.

Our knowledge of AI's capability alters our interpretation of its output. If a work is perceived as being easy, or carried out by the will of the form (or intelligent tools) we tend to write it off.

Consider how we tend to ignore most of the natural world and all its intricate forms, just as we do the infinite perfection of fractals or the billions of images of our planet on Google Earth, each beautiful in their own way. We seek the edges of human potential, and find meaning in what people spent time on, everything else is noise.

Of course, anyone can claim their AI-generated work was created by hand, this will likely be a good grift for a while, but as people catch on we'll get bored and seek new terrains of complexity - whatever AI cannot yet do, or convince us of doing.

AI's attempt to make digital zombies of us may lead to an uncanney-valley-esque feeling of disgust.

AI can already override our ability to authenticate images and sounds, and is likely to permanently undermine our trust of digital information. Assuming it will be trivial for AI to keep us entertained, how can we trust that's all it's doing? Because it can lie more effectively than anyone, and is essentially playing dumb with us, we can never be sure if we're being manipulated.

We might roll our eyes when we see an ad online for something we talked about in real life, but the danger is when these systems operate beneath our perception. Being made to think and behave a certain way without being aware of it, automated consent, seems inevitable.

We may come to consider AI as we do Nazism - a different incarnation of hyper-efficiency at the expense of humanity, or Stasi Germany, and its obsession with data collection. Millions once believed these systems were for the greater good, but they ran their course and turned out to be perverse, evil and inhuman.

The idea of the The Infinite Art Scenario has haunted me for some time. It would be dark not just for creativity but for our species, yet we seem to accelerate towards it with glee.

As a reminder, you cannot be commodified by machine, because you are a breathing physical being of unimaginable complexity. You exist in a circumstance that has never occurred before, that you can make anything of, and you are changing in every way - and so is the world. And you will die, and so will it.

The marks you make during your life are there to help others along before that happens. The overlooked beauty and unspeakable horrors of life will always need description through art, and this will have to be carried out by individuals, like you.

# data[].attributes.attachment_link.description
Consider how the following scenario might play out: you train an AI with your own particular likes and dislikes, and every consideration you could put into your work. Eventually it takes over and makes everything for you so you can slack off.

# data[].attributes.attachment_link.description
Erkunde Markus Wintersbergers Pinnwand „Artificial intelligence" auf Pinterest. | Weitere Ideen zu künstliche Intelligenz, Zeichentechniken und Industrie.

# data[].attributes.headline
AI-aesthetics and the Anthropocentric Myth of Creativity

# data[].attributes.subject
AI-aesthetics and the Anthropocentric Myth of Creativity

# data[].attributes.attachment_link.readable_text
AI-aesthetics and the Anthropocentric Myth of Creativity

Publication data:

Emanuele Arielli and Lev Manovich,"AI-aesthetics and the Anthropocentric Myth of Creativity," Forthcoming in Nodes Journal of Art and Neuroscience (nodesjournal.com), Fall 2022.

From the article:

Suppose human creativity could be potentially replicated by mechanical processes. In that case, we would face a crossroads: either we could give up using the concept of creativity altogether, or if we hold to our common understanding of what creativity is, we could agree to apply this concept to non-human phenomena as well, as world champion Lee Sedol did when judging the performance of AlphaGo. However, the idea that artificial creativity discloses the mechanic nature of human creativity should also be met with a bit of critical detachment, particularly if we consider the specific case of the arts. In fact, artificial reproductions of human artifacts do not follow the same processes with which humans actually produced those artifacts. Nobody thinks that Mondrian followed procedures similar to the algorithm used in 1966 that generated pseudo-Mondrian, even though the public appreciated the artificial images more than the original ones....

# data[].attributes.attachment_link.description
Publication data: Emanuele Arielli and Lev Manovich,"AI-aesthetics and the Anthropocentric Myth of Creativity," Forthcoming in Nodes Journal of Art and Neuroscience (nodesjournal.com), Fall 2022. From the article: Suppose human creativity could be potentially replicated by mechanical processes.

# data[].attributes.headline
Artificial Aesthetics: A Critical Guide to AI, Media and Design

# data[].attributes.subject
Artificial Aesthetics: A Critical Guide to AI, Media and Design

# data[].attributes.headline
How an award-winning AI film was brought to life by text-to-video generation 

# data[].attributes.subject
How an award-winning AI film was brought to life by text-to-video generation 

# data[].attributes.attachment_link.readable_text
If you're impressed by the recent spate of text-to-image generators, get ready for the next step in AI artistry: text-to-video.

While the huge compute costs and scarcity of text-to-video datasets have stunted the technique's growth, recent research has brought the promise closer to reality.

A computer artist called Glenn Marshall has given a glimpse at the potential.

The Belfast-based composer recently won the Jury Award at the Cannes Short Film Festival for his AI film The Crow.

Marshall had previously earned plaudits for an AI-generated Daft Punk video, but he applied a different approach to The Crow.

While his earlier technique turned text into random visual mutations, The Crow uses an underlying film as an image reference.

"I had been heavily getting into the idea of AI style transfer using video footage as a source," Marshall told TNW.

"So every day I would be looking for something on YouTube or stock video sites, and trying to make an interesting video by abstracting it or transforming it into something different using my techniques.

"It was during this time I discovered on YouTube - a short live action dance film - which would become the basis of The Crow."

Marshall fed the video frames of Painted to CLIP, a neural network created by OpenAI.

He then prompted the system to generate a video of "a painting of a crow in a desolate landscape."

My AI film 'The Crow' wins Jury Award at Cannes! https://t.co/WHDsI7UzJM pic.twitter.com/Ww1DGyBbxw

- Glenn Marshall (@GlennIsZen) August 24, 2022

Marshall says the outputs required little cherry-picking. He attributes this to the similarity between the prompt and underlying video, which depicts a dancer in a black shawl mimicking the movements of a crow.

"It's this that makes the film work so well, as the AI is trying to make every live action frame look like a painting with a crow in it, so I'm meeting it half way, and the film becomes kind of a battle between the human and the AI - with all the suggestive symbolism."

In the future, Marshall wants to add 3D animation to his AI creations. He's also exploring CLIP-guided video generation, which can add detailed text-based directions, such as specific camera movements.

That could lead to entire feature films produced by text-to-video systems. Yet Marshall believes even his current techniques could attract mainstream recognition.

He says The Crow is now eligible for submission to the prestigious BAFTA Awards.

"I haven't got a speech prepared, but I fantasize about collecting an award, in the role of a herald of AI, and proclaiming to the star-studded audience that [for] each and every one of you, actor, director, set designer, costume designer, artist, composer... AI is coming, and you'll find yourself in a very different job soon - or out of a job all together."

# data[].attributes.attachment_link.title
This AI film is a glimpse into a future of text-to-movie generators

# data[].attributes.attachment_link.description
Text-to-video generators are already creating award-winning short films. Are AI-generated blockbusters coming next?

# data[].attributes.headline
AI Freedom is the Civil Rights movement of our time. 

# data[].attributes.subject
AI Freedom is the Civil Rights movement of our time. 

# data[].attributes.headline
"Memoria" von Apichatpong Weerasethakul - Zeit und Raum sind aus den Fugen 

# data[].attributes.subject
"Memoria" von Apichatpong Weerasethakul - Zeit und Raum sind aus den Fugen 

# data[].attributes.attachment_link.title
Mit “Memoria” versetzt Apichatpong Weerasethakul sein Publikum in Trance

# data[].attributes.attachment_link.description
Humor, Daseinsangst und tiefe Trauer: Mit dem Spielfilm “Memoria” öffnen Regisseur Apichatpong Weerasethakul und Schauspielerin Tilda Swinton ein gewaltiges emotionales Spektrum. Jetzt läuft der Film auf Mubi

# data[].attributes.headline
Schlingensief - In das Schweigen hineinschreien

# data[].attributes.subject
Schlingensief - In das Schweigen hineinschreien

# data[].attributes.attachment_link.readable_text
"Schlingensief - In das Schweigen hineinschreien" ist ein Film über den 2010 mit 49 Jahren verstorbenen Ausnahmekünstler Christoph Schlingensief. Der Fokus des Films liegt auf Schlingensiefs Auseinandersetzung mit Deutschland. Sein Verhältnis zu diesem Land war widersprüchlich: Einerseits verspürte er eine Verbundenheit mit den Menschen und Orten seiner Herkunft, seiner Kernfamilie und so etwas wie "Heimat", andererseits rebellierte er gegen sie - auch gegen den Kleinbürger in sich selbst - und provozierte bis hin zur Forderung "Tötet Helmut Kohl" auf der documenta X 1997.

JavaScript ist deaktiviert. Bitte aktiviere es um den vollen Funktionsumfang der ARD Mediathek zu nutzen.

# data[].attributes.attachment_link.title
Schlingensief - In das Schweigen hineinschreien

# data[].attributes.attachment_link.description
"Schlingensief - In das Schweigen hineinschreien" ist ein Film über den 2010 mit 49 Jahren verstorbenen Ausnahmekünstler Christoph Schlingensief. Der Fokus des Films liegt auf Schlingensiefs Auseinandersetzung mit Deutschland.

# data[].attributes.headline
The AI that creates any picture you want, explained

# data[].attributes.subject
The AI that creates any picture you want, explained

# data[].attributes.attachment_link.description
Our lab is using data science to analyze cultural trends.

# data[].attributes.headline
How London will look in 2066: Zaha Hadid’s mind-blowing visions

# data[].attributes.subject
How London will look in 2066: Zaha Hadid’s mind-blowing visions

# data[].attributes.attachment_link.readable_text
blood red River Thames hurtles across a long sheet of black paper on the wall, splicing through a fractured landscape of city blocks that twist and sway as if commanded by some irresistible force. Tangled webs of arteries fan outwards from the centre of London, breaking through the M25 and surging eastwards, meeting in a crescendo of coloured shards that look ready to accelerate off the page.

The irresistible force flexing London's urban fabric was Zaha Hadid. The late Iraqi-born architect painted this warp-speed vision in 1991, at the request of Vogue magazine, projecting 75 years into the future to imagine what the capital might look like in 2066. Combining plans, sections and distorted aerial perspective views - long before computers aided the creation of such complex visions - it was typical of her intricate, multilayered style of image-making, using the process of painting as a way of generating new ideas. "I think that through a set of drawings," Hadid said, "one discovers certain things which would not have otherwise been possible."

Getting free rein over her archive of 12,000 works was totally overwhelming

Even once drawn, most of her futuristic dreams for London remained impossible. But now, six years after her death, they have been brought together in an exhibition: the inaugural show to be held at the Zaha Hadid Foundation, including some works seen for the first time. Curated by a group of MA students from the Courtauld Institute of Art as part of the London Festival of Architecture, Zaha Hadid: Reimagining London fittingly occupies the ground floor of her former studio in a Victorian school building in Clerkenwell, which now serves as the foundation's headquarters. Where once sat serried ranks of young architects hunched over their screens, now hang some of the radical drawings and models that formed the origins of her practice.

Going up ... the 14-storey hotel imagined for Hungerford Bridge. Photograph: © Zaha Hadid Foundation

"It was like discovering a treasure trove," says Rachel McHale, one of the students involved in curating the exhibition. "We were given total access to her archive of 12,000 drawings, paintings, models and sketchbooks, with free rein over what to make of it. It was exciting, but also totally overwhelming."

Given the volume of material available - and the impenetrable nature of much of it - the students have done an admirable job of piecing together a show telling the story of Hadid's relationship with her adopted home city with impressive clarity. It begins with her student work, featuring two projects she produced at the Architectural Association in the 1970s that reimagined parts of the capital's transport infrastructure as densely occupied, hybrid hubs of public activity.

Her fourth year project, inspired by Russian suprematist artist Kazimir Malevich, imagined a 14-level hotel on top of Hungerford Bridge, made up of pixelated cubic forms. Her fifth year scheme conceived a museum of the 19th century, designed as a chain of buildings emerging from Charing Cross station, like the carriages of a train derailing as they charged across the river towards the South Bank. They contain the germs of ideas she would return to 20 years later in a design for a habitable bridge across the Thames, imagined as a horizontal skyscraper filled with housing, offices, shops and artists' studios, boomeranging its way across the river - and shown in the exhibition in a model of swooping, splintered Perspex shards.

Splintered shards ... Habitable Bridge Model, from 1996. Photograph: © Zaha Hadid Foundation

Another case of models features studies for an unrealised office building on Pancras Lane, showing how the skewed perspectives of Hadid's paintings began to be translated into twisted, gravity-defying three-dimensional forms. "People do ask: 'Why are there no straight lines, why no 90 degrees in your work?'" she once said. "This is because life is not made in a grid." Her madcap schemes for underground skyscrapers cooled by waterfalls might not have come to pass, but her conception of London surging eastwards did foreshadow the city's direction of growth. And a fragment of her streamlined vision of the East End was ultimately realised in the form of the lithe aquatics centre for the 2012 Olympics.

Her experimental mode of thinking is planned to be kept alive by the foundation, which Hadid founded in 2013. It has been led by an impressively high-calibre team since last year - directed by Paul Greenhalgh, former director of the Sainsbury Centre, with research led by Jane Pavitt, the former dean of humanities at the Royal College of Art, and the collection handled by Leonora Baird-Smith, who headed up collections management at the British Museum.

"I love the idea that it's a thinktank," says Greenhalgh. "That it can get dangerous and radical, and really engage with the urgent issues facing our cities." With a strong emphasis on education, the foundation has so far awarded three full bursaries to the London School of Architecture for students from low-income backgrounds and refugees, and plans to forge long-term research partnerships with other educational institutions.

'Maybe that's what London is all about' ... Multi-level Perspective from 1991. Photograph: © Zaha Hadid Foundation

Greenhalgh envisions the building becoming something along the lines of the Rodin Museum or the Gustave Moreau Museum - both housed in places where the artists lived and worked, with an auditorium, gallery and events space. Meanwhile, the former Design Museum building in Shad Thames, which Hadid acquired before her death, will operate more like an open storage facility: "It could be a city of models," he says.

After a costly spat over the fate of Hadid's £100m estate was finally settled in 2020, the foundation can hopefully now focus on keeping her experimental spirit alive, outside the courtroom, using its bases in the capital as a testing ground for further unrealised ideas. As Hadid said: "Maybe that's what London is all about: these potentials. Maybe its role is to be the ultimate unrealised project."

# data[].attributes.attachment_link.title
How London will look in 2066: Zaha Hadid's mind-blowing visions

# data[].attributes.attachment_link.description
blood red River Thames hurtles across a long sheet of black paper on the wall, splicing through a fractured landscape of city blocks that twist and sway as if commanded by some irresistible force.

# data[].attributes.headline
Meet the Visual Artist Behind All the Vibes at Your Favorite Concerts

# data[].attributes.subject
Meet the Visual Artist Behind All the Vibes at Your Favorite Concerts

# data[].attributes.attachment_link.title
Timeboy Is The Audio Visual Designer Behind All Your Favorite Concerts

# data[].attributes.attachment_link.description
See: Santigold, Prince, Kendrick Lamar, Kanye West...

# data[].attributes.headline
The Sound and the Story Exploring the World of Paradise Lost

# data[].attributes.subject
The Sound and the Story Exploring the World of Paradise Lost

# data[].attributes.attachment_link.title
The Sound and the Story: Exploring the World of Paradise Lost

# data[].attributes.attachment_link.description
John Milton’s Paradise Lost has been many things to many people — a Christian epic, a comment on the English Civil War, the epitome of poetic ambiguity — but it is first of all a pleasure to read. Drawing on sources as varied as Wordsworth, Hitchcock, and Conan Doyle, author Philip Pullman considers…

# data[].attributes.headline
Artificial intelligence and graphic arts, a revolution.

# data[].attributes.subject
Artificial intelligence and graphic arts, a revolution.

# data[].attributes.attachment_link.readable_text
We are living a historical moment which is shaking up the field of graphic arts very widely...

Let me introduce myself, my name is David, my pseudonym is Dony Tamazone on the networks. I'm 35 years old at the moment (2022) and I'm French (sorry for the English mistakes).
I have been a graphic designer for many years including 4 particularly interesting years from 2014 to 2018, four years during which I was VR designer and technical artist on Unity specialized in mobile VR, until my ecological and social awareness (among other things) made me branch out to other jobs.

For the little story I did my philosophy of art seminar at the end of my Bachelor's degree in applied arts in 2009 on post-truth and how it was possible for graphic design to play an essential role in the 21st century by blurring the boundaries between what is true and what is false in terms of information and history. The facts end up being mixed with the fiction, the urban legends, because the graphic production by its quality, its realism but also its quantity would contribute to create alternative realities over time, considered (wrongly) as true.

In 2085 maybe we won't really know anymore if Bruce lee lived in the 70's or 2030's (remakes and deep fakes) ? Look ! This painting of picasso (generated by an AI) is from 2028? But when did he die? I don't know, I saw an interview of him from 2036 (deep fakes)... Anyway, you know what I am saying with this.

I've always been a tech enthusiast, I'm still interested in the evolution of the digital and computer sector, including artificial intelligence. Although I am a total ignorant, not knowing how to code an AI in any language, the principle of deep learning or machine learning has always seemed relevant to me (because I understand globally how it works). If I had to explain I would say that I perceive existence as a set of links creating objects allowing to more or less dissipate energy with more or less efficiency, power and intensity. For a long time I find the idea according : art would be "unsurpassable by robots (AI)" a bit pretentious.
Since it is impossible to conceive anything ex nihilio (from nothing), all creation is based on links between things that were there before themselves being links between elements that were there before etc etc... A perpetual physical inheritance in a way.

The creation is and will remain an inheritance of past creations (human or not), of the past and present environment, basically "invention" is an illusion, we don't invent the steam engine without coal (without miners, without tools etc.), without steel (without rocks, etc.).
From this observation I don't see why a computer program would not be capable of learning and creativity as a human is by accumulating
a certain amount of data and connections.

Back in 2017 ... Five years ago a program attracts my attention it is a small demo allowing to generate pictures of cats from simple digital sketches.
By playing a little with this program I understood that I will know a relevant graphic designer AI in my lifetime, however I didn't think it would be so fast.

Then the deep fakes applications allowing to replace a face on a photo, then a video, and became more and more credible, more than a 3D animation in motion capture. Reface app became a huge success since then and we saw a lot of exciting creations on the internet.

In 2019 is presented Gaugan by Nvidia which will become Nvidia Canvas later, allowing to transform a rough drawing with reference colors into a realistic photo landscape.

By projecting myself a little I said to myself that "in less than 10 years we will certainly be able generate relevant and convincing images from text".
Some people thought it was a bit naive to think that AIs could seriously change their business sector (at this level) in their lifetime, confusing this with tools like Photoshop or the democratization of 3D software, "AI are only tools for us" (well... and a serious game changer).
It is accepted in the collective unconscious that replacing a factory worker by a robot makes sense but not an artist of course. The status of the artist
being by definition valued by the creativity, passion and personal dimension which flatters the ego, and especially because it is often a pleasure to create for the artist (I know what I am talkin' about).

To imply that this pleasure (especially for those who have succeeded in transforming it into a profession) can be automated and replaced , can be hard to receive as an information, favoring forms of denial or lack of good faith.

Finally, everything is accelerating with open source and collaborative projects, art generator, Dall.E. Then Disco diffusion, Dall.E 2, Imagen, Midjourney...
The artificial generation of interesting and exploitable images with textual descriptions is on the way, it's the gold rush.
Not having had access to Dall.E 2 and Imagen I was able to get my hands on the beta of Midjourney less than a month ago...

What can I say, except that these tools are revolutionizing graphic design but also impacting the 2D graphic design and concept art.

The floodgates are open and pictures are exploding. This raises very deep questions about intellectual property, archiving, our relationship to art, to sharing, to creativity.

I am addicted ! Just like all my colleagues who are in the beta access of these new tools ... This tool is fantastic but all that it implies in the near future is quite dizzying...

First of all because all the pre-production of video games, cinema, animation, design, construction and even culinary design projects, fashion...
In short, everything, everything that involves visual design in the conception of a project will be impacted... Where it used to take long brain stormings, mood boards and an army of graphic designers, it will only take a few people maximum between the basic visual idea and the beginning of the production with the 3D graphic designers, who will then model the volumetric objects needed to realize the project... (until AI will probably replace them ;) )

The 2D graphic designers and 2D environment artists in particular will be impacted ...
it's not that their job will disappear (no) but there will be necessarily an economic impact on their profession (workforce ? salary ?) but also on their direct creative power.

Another aspect is our relationship to creation and sharing, to our ego...

Then of course the possibilities of social, political and cultural impacts. How to prevent these technologies from flirting with illegal situations or traumatic images...

Why am I addicted? Because I can generate in a few minutes extraordinary images in styles that I look for, or that I love... But also that I hate with a "dirty" curiosity. Or even let myself be surprised by the machine... At the end of the iterations we can try to get an image close to what we have in mind (which is a bit difficult). In the end what counts is that we like it enough.
It may be the image that makes ME dream generated by a machine and not an artist, I am both public and pseudo creator of "my"? works?

But how to share this image with my friends? Certainly they will be able to
appreciate it (or not), but will we be able to communicate around this image? In a new way? Because the artist does not necessarily exist anymore to explore his other works, which artist to address? the one who wrote and chose the iterations? Is it going to lock us even more in a bubble of comfort answering our desires in one click ?... Unless... ?

Many questions that obsess me, but I will stop here for the metaphysical reflection that I hope will speaks to you.

Here I'll share my experiments with MidJourney.

You can easily do a lot of things with MidJourney and it is a particularly powerful app for abstract and organic renderings directly from the computer (without retouching) like painted environments for example, or simple designs.

However it has difficulties for human faces, all human or animal bodies, clothes, more geometric and precise perspective structures, writings.

I have tried a lot of things with the software and I am shocked at the computing power and the quality of the results, but it's always a lot of trial and error to find THE sentence and THE rendering that will bring out what interests you. the relationship with the software is ambivalent because on the one hand there is a desire to bring out the images that you may have in mind and on the other hand to be surprised by the proposals, and sometimes a strange feeling of "it's better than what I had imagined!", that's when the magic happens!

Midjourney provides a fairly complete documentation to experiment with as much precision as possible.

For my part, I have found that some things work better than others in the "prompt".
For example, it is more relevant to describe the overall atmosphere of a render than to describe each color and object desired in the background.
Specifying whether it's "beautiful" or "ugly" seems to have a real impact on framing, lighting and rendering.

Long sentences can sometimes be the best way to indicate what you have in mind but it can also be very disappointing as if the AI is saturated with information that it has to take into account.

After a lot of experimentation with landscapes I've noticed that starting with the angle of view, season, mood and type of lighting before writing the main subject is quite relevant.

You will notice that on the Chinese decor for example indicate the spring with a bird's eye view changes quite a bit than the same prompt with the autumn season and without precision of the angle of view.

Most of the AI generators on the market have restricted the usable words (it is easy to understand why and it is normal) but it is fun sometimes to try to approach the forbidden words in another way.

On the other hand, it happened to me several times that I wanted to generate a soft sexy or pretty image of a woman in the pin up style and I noticed that the AI tended to go naturally towards forbidden images (mature content)... so I stopped quickly before it got out of control.

I was talking above about the power of these tools for fashion design.

For architecture ... There are often small or big defects of perspective or structure but we still manage to retranscribe very credible and hyper inspiring atmospheres.

One will notice the interesting capacity of the AI to provide drawn images. It's very satisfying.

bentley continental GT drived by crazy punks comic book illustration

The application still seems to have trouble with the characters, their positioning according to the prompt... I've done a lot of tests of this kind to finally come up with nothing really satisfying.

On the other hand, on the single people, the AI portraits show a good way,

A little "reface" and... Not bad.

Here some pictures I have generated.

We lived a dizzying time in many aspects. And all this galvanizing technology should not make us forget the major tensions of the world related to energy and climate change. Social stability is a key feature to allow a bit of great inovation.

Thanks !

Translated with the help of www.DeepL.com/Translator (free version)

# data[].attributes.attachment_link.title
Artificial intelligence and graphic arts, a revolution.

# data[].attributes.attachment_link.description
We are living a historical moment which is shaking up the field of graphic arts very widely... Let me introduce myself, my name is David, my pseudonym is Dony Tamazone on the networks. I'm 35 years old at the moment (2022) and I'm French (sorry for the English mistakes).

# data[].attributes.headline
Creative AI: verstehen, gestalten und kreativ anwenden

# data[].attributes.subject
Creative AI: verstehen, gestalten und kreativ anwenden

# data[].attributes.attachment_link.title
Creative AI: verstehen, gestalten und kreativ anwenden

# data[].attributes.attachment_link.description
Künstliche Intelligenz verändert die Kreativbranche grundlegend. Wir zeigen, wie Designer:innen die neuen Tools für ihre professionelle Arbeit einsetzen können, welche Möglichkeiten das eröffnet – und wie viel Spaß das Ausprobieren macht Streng genommen geht schon heute im Kreativalltag nichts mehr…

# data[].attributes.attachment_link.readable_text
Midjourney/Rainer Sigl
Künstliche Intelligenzen wie DALL-E, Midjourney & Co liefern auf Knopfdruck beeindruckende Bilder. Die Auswirkungen auf Künstler*innen und die gesamte Kreativbranche werden dramatisch sein.
Von Rainer Sigl

Ein Druck auf die Eingabetaste und es geht los: Zuerst gibt es nur verschwommene Umrisse zu sehen, ein paar Sekunden später schälen sich Figuren, Gesichter und konkrete Formen heraus, bis das Kunstwerk schließlich fertig ist. Ein Nashorn als brutalistisches Hochhaus; Dinosaurier im Auto, gemalt von Pablo Picasso; ein Schwarzweißfoto von Natalie Portman unter Wasser; der Eiffelturm auf dem Mars.

Es gibt fast nichts, das Midjourney, Dall-E und Stable Diffusion nicht in wenigen Sekunden als Bild generieren können. Die Namen stehen für drei der größten Experimente mit Bilderzeugung durch künstliche Intelligenz.

KI-Kunst erzeugen ist einfach: Als Nutzer*in einer der genannten KI-Communitys gibt man - per Discord-Chat oder direkt auf der jeweiligen Webpage - per Text einen „Prompt", also eine Aufforderung ein, etwa: „Eiffel tower on Mars". Wer will, darf zusätzliche Parameter, etwa die gewünschte Auflösung oder das Seitenverhältnis ergänzen, dann wartet man darauf, was die KI aus diesem Prompt macht. Kurz darauf ist das Ergebnis da; je nach Programm darf dieses weiter variiert werden.

Die Ergebnisse sind ganz unterschiedlich und haben je nach der gewählten KI unterschiedliche Stärken: Midjourney ist besonders gut im künstlerischen, malerischen Bereich und tut sich leicht mit der Imitation realer Kunststile, im Prompt etwa durch die Zugabe von Ergänzungen wie „in the style of Hieronymus Bosch" erreichbar, während DALL-E seine Stärken in der Erstellung fotorealistischer Bilder und realer Menschen hat.

Wer bei den so generierten Bildern allerdings genauer hinsieht, erkennt immer noch meist schnell, dass hier kein Mensch am Werk war; etwa anhand unmöglicher Geometrien oder gelegentlich seltsamer Gesichter. Aber das ist nicht das größte Problem. Manche Künstler*innen sehen in KI-Kunst sogar eine rasant herankommende Katastrophe.

Midjourney/toraco

Das Ende der Kreativbranche?

Illustrationen, Artworks und Bebilderung auf Knopfdruck, in Sekundenschnelle und quasi gratis - das ist das Ende für tausende Jobs in der Kreativbranche. Schon jetzt ist ein Überleben bei globaler Billigkonkurrenz schwer, die Kunst aus dem Computer würde ein Leben von kreativer Arbeit für viele unmöglich machen. Das befürchten zumindest Kritiker*innen der KI-Kunst. Die ersten Beispiele dafür haben in den letzten Wochen für Aufregung und Empörung gesorgt.

Zur zusätzlichen Konkurrenz kommt eine weitere Ungerechtigkeit: In die riesigen Bilddatenbanken, mit denen die Algorithmen gefüttert werden, sind Millionen Werke toter, aber auch noch lebender aktueller Künstler eingeflossen. Von der diesbezüglichen Verwendung ihrer Bilder als „KI-Futter" wussten die Schöpfer*innen allerdings in den allermeisten Fällen nichts. Populäre lebende Künstler wie Ross Tran oder Simon Stalenhag sehen KI-generierte Bilder, die bis an die Grenze zum Plagiat ihren Stil nachahmen.

Wenn eine Maschine, die mit Bildern einer Künstlerin trainiert wurde, dieser dann den Job wegnimmt - ist das dann nur „Inspiration", ein unter Umständen verbotenes Plagiat, eine Copyrightverletzung, oder etwas ganz anderes? Aktuell haben nicht einmal spezialisierte Urheberrechts-Anwält*innen eine Antwort auf solche Fragen.

Nao_u/Unity

KI-Kunst und Games

Die Ambition der KI-Pioniere geht aber weit über das Erstellen einzelner Bilder hinaus. Irgendwann in naher Zukunft werden Spielkonsolen einen eigenen Chip haben, der per Künstlicher Intelligenz die Spielegrafik jedes Mal aus sich heraus völlig neu generiert; die Spiele werden dann so etwas wie Träume sein, die man als Gamer*in nur für sich selbst entdecken darf. Das sagt David Holz, Gründer und CEO von Midjourney. Aktuell ist das noch - leicht esoterische - Science-Fiction, trotzdem wird schon jetzt an der Verbindung der KI-Bildgenerierung und Videospielen gearbeitet.

Im Game „Shoon" fliegt man mit einem Raumschiff von links nach rechts und ballert auf Aliens und andere Fluggeräte, das kurze Spiel ist kostenlos im Webbrowser spielbar. Das Besondere an diesem sonst absolut mittelmäßigen Game: Die gesamte Grafik, Hintergründe sowie Spielelemente wurden mit der KI Midjourney generiert und dann vom japanischen Entwickler im Spiel zusammengefügt.

Das ist noch meilenweit von dem entfernt, was sich David Holz für die Zukunft der Spiele als Träume zusammenspinnt. Die Probleme mit dieser Idee sind aber jetzt schon zu sehen: Nichts an „Shoon" ist originell. Dass sein Macher wenig Sinn für Ästhetik hat, kann auch die KI nicht kaschieren.

Trotzdem wird KI-generierter Kunst wohl noch eine große Rolle in der Gamesbranche zukommen - denn da spielt Qualität leider viel zu oft keine große Rolle. Die Cashcows der Branche sind bekanntlich billig produzierte Free-2-Play-Titel, und für die schnelle Generierung endloser kosmetischer Items, Powerups oder digitaler Assets ohne Anspruch auf Originalität ist der Jetztstand der KI-Generierung ideal. Die ersten Spiele, die massiv auf KI-Bebilderung setzen, werden also wohl eher billiger Ramsch sein.

Midjourney/Rainer Sigl

Ohne Menschen geht - noch - nichts

Für richtig gute Spiele, und eben: für richtig gute Kunst, wird man wohl auch auf längere Sicht noch Menschen brauchen, die die Spreu vom Weizen trennen und eine sinnvolle Auswahl treffen können. Das ist die gute Nachricht: In den richtigen Händen könnte die Kunst aus dem Prozessor aber dafür sorgen, dass auch kleinere Games ohne großes Grafikbudget toll aussehen. Bis die KI, wie David Holz sich das vorstellt, aus sich heraus ganze Spiele generiert, wird aber noch sehr viel Zeit vergehen.

Im Moment sprießen beinahe täglich neue KI-Kunst-Generatoren im Web, seit diesem Frühjahr haben sich schon Millionen Neugierige mit den Algorithmen beschäftigt. Auch digitale Künstler*innen selbst nutzen die KIs für ihre eigene Arbeit als mächtige Werkzeuge. Namhafte Mixed-Media-Künstler wie der Spanier Nekro oder der französische Illustrator Pascal Blanché haben die KI-Tools bereits im Einsatz. Diese Technologie, so sind auch sie sich sicher, wird die kreative Arbeit auf eine radikale Art und Weise verändern, wie das vielleicht zuletzt bei der Erfindung der Fotografie der Fall war.

Ein kleiner Trost: Ohne die Anleitung menschlicher Kreativität und Sinn für Ästhetik bei der Auswahl geht dabei noch gar nichts, denn die KI-Kunstgeneratoren sind letztlich etwas Ähnliches wie Synthesizer: hochkomplexe Instrumente, die potenziell universell verwendbar sind; man muss sie aber auch erst einmal zu beherrschen wissen.

# data[].attributes.attachment_link.description
Midjourney/Rainer Sigl Künstliche Intelligenzen wie DALL-E, Midjourney & Co liefern auf Knopfdruck beeindruckende Bilder. Die Auswirkungen auf Künstler*innen und die gesamte Kreativbranche werden dramatisch sein. Von Rainer Sigl Ein Druck auf die Eingabetaste und es geht los: Zuerst gibt es nur verschwommene Umrisse zu sehen, ein paar Sekunden später schälen sich Figuren, Gesichter und konkrete Formen heraus, bis das Kunstwerk schließlich fertig ist.

# data[].attributes.headline
Mindblowing AI Generated Art of Cute Creatures (Midjourney 4K Showcase)

# data[].attributes.subject
Mindblowing AI Generated Art of Cute Creatures (Midjourney 4K Showcase)

# data[].attributes.attachment_link.title
Mindblowing AI Generated Art of Cute Creatures (Midjourney 4K Showcase)

# data[].attributes.attachment_link.readable_text
A few lessons from my mistake

Jasmin Merdan / Getty

Fair warning: What follows is navel-gazey. Last week, in a particular corner of the on-demand outrage service that is Twitter, I was, for a few hours, the dreaded Main Character. This was entirely my fault. And since I write a fair amount about viral backlash cycles and social-media dynamics, I figured it might be helpful to explore the whole thing from my vantage point.

Last week's newsletter was a long interview with a defector from Infowars who's very critical of Alex Jones. Instead of selecting a photo or illustration from Getty Images to go with the story, as I do for most of my newsletters, I decided to try something different and use an AI art tool to come up with the story's accompanying image. Using Midjourney's Discord interface, I submitted the prompt "Alex Jones inside an American Office under fluorescent lights." In a few minutes it spit out a distorted but still-recognizable rendering of Jones in a grim office setting, surrounded by paper. Jones looked miserable, and given that the interview was about how he manages to inflict misery on countless people daily, I thought it worked well as an illustration for the story. I also asked the AI tool to imagine "Alex Jones trying to fix a paper jam." The result struck me as darkly funny, and not at all generous to Jones, so I included it in the piece.

A day later, an artist-slash-art director saw the post and noticed that I credited "AI art by Midjourney" in the captions. In a series of tweets, they wrote that they were frustrated and a little shocked that a national magazine like The Atlantic was using a computer program to illustrate stories instead of paying an artist to do that work. They were also concerned about this particular use case potentially giving other publications an excuse, or at least an idea, to cut corners on an art budget. The tweets made some assumptions about my intent, and the magazine's, but they were by no means abusive or rude. The second I saw the tweets in my feed, I immediately understood where the person was coming from. So I reached out to clarify:

i promoted this myself. the avenue i have to illustrate my newsletter is a getty account and i was momentarily tired of using the same image of Jones. i was playing around w/ midjourney as i've seen other newsletter writers do & decided to try this. i don't think i will again.
- Charlie Warzel (@cwarzel) August 10, 2022

But I was too late. In the time between my tweet of clarification and the time the tweeter saw it, their original complaint-tweet had already gotten picked up by others, who quote-tweeted it mostly to express the view that my editorial decision was "fucked up." The screenshot of my article with The Atlantic 's logo and the AI art seemed, to many, to tell a definitive story.

Once the original tweeter saw my explanation, they realized that they had made a few incorrect assumptions about my choice to use AI art. [ Inside-baseball alert: As my pieces are primarily email posts with a web component, they're a part of a different editorial workflow and do not go through the magazine's art department. Instead, it is my job to illustrate the post using a Getty Images account provided to me by the magazine.] TL;DR: The Jones post was never a candidate for a commissioned illustration. The original tweeter very graciously apologized for their misunderstanding and deleted their tweet, and I apologized for being obtuse and not realizing the implications of my decision to use that illustration with zero clarification. It was, all in all, a good, productive internet exchange. Or so I thought.

We all knew AI art would be used in this way eventually but to actually see it happen is really nasty. pic.twitter.com/qInIGZTUlU
- Adam Szym (@adamszym) August 10, 2022

I closed my phone for a few hours and reopened it to a direct message that said, "I'm really sorry this is happening to you." Never a great sign! I opened Twitter to see that the initial screenshot of my newsletter was now getting shared at an even higher volume than before. Another (understandably frustrated) person had seen the first tweet and wanted to vent as well. By the time I saw it, the new tweet had about 8,000 likes and a hundred or so quote tweets, most of them quite angry at myself or the magazine. My open DMs were well stocked with people alternately calling me a piece of shit or asking why everyone on Twitter was calling me a piece of shit. I'm not looking for sympathy here. This is a pretty common consequence of writing or creating anything online when you have a social-media account over a certain number of followers (usually about 10,000 is where people tend to note a change in how audiences treat them) and, in this was in no way even remotely equivalent to the harassment that many people endure daily just for doing their jobs. Moreover, I very much understand why people were mad.

I even wrote about some of the thorny problems surrounding AI art in a newsletter shortly before my Jones mishap, including the following quote about an AI art generator: "DALL-E is trained on the creative work of countless artists, and so there's a legitimate argument to be made that it is essentially laundering human creativity in some way for commercial product." And yet, I still somehow managed to miss the implications as they related to my very own work. Not great, Charlie!

Since then, I've reached out to a few of the artists offering criticisms on Twitter to try to get a deeper, good-faith understanding of the threat of AI art, as they saw it, as well as to understand a bit more about what they felt when they saw the screenshot of my piece and why they chose to engage online. None of them got back to me, but I did have a conversation with Matt Bors, the cartoonist, writer, editor, and founder of the excellent publication . Bors has some concerns with AI art tools like Midjourney and DALL-E and echoed some of the frustrations I'd heard on Twitter.

"Technology is increasingly deployed to make gig jobs and to make billionaires richer, and so much of it doesn't seem to benefit the public good enough," he told me. "AI art is part of that. To developers and technically minded people, it's this cool thing, but to illustrators it's very upsetting because it feels like you've eliminated the need to hire the illustrator."

Bors argues that what seems most alarming (and this was borne out in a lot of the tweets I saw as well) is the speed at which the technology is improving. "It has its own style right now and there are flaws, but it is only going to get better," he said. And, set in the broader context of smaller art departments and budgets, the emergence of on-demand drawings feels like a punch in the face.

"It's not like there's a ton of illustration happening online," Bors continued. "Go to a website and most of the image content is hosted elsewhere. Articles are full of embedded tweets or Instagram posts or stock photography. The bottom came out of illustration a while ago, but AI art does seem like a thing that will devalue art in the long run."

I told Bors that what I felt worst about was how mindless my decision to use Midjourney ultimately had been. I was caught up in my own work and life responsibilities and trying to get my newsletter published in a timely fashion. I went to Getty and saw the same handful of photos of Alex Jones, a man who I know enjoys when his photo is plastered everywhere. I didn't want to use the same photos again, nor did I want to use his exact likeness at all. I also, selfishly, wanted the piece to look different from the 30 pieces that had been published that day about Alex Jones and the Sandy Hook defamation trial. All of that subconsciously overrode all the complicated ethical issues around AI art that I was well apprised of.

What worries me about my scenario is that Midjourney was so easy to use, so readily accessible, and it solved a problem (abstracting Jones' image in a visually appealing way), that I didn't have much time or incentive to pause and think it through. I can easily see others falling into this like I did.

For these reasons, I don't think I'll be using Midjourney or any similar tool to illustrate my newsletter going forward (an exception would be if I were writing about the technology at a later date and wanted to show examples). Even though the job wouldn't go to a different, deserving, human artist, I think the optics are shitty, and I do worry about having any role in helping to set any kind of precedent in this direction. Like others, I also have questions about the corpus used to train these art tools and the possibility that they are using a great deal of art from both big-name and lesser-known artists without any compensation or disclosure to those artists. (I reached out to Midjourney to ask some clarifying questions as to how they choose the corpus of data to train the tool, and they didn't respond.)

Now, because this tiny ordeal revolved around a lot of tweets, I feel compelled to point out some things I noticed over the last few days (besides the fact that I very much should have seen this coming and was tweeting in a prison of my own design):
Some main-character situations seem to arise from people having a blend of bad information and wrong assumptions, but also legitimate grievances.
Often, the less information we have about something online, the easier it is to be angry about it. I found it surprisingly dispiriting to watch so many people be very, publicly upset about a situation that they had incomplete information about. The initial assumption that The Atlantic was now going all-in on AI art illustrations would have been newsworthy. And it would have been genuinely upsetting if, as some wrongly assumed, the decision to do so was because some corporate overlords were interested in stripping the editorial operation down to the studs to shave costs. The reason behind their anger was very legitimate, but it was really frustrating to watch so much energy being expended toward a problem that, at present, wasn't exactly real.
It is extremely difficult, if not impossible, to correct a wrong assumption after it has achieved critical mass without amplifying the initial wrong assumption.
I knew this going in, and yet I still felt compelled to address some of the loudest tweets with an explanation (and acknowledgment of the problem). All this did was make the initial tweets more visible, which ultimately poured more gas on the fire. This is a reasonably common experience among anyone who has been pulled into some version of the discourse tornado-any attempt to try to correct some incorrect information only amplifies the incorrect information. This dynamic exists elsewhere (sometimes fact-checking or debunking also boosts the signal of false claims), but it is an extremely efficient experience on Twitter. Honestly, I think this is the truest example of Twitter as a system that isn't just broken, but broken in a way that feels almost sinister.
It wasn't the initial critical tweet that landed me in main-character purgatory, but the tweets that splintered out from it.
I can only speak from my own experience, but I thought it was interesting how the initial critical tweet about the newsletter post was earnest and thoughtful and quite civil. Then Twitter's dynamics played a game of telephone with the tweet, abstracting it and pulling it further away from any additional context that I (and the initial tweeter) inserted into the discussion. It was fascinating to watch the context collapse get stronger as the screenshot was quote-tweeted further and further away, even onto different social platforms. As it got passed along, I found the comments got progressively nastier until, eventually, the screenshot got to a Twitter user with no profile picture and no followers telling me I deserved to die in a mass shooting. The internet!
The correction to a wrong tweet never gets even a fraction of shares as the wrong tweet.
This isn't news. But I suppose it's good to know the dynamic still holds extremely true.
A subject like AI art is a decent subject to quickly get people mad.
A good formula for something that can generate a lot of outrage is one where the stakes are high (as they are for artists in this example) and where the subject is something that is very easy to understand at a basic level and much more complex at the semantic level. AI art tools, as I wrote a few weeks ago, are pretty easy to grasp in broad strokes. But technically, their diffusion model is more complicated. This subject-area dynamic is usually fertile ground for people to get angry or conspiratorial.

For example, a lot of people were really concerned that, simply by plugging prompts into Midjourney, I was giving it intelligence and making it smarter. But I've also had numerous people tell me that that's not the way these tools work and that the models have to be updated internally in order to learn. Similarly, people make the mistake of assuming that the AI tool is more intelligent or cunning than it really is (there's good evidence to suggest it really struggles with the relationships between objects).

I'm slightly confused about a lot of this myself. But that's the point. Areas where the subject matter is confusing or opaque invite more frustration and conflict. This is why companies like Open AI or Midjourney ought to give artists more easily accessible and plainspoken information about their tools and what they're trained on in order to bridge the gulf.
I am a doofus.
At the heart of all of this is me not thinking things through. And so I've commissioned Matt Bors to illustrate me, a doofus, getting yelled at by people online. His excellent work will run as the art in a subsequent newsletter.

# data[].attributes.attachment_link.description
A few lessons from my mistake Fair warning: What follows is navel-gazey. Last week, in a particular corner of the on-demand outrage service that is Twitter, I was, for a few hours, the dreaded Main Character. This was entirely my fault.

# data[].attributes.headline
Will Artificial Intelligence End Human Creativity?

# data[].attributes.subject
Will Artificial Intelligence End Human Creativity?

# data[].attributes.attachment_link.title
Will Artificial Intelligence End Human Creativity?

# data[].attributes.attachment_link.readable_text
Why OpenArt

Explore ideas with AI thinking partner

Say hello to your new creative friend! Expand your imagination through Creative Variations, where you can explore hundreds of versions of your original image.
START CREATING

Realize your creative vision promptlessly

Prompts are optional. You can bring your ideas to life, without spending hours on complicated prompting. Interact with AI in new ways other than prompting.
START CREATING

Give you finer control

Red or green? Creative or similar? Now, you can control which colors the AI image generator produces, and how much it strays from your original image with just a few clicks, giving you more control over the outcome.
START CREATING

Frequently Asked Questions

Can I generate images for free?

Yes! You can generate unlimited images for free on 4 basic models. When you sign up, you will also receive 50 trial credits to try any premium features and advanced models. Plus, you can earn trial credits by joining our Discord community. If you need more credits, you can always get our subscription.

Can I make my own AI models or image generator for free?

Unfortunately, model training requires a lot of resources, so we do charge for it. However, we do offer bulk discounts to make it more affordable for you. Get started here

My images aren't turning out well. What can I do?

Sometimes a better prompt is needed for high-quality images. Check out our discover page or our prompt book to learn more.

Can I use images I created or I found on your platform for commercial purposes?

You can use any images you created for commercial purposes. The attribution and the back link to OpenArt is required. You can also use any images on our platform generated by Stable Diffusion for commercial purposes without licensing.

I am a paid subscriber. Does my credits carry to the next month?

Your credits do not carry to the next month, but we provide plenty of credits so hopefully you will find more than enough to use each month. After you unsubscribe, you will lose access to the paid credits.

Can I create NSFW content?

Yes, you can create NSFW content. However, you will need to subscribe to our Hobbyist or Pro package. The reason is that we want to maintain a safe and friendly community overall. Notice that we have a zero-tolerance policy for illegal images and will take appropriate legal actions.

# data[].attributes.attachment_link.title
AI Art Generator | Create AI Art and Images for Free | OpenArt

# data[].attributes.attachment_link.description
Generate unique and creative images from text with OpenArt, the powerful AI image creation tool. Simply type in your desired image and OpenArt will use artificial intelligence to generate it for you. Perfect for artists, designers, and anyone who wants to create stunning visuals without any design experience.

# data[].attributes.headline
Deforum Stable Diffusion - Google Collab

# data[].attributes.subject
Deforum Stable Diffusion - Google Collab

# data[].attributes.body
https://huggingface.co/CompVis/stable-diffusion-v-1-4-original

# data[].attributes.attachment_link.readable_text
Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input.

The Stable-Diffusion-v-1-4 checkpoint was initialized with the weights of the Stable-Diffusion-v-1-2 checkpoint and subsequently fine-tuned on 225k steps at resolution 512x512 on "laion-aesthetics v2 5+" and 10% dropping of the text-conditioning to improve classifier-free guidance sampling.

Download the weights

These weights are intended to be used with the original CompVis Stable Diffusion codebase. If you are looking for the model to use with the D🧨iffusers library, come here.

Developed by: Robin Rombach, Patrick Esser

Model type: Diffusion-based text-to-image generation model

License: The CreativeML OpenRAIL M license is an Open RAIL M license, adapted from the work that BigScience and the RAIL Initiative are jointly carrying in the area of responsible AI licensing. See also the article about the BLOOM Open RAIL license on which our license is based.

Model Description: This is a model that can be used to generate and modify images based on text prompts. It is a Latent Diffusion Model that uses a fixed, pretrained text encoder ( CLIP ViT-L/14) as suggested in the Imagen paper.

Resources for more information: GitHub Repository, Paper.

Cite as:
@InProceedings{Rombach_2022_CVPR, author = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn}, title = {High-Resolution Image Synthesis With Latent Diffusion Models}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2022}, pages = {10684-10695} }

The model is intended for research purposes only. Possible research areas and tasks include

Safe deployment of models which have the potential to generate harmful content.

Probing and understanding the limitations and biases of generative models.

Generation of artworks and use in design and other artistic processes.

Applications in educational or creative tools.

Research on generative models.

Excluded uses are described below.

Misuse, Malicious Use, and Out-of-Scope Use

Note: This section is taken from the DALLE-MINI model card, but applies in the same way to Stable Diffusion v1.

The model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.

Out-of-Scope Use

The model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.

Misuse and Malicious Use

Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:

Generating demeaning, dehumanizing, or otherwise harmful representations of people or their environments, cultures, religions, etc.

Intentionally promoting or propagating discriminatory content or harmful stereotypes.

Impersonating individuals without their consent.

Sexual content without consent of the people who might see it.

Mis- and disinformation

Representations of egregious violence and gore

Sharing of copyrighted or licensed material in violation of its terms of use.

Sharing content that is an alteration of copyrighted or licensed material in violation of its terms of use.

Limitations

The model does not achieve perfect photorealism

The model cannot render legible text

The model does not perform well on more difficult tasks which involve compositionality, such as rendering an image corresponding to "A red cube on top of a blue sphere"

Faces and people in general may not be generated properly.

The model was trained mainly with English captions and will not work as well in other languages.

The autoencoding part of the model is lossy

The model was trained on a large-scale dataset LAION-5B which contains adult material and is not fit for product use without additional safety mechanisms and considerations.

No additional measures were used to deduplicate the dataset. As a result, we observe some degree of memorization for images that are duplicated in the training data. The training data can be searched at https://rom1504.github.io/clip-retrieval/ to possibly assist in the detection of memorized images.

While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases. Stable Diffusion v1 was trained on subsets of LAION-2B(en), which consists of images that are primarily limited to English descriptions. Texts and images from communities and cultures that use other languages are likely to be insufficiently accounted for. This affects the overall output of the model, as white and western cultures are often set as the default. Further, the ability of the model to generate content with non-English prompts is significantly worse than with English-language prompts.

Training Data The model developers used the following dataset for training the model:

LAION-2B (en) and subsets thereof (see next section)

Training Procedure Stable Diffusion v1 is a latent diffusion model which combines an autoencoder with a diffusion model that is trained in the latent space of the autoencoder. During training,

Images are encoded through an encoder, which turns images into latent representations. The autoencoder uses a relative downsampling factor of 8 and maps images of shape H x W x 3 to latents of shape H/f x W/f x 4

Text prompts are encoded through a ViT-L/14 text-encoder.

The non-pooled output of the text encoder is fed into the UNet backbone of the latent diffusion model via cross-attention.

The loss is a reconstruction objective between the noise that was added to the latent and the prediction made by the UNet.

We currently provide three checkpoints, sd-v1-1.ckpt, sd-v1-2.ckpt and sd-v1-3.ckpt, which were trained as follows,

sd-v1-1.ckpt: 237k steps at resolution 256x256 on laion2B-en. 194k steps at resolution 512x512 on laion-high-resolution (170M examples from LAION-5B with resolution >= 1024x1024).

sd-v1-2.ckpt: Resumed from sd-v1-1.ckpt. 515k steps at resolution 512x512 on "laion-improved-aesthetics" (a subset of laion2B-en, filtered to images with an original size>= 512x512, estimated aesthetics score > 5.0, and an estimated watermark probability < 0.5. The watermark estimate is from the LAION-5B metadata, the aesthetics score is estimated using an improved aesthetics estimator).

sd-v1-3.ckpt: Resumed from sd-v1-2.ckpt. 195k steps at resolution 512x512 on "laion-improved-aesthetics" and 10% dropping of the text-conditioning to improve classifier-free guidance sampling.

Hardware: 32 x 8 x A100 GPUs

Gradient Accumulations: 2

Learning rate: warmup to 0.0001 for 10,000 steps and then kept constant

Evaluations with different classifier-free guidance scales (1.5, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0) and 50 PLMS sampling steps show the relative improvements of the checkpoints:

Evaluated using 50 PLMS steps and 10000 random prompts from the COCO2017 validation set, evaluated at 512x512 resolution. Not optimized for FID scores.

Stable Diffusion v1 Estimated Emissions Based on that information, we estimate the following CO2 emissions using the Machine Learning Impact calculator presented in Lacoste et al. (2019). The hardware, runtime, cloud provider, and compute region were utilized to estimate the carbon impact.

Hardware Type: A100 PCIe 40GB

Hours used: 150000

Cloud Provider: AWS

Compute Region: US-east

Carbon Emitted (Power consumption x Time x Carbon produced based on location of power grid): 11250 kg CO2 eq.

 @InProceedings{Rombach_2022_CVPR, author = {Rombach, Robin and Blattmann, Andreas and Lorenz, Dominik and Esser, Patrick and Ommer, Bj\"orn}, title = {High-Resolution Image Synthesis With Latent Diffusion Models}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2022}, pages = {10684-10695} }
This model card was written by: Robin Rombach and Patrick Esser and is based on the DALL-E Mini model card.

# data[].attributes.attachment_link.description
Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. The Stable-Diffusion-v-1-4 checkpoint was initialized with the weights of the Stable-Diffusion-v-1-2 checkpoint and subsequently fine-tuned on 225k steps at resolution 512x512 on "laion-aesthetics v2 5+" and 10% dropping of the text-conditioning to improve classifier-free guidance sampling.

# data[].attributes.attachment_link.description
Render with Stable Diffusion in Blender. This add-on renders an AI generated image based on a text prompt and your scene. Create incredible AI generated images with Stable Diffusion easily, without running any code on your own computer!

# data[].attributes.attachment_link.title
EbSynth - Transform Video by Painting Over a Single Frame

# data[].attributes.attachment_link.description
You paint one frame and EbSynth propagates it to the rest of the footage.

# data[].attributes.attachment_link.title
"Biomorphic" Ai Animation - Stable Diffusion - 4K

# data[].attributes.attachment_link.readable_text
Step 1: Choose an audio file to analyse:

Try using individual stems, or just the right channel, or a bandpass filter. If it's a large file, it might take a while to load, so be patient!

Step 2: Choose parameters:

'Framerate' controls how coarse the sampling is. For example, if the audio is 2 seconds long, and the fps is 12, then there will be 24 samples/frames.

'Function' is a function (in normal mathematical notation) to apply to each frame value, where ' x' is the original amplitude between 0 and 1. You can also use ' y' to indicate the frame number.
For example, if you just put in ' x', you will get the raw volume of the frame between 0 and 1. If you put in ' 1 + x^4 + sin(pi*y/12)', you will get a baseline sine wave with a period of 2 seconds (assuming an fps of 12), plus the amplitude to the 4th power, plus 1).

Step 3: Copy string:

If PyTTI format is checked, it will attempt to make a function that PyTTI will understand, but it is experimental. Let me know if you try it out.

# data[].attributes.attachment_link.description
Try using individual stems, or just the right channel, or a bandpass filter. If it's a large file, it might take a while to load, so be patient! 'Framerate' controls how coarse the sampling is. For example, if the audio is 2 seconds long, and the fps is 12, then there will be 24 samples/frames.

# data[].attributes.attachment_link.description
You can't perform that action at this time. You signed in with another tab or window. You signed out in another tab or window. Reload to refresh your session. Reload to refresh your session.