This Lego machine can easily create a beautiful pixelart of anything you want! It is programmed in Python, and, with help of OpenAI’s DALL-E 3, it can make anything!
Sten of the YouTube channel Creative Mindstorms demonstrates his very own robotprinter named Pixelbot 3000, made of LEGO bricks, that can produce pixel art with the help of OpenAI’s DALL-E 3 and AI images. Using a 32 x 32 plate and numerous round LEGO bricks, the robot printer automatically pins the pieces onto their designated positions until it forms the pixel art version of the image. He uses Python as his main programming language, and to create pixel art of anything, he employs AI, specifically OpenAI’s DALL-E 3.
The Designer team at Microsoft is working to enable AI-powered creation & editing experiences across a wide range of tools, and I’m delighted that my new teammates are rolling out a new set of integrations. Check out how you can now create images right inside Microsoft Teams:
Check out the latest work (downloadable for free here) from longtime Adobe veteran (and former VP of product at Stability AI) Christian Cantrell:
The new version of the Concept Art #photoshop plugin is here! Create your own AI-powered workflows by combining hundreds of different imaging models from @replicate — as well as DALL•E 2 and 3 — without leaving @Photoshop. This is a complete rewrite with tons of new features coming (including local inference).
When DALL•E first dropped, it wasn’t full-image creation that captured my attention so much as inpainting, i.e. creating/removing objects in designated regions. Over the years (all two of ’em ;-)) I’ve lost track of whether DALL•E’s Web interface has remained available (’cause who’s needed it after Generative Fill?), but I’m very happy to see this sort of selective synthesis emerge in the ChatGPT-DALL•E environment:
It’s a great question, and I think it’s really thoughtful that the day before I joined, the company was generous enough to run a Superb Owl—er, Super Bowl—commercial, just to help me explain the mission to my parents. 😀
But seriously, this ad provides a brief peek into the world of how Copilot can already generate beautiful, interesting things based on your needs—and that’s a core part of the mission I’ve come here to tackle.
So, it’s true: After nearly three great years back at Adobe, I’ve moved to just the third place I’ve worked since the Clinton Administration: Microsoft!
I’ve signed on with a great group of folks to bring generative imaging magic to as many people as possible, leveraging the power of DALL•E, ChatGPT, Copilot, and other emerging tech to help make fun, beautiful, meaningful things. And yes, they have a very good sense of humor about Clippy, so go ahead and get those jokes out now. :->
It really is a small world: The beautiful new campus (see below) is just two blocks from my old Google office (where I reported to the same VP who’s now in charge of my new group), which itself is just down the road from the original Adobe HQ; see map. (Maybe I should get out more!)
And it’s a small world in a much more meaningful sense: I remain in a very rare & fortunate spot, getting to help guide brilliant engineers’ efforts in service of human creativity, all during what feels like one of the most significant inflection points in decades. I’m filled with gratitude, curiosity, and a strong sense of responsibility to make the most of this moment.
Thank you to my amazing Adobe colleagues for your hard & inspiring work, and especially for chance to build Firefly over the last year. It’s just getting started, and there’s so much we can do together.
Thank you to my new team for opening this door for us. And thank you to the friends & colleagues reading these words. I’ll continue to rely on your thoughtful, passionate perspectives as we navigate these opportunities together.
From its first launch, Adobe Firefly has included support for content credentials, providing more transparency around the origin of generated images, and I’m very pleased to see Open AI moving in the same direction:
Early this year, we will implement the Coalition for Content Provenance and Authenticity’s digital credentials—an approach that encodes details about the content’s provenance using cryptography—for images generated by DALL·E 3.
We are also experimenting with a provenance classifier, a new tool for detecting images generated by DALL·E. Our internal testing has shown promising early results, even where images have been subject to common types of modifications. We plan to soon make it available to our first group of testers—including journalists, platforms, and researchers—for feedback.
Here are four minutes that I promise you won’t regret spending as Nathan Shipley demonstrates DALL•E 3 working inside ChatGPT to build up an entire visual world:
I mean, seriously, the demo runs through creating:
Ideas
Initial visuals
Logos
Apparel featuring the logos
Game art
Box copy
Games visualized in multiple styles
3D action figures
and more.
Insane. Also charming: its extremely human inability to reliably spell “Dachshund!”
Our friend Christian Cantrell (20-year Adobe vet, now VP of Product at Stability.ai) continues his invaluable world to plug the world of generative imaging directly into Photoshop. Check out the latest, available for free here:
1) Support for extreme resolutions (up to 1MP). 2) Automatic selection of optimal models. 3) Access to all SD versions (1.4, 1.5, 2.0, and 2.1). 4) Account credits and avatar.https://t.co/gqFWpAkfnopic.twitter.com/DSwbC2xstL
Among the great pleasures of this year’s revolutions in AI imaging has been the chance to discover & connect with myriad amazing artists & technologists. I’ve admired the work of Nathan Shipley, so I was delighted to connect him with my self-described “grand-mentee” Joanne Jang, PM for DALL•E. Nathan & his team collaborated with the Dalí Museum & OpenAI to launch Dream Tapestry, a collaborative realtime art-making experience.
The Dream Tapestry allows visitors to create original, realistic Dream Paintings from a text description. Then, it stitches a visitor’s Dream Painting together with five other visitors’ paintings, filling in the spaces between them to generate one collective Dream Tapestry. The result is an ever-growing series of entirely original Dream Tapestries, exhibited on the walls of the museum.
Whew—no more wheedling my “grand-mentee” Joanne on behalf of colleagues wanting access. 😅
Starting today, we are removing the waitlist for the DALL·E beta so users can sign up and start using it immediately. More than 1.5M users are now actively creating over 2M images a day with DALL·E—from artists and creative directors to authors and architects—with over 100K users sharing their creations and feedback in our Discord community.
We are currently testing a DALL·E API with several customers and are excited to soon offer it more broadly to developers and businesses so they can build apps on this powerful system.
It’s hard to overstate just how much this groundbreaking technology has rocked our whole industry—all since publicly debuting less than 6 months ago! Congrats to the whole team. I can’t wait to see what they’re cooking up next.
Karen X. Cheng & pals (including my friend August Kamp) went to work extending famous works by Vermeer, Da Vinci, and Magritte, then placing them into AR filter (which you can launch from the post) that lets you walk right into the scenes. Wild!
Creative director Wes Phelan shared this charming little summary of how he creates kids’ books & games using DALL•E, including their newly launched outpainting support:
Let the canvases extend in every direction! The thoughtfully designed new tiling UI makes it easy to synthesize adjacent chunks in sequence, partly overcoming current resolution limits in generative imaging:
We just released a new edit interface for DALL·E that lets you use Outpainting to expand beyond the original borders of an image!
You can use this to make images with different aspect ratios, or arbitrarily large images like murals or magazine covers. pic.twitter.com/OW4lC6HQFl
Speaking of Paul here’s a fun new little VFX creation made using DALL•E:
AI is going to change VFX. This is a silly little experiment but it shows how powerful dall-e 2 is in generating elements into a pre existing video. These tools will become easier to use so when spectacle becomes cheap, ideas will prevail#aiart#dalle#ufo@openaidalle#dalle2pic.twitter.com/XGHy9uY09H
Now the somewhat scarily named CLIP Interrogator promises exactly that kind of insight:
What do the different OpenAI CLIP models see in an image? What might be a good text prompt to create similar images using CLIP guided diffusion or another text to image model? The CLIP Interrogator is here to get you answers!
Here’s hoping it helps us get some interesting image -> text -> image flywheels spinning.
Though we don’t (yet?) have the ability to use 3D meshes (e.g. those generated from a photo of a person) to guide text-based synthesis through systems like DALL•E, here’s a pretty compelling example of making 2D art, then wrapping it onto a body in real time:
Asked #dalle2 to generate some jeans look in a style of Gustav Klimt, then put it on cloth template from the latest workshop from @SnapAR ✨👖 pic.twitter.com/lUH0YSqB1t
“This emerging tech isn’t perfect yet, so we got some weird results along with ones that looked like Heinz—but that was part of the fun. We then started plugging in ketchup combination phrases like ‘impressionist painting of a ketchup bottle’ or ‘ketchup tarot card’ and the results still largely resembled Heinz. We ultimately found that no matter how we were asking, we were still seeing results that looked like Heinz.”
Creator Paul Trillo (see previous) is back at it. Here’s new work + a peek into how it’s made:
To create this, the shot had to be tracked in 3D to create a moving mask that matches the camera move. The frames are exported out as pngs with transparency. Dall-e then fills in the gap of the transparent hole. The images are sequenced together and slowed down pic.twitter.com/GhQ4CtlnGB
