Have you ever wondered what a Picasso painting of Donald Trump might have looked like? How about an Edward Hopper portrait of the current President Joe Biden?
It could not be simpler to use either. Just head to the website here and type in a phrase describing what you want to see. Hit "enter" and after a few seconds you'll be presented with a grid of nine different pictures matching your request.
Donald Trump painted in the style of Picasso and a series of Edward Hopper portraits focusing on President Joe Biden - Dall-E Mini generates images like these at the stroke of a few keys. Dall-E Mini/
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Some of the attempts may come off better than others, while certain phrases and types of requests appear to deliver better results.
For example, asking for a particular person to be painted in the style of a noted artist, more often than not, delivers the desired results.
While AI tools of this kind have existed previously, this is the first to be put into the public sphere and it has proven a hit on social media.
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Capable of being run on either a computer or phone (though the former tends to work better), the app has seen people across Twitter getting seriously creative.
Everyone posting what theyve done with dall e mini today so here's what i was doing last night pic.twitter.com/m8ej21I4nj— Vinny Jazz (@PrisonerOfSleep) June 6, 2022
I'm so happy they put aside their differences and finally bonded over their shared homosexual experiences. #Pride2022 #SonicTheHedgehog #mario #dallemini pic.twitter.com/ojY7bBstEG— Muted2 (@MutedNotSuited) June 6, 2022
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It's the brainchild of Normandy programmer Boris Dayma, who developed the app from his current base in Houston, Texas, as part of an AI computing competition run by Hugging Face and Google in July 2021.
"The hardest part is definitely people, " he explained. "If you draw a landscape with Dall-E, it's amazing, because if there's a small problem with a tree, nobody notices it and the landscape still looks great.
"But if there's a problem with a face, we notice it. If there's a small flaw with an eye, we can see it. With an avocado, even if it has flaws, it's good enough."
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Despite such minor flaws, the system is providing endless hours of entertainment on social media and represents a significant first step into an exciting new realm in online creativity.
"We have been litigating based on this false premise that Rupert Murdoch wasn't an officer of Fox News, " attorney Justin Nelson told a judge.
Social Security's trust funds are expected to be depleted by 2033. Will a drastic reform of the U.S. pension system spark protests the size of the French ones?Josh, I’ve been hearing a lot about ‘AI-generated art’ and seeing a whole lot of truly insane-looking memes. What’s going on, are the machines picking up paintbrushes now?
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Not paintbrushes, no. What you’re seeing are neural networks (algorithms that supposedly mimic how our neurons signal each other) trained to generate images from text. It’s basically a lot of maths.
Neural networks? Generating images from text? So, like, you plug ‘Kermit the Frog in Blade Runner’ into a computer and it spits out pictures of … that?
You aren’t thinking outside the box enough! Sure, you can create all the Kermit images you want. But the reason you’re hearing about AI art is because of the ability to create images from ideas no one has ever expressed before. If you do a Google search for “a kangaroo made of cheese” you won’t really find anything. But here’s nine of them generated by a model.
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You mentioned that it’s all a load of maths before, but – putting it as simply as you can – how does it actually work?
I’m no expert, but essentially what they’ve done is get a computer to “look” at millions or billions of pictures of cats and bridges and so on. These are usually scraped from the internet, along with the captions associated with them.
The algorithms identify patterns in the images and captions and eventually can start predicting what captions and images go together. Once a model can predict what an image “should” look like based on a caption, the next step is reversing it – creating entirely novel images from new “captions”.
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When these programs are making new images, is it finding commonalities – like, all my images tagged ‘kangaroos’ are usually big blocks of shapes like
It’s a bit more than that. If you look at this blog post from 2018 you can see how much trouble older models had. When given the caption “a herd of giraffes on a ship”, it created a bunch of giraffe-coloured blobs standing in water. So the fact we are getting recognisable kangaroos and several kinds of cheese shows how there has been a big leap in the algorithms’ “understanding”.
There’s been a number of developments in techniques, as well as the datasets that they train on. In 2020 a company named OpenAi released GPT-3 – an algorithm that is able to generate text eerily close to what a human could write. One of the most hyped text-to-image generating algorithms, DALLE, is based on GPT-3; more recently, Google released Imagen, using their own text models.
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Actually, this is another big development. When you use one of these models you’re probably only seeing a handful of the images that were actually generated. Similar to how these models were initially trained to predict the best captions for images, they only show you the images that best fit the text you gave them. They are marking themselves.
I can’t stress enough that this isn’t intelligence. The algorithms don’t “understand” what the words mean or the images in the same way you or I do. It’s kind of like a best guess based on what it’s “seen” before. So there’s quite a few limitations both in what it can do, and what it does that it probably shouldn’t do (such as potentially graphic imagery).
For now, these algorithms are largely restricted or pricey to use. I’m still on the waiting list to try DALLE. But computing power is also getting cheaper, there are many huge image datasets, and even regular people are creating their own models. Like the one we used to create the kangaroo images. There’s also a version online called Dall-E 2 mini, which is the one that people are using, exploring and sharing online to create everything from Boris Johnson eating a fish to kangaroos made of cheese.
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I doubt anyone knows what will happen to artists. But there are still so many edge cases where these models break down that I wouldn’t be relying on them exclusively.
I have a looming feeling AI generated art will devour the economic sustainability of being an illustrator not because art will be replaced by AI as a whole - but because it'll be so much cheaper and good enough for most people and corporations— Freya Holmér (@FreyaHolmer) June 2, 2022
Are there other issues with making images based purely on pattern-matching and then marking themselves on their answers? Any questions of bias, say, or unfortunate associations?
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Something you’ll notice in the corporate announcements of these models is they tend to use innocuous examples. Lots of generated images of animals. This speaks to one of the massive issues with using the internet to train a pattern matching algorithm – so much of it is absolutely terrible.
A couple of years ago a dataset of 80m images used to train algorithms was taken down by MIT researchers because of “derogatory terms as categories and offensive images”. Something we’ve noticed in our experiments is that “businessy” words seem to be associated with generated images of men.
So right now it’s just about good enough for memes, and still makes weird nightmare images (especially of faces), but not as much as it used to. But who knows about the future. Thanks Josh.AI image generators are having their moment right now. Thanks to OpenAI and their creation known as Dall-E 2, people across the internet have been able to make their own detailed images just from worded prompts.
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But quickly after OpenAI’s creation, we then saw Google release a direct competitor, using OpenAI’s open-source code to help create Imagen – an equally as impressive AI image generator, capable of once again making images just from simple phrases.
However, while both of these inventions were revolutionary in the AI world, they were only available to a select few, offering waitlists as they slowly gave access to new users.
Shortly after, the internet exploded with people making their own Dall-E images, albeit at a much lower level of quality. It wasn’t because OpenAI suddenly opened up access but instead because someone had made their own version of the software based heavily on the original, known as Dall-E mini.
Dalle Mini/dalle Mini · Just A Forum To Talk About Crayion.ai, Dalle Mini, Or Any Othe Type Of A.i Art Generator . No Spam. No Clickbait. No Adult Content Or 18+
We spoke to the creator of Dall-E mini about how it came to be, its viral potential and the future of the project.
Dall-E mini is yet another AI image generator taking the internet by storm. However, where it differs is that it is completely free for everyone to use. Despite the near-identical name, it has nothing to
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