Category Archives: AI/ML

Fun papercraft-styled video

My friend Nathan Shipley has been deeply exploring AnimateDiff for the last several months, and he’s just collaborated with the always entertaining Karen X. Cheng to make this little papercraft-styled video:

“Neither Artificial nor Intelligent: Artists Working with Algorithms”

Just in case you’ll be around San Jose this Friday, check out this panel discussion featuring our old Photoshop designer Julie Meridian & other artists discussing their relationship with AI:

Panel discussion: Friday, February 23rd 7pm–9pm. Free admission

Featuring Artists: Julie Meridian, James Morgan, and Steve Cooley
Moderator: Cherri Lakey

KALEID Gallery is proud to host this panel with three talented artists who are using various AI tools in their artistic practice while navigating all the ethical and creative dilemmas that arise with it. With all the controversy around AI collaborative / generated art, we’re looking forward to hearing from these avant-garde artists that are exploring the possibilities of a positive outcome for artists and creatives in this as-of-yet undefined new territory.

“Boximator” enables guided image->video

Check out this research from ByteDance, the makers of TikTok (where it could well be deployed), which competes with tools like Runway’s Motion Brush:

Check out Sora, OpenAI’s eye-popping video model

Hot on the heels of Lumiere from Google…

…here comes Sora from OpenAI:

My only question: How did they not call it SORR•E? :-p

But seriously, as always…

OpenAI, Meta, & Microsoft promote AI transparency

Good progress across the board:

  • OpenAI is adding new watermarks to DALL-E 3
    • “The company says watermarks from C2PA will appear in images generated on the ChatGPT website and the API for the DALL-E 3 model. Mobile users will get the watermarks by February 12th. They’ll include both an invisible metadata component and a visible CR symbol, which will appear in the top left corner of each image.”
  • Meta Will Label AI Images Across Facebook, Instagram, & Threads
    • “Meta will employ various techniques to differentiate AI-generated images from other images. These include visible markers, invisible watermarks, and metadata embedded in the image files… Additionally, Meta is implementing new policies requiring users to disclose when media is generated by artificial intelligence, with consequences for failing to comply.”
  • Building trust with content credentials in Microsoft Designer
    • “When you create a design in Designer you can also decide if you’d like to include basic, trustworthy facts about the origin of the design or the digital content you’ve used in the design with the file.”

Firefly image creation & Lightroom come to Apple Vision Pro

Not having a spare $3500 burning a hole in my pocket, I’ve yet to take this for a spin myself, but I’m happy to see it. Per the Verge:

The interface of the Firefly visionOS app should be familiar to anyone who’s already used the web-based version of the tool — users just need to enter a text description within the prompt box at the bottom and hit “generate.” This will then spit out four different images that can be dragged out of the main app window and placed around the home like virtual posters or prints. […]

Meanwhile, we also now have a better look at the native Adobe Lightroom photo editing app that was mentioned back when the Apple Vision Pro was announced last June. The visionOS Lightroom experience is similar to that of the iPad version, with a cleaner, simplified interface that should be easier to navigate with hand gestures than the more feature-laden desktop software.

Check out my chat with Wharton

I had a chance to sit down for an interesting & wide-ranging chat with folks from the Wharton Tech Club:

Tune into the latest episode of the Wharton Tech Toks podcast! Leon Zhang and Stephanie Kim chat with John Nack, Principal Product Manager at Adobe with 20+ years of PM experience across Adobe and Google, about GenAI for creators, AI ethics, and more. He also reflects on his career journey. This episode is great if you’re recruiting for tech, PM, or Adobe.

Listen now on Apple Podcasts or Spotify.

As always I’d love to know what you think.

Making today’s AI interfaces “look completely absurd”

Time is a flat circle…

Daring Fireball’s Mac 40th anniversary post contained a couple of quotes that made me think about the current state of interaction with AI tools, particularly around imaging. First, there’s this line from Steven Levy’s review of the original Mac:

[W]hat you might expect to see is some sort of opaque code, called a “prompt,” consisting of phosphorescent green or white letters on a murky background.

Think about how revolutionarily different & better (DOS-head haters’ gripes notwithstanding) this was.

What you see with Macintosh is the Finder. On a pleasant, light background, little pictures called “icons” appear, representing choices available to you.

And then there’s this kicker:

“When you show Mac to an absolute novice,” says Chris Espinosa, the twenty-two-year-old head of publications for the Mac team, “he assumes that’s the way all computers work. That’s our highest achievement. We’ve made almost every computer that’s ever been made look completely absurd.

I don’t know quite what will make today’s prompt-heavy approach to generation feel equivalently quaint, but think how far we’ve come in less than two years since DALL•E’s public debut—from swapping long, arcane codes to having more conversational, iterative creation flows (esp. via ChatGPT) and creating through direct, realtime UIs like those offered via Krea & Leonardo. Throw in a dash of spatial computing, perhaps via “glasses that look like glasses,” and who knows where we’ll be!

But it sure as heck won’t mainly be knowing “some sort of opaque code, called a ‘prompt.'”

My panel discussion at the AI User Conference

Thanks to Jackson Beaman & crew for putting together a great event yesterday in SF. I joined him, KD Deshpande (founder of Simplified), and Sofiia Shvets (founder of Let’s Enhance & for a 20-minute panel discussion (which starts at 3:32:03 or so, in case the embedded version doesn’t jump you to the proper spot) about creating production-ready imagery using AI. Enjoy, and please let me know if you have any comments or questions!

The Founding Fathers talk AI art

Well, not exactly—but T-Paine’s words about how we value things still resonate today:

We humans are fairly good at pricing effort (notably in dollars paid per hour worked), but we struggle much more with pricing value. Cue the possibly apocryphal story about Picasso asking $10,000 for a drawing he sketched in a matter of seconds, but the ability to create which had taken him a lifetime.

A couple of related thoughts:

  • My artist friend is a former Olympic athlete who talks about how people bond through shared struggle, particularly in athletics. For him, someone using AI-powered tools is similar to a guy showing up at the gym with a forklift, using it to move a bunch of weight, and then wanting to bond afterwards with the actual weightlifters.
  • I see ostensible thought leaders crowing about the importance of “taste,” but I wonder how they think that taste is or will be developed in the absence of effort.
  • As was said of—and by?—Steve Jobs, “The journey is the reward.”

[Via Louis DeScioli]

After Effects + Midjourney + Runway = Harry Potter magic

It’s bonkers what one person can now create—bonkers!

I edited out ziplines to make a Harry Potter flying video, added something special at the end
byu/moviemaker887 inAfterEffects

I took a video of a guy zip lining in full Harry Potter costume and edited out the zip lines to make it look like he was flying. I mainly used Content Aware Fill and the free Redgiant/Maxon script 3D Plane Stamp to achieve this.

For the surprise bit at the end, I used Midjourney and Runway’s Motion Brush to generate and animate the clothing.

Trapcode Particular was used for the rain in the final shot.

I also did a full sky replacement in each shot and used assets from ProductionCrate for the lighting and magic wand blast.

[Via Victoria Nece]

Krea upgrades its realtime generation

I had the pleasure of hanging out with these crazy-fast-moving guys last week, and I remain amazed at the speed of their shipping velocity. Check out the latest updates to their realtime canvas:

Check out how trailblazing artist Martin Nebelong is putting it to use:

Google introduces Lumiere for video generation & editing

Man, not a day goes by without the arrival of some new & mind-blowing magic—not a day!

We introduce Lumiere — a text-to-video diffusion model designed for synthesizing videos that portray realistic, diverse and coherent motion — a pivotal challenge in video synthesis. To this end, we introduce a Space-Time U-Net architecture that generates the entire temporal duration of the video at once, through a single pass in the model. This is in contrast to existing video models which synthesize distant keyframes followed by temporal super-resolution — an approach that inherently makes global temporal consistency difficult to achieve. […]

We demonstrate state-of-the-art text-to-video generation results, and show that our design easily facilitates a wide range of content creation tasks and video editing applications, including image-to-video, video inpainting, and stylized generation.

Content credentials are coming to DALL•E

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.

Tutorial: Firefly + Character Animator

Helping discover Dave Werner & bring him into Adobe remains one of my favorite accomplishments at the company. He continues to do great work in designing characters as well as the tools that can bring them to life. Watch how he combines Firefly with Adobe Character Animator to create & animate a stylish tiger:

Adobe Firefly’s text to image feature lets you generate imaginative characters and assets with AI. But what if you want to turn them into animated characters with performance capture and control over elements like arm movements, pupils, talking, and more? In this tutorial, we’ll walk through the process of taking a static Adobe Firefly character and turning it into an animated puppet using Adobe Photoshop or Illustrator plus Character Animator.

“How Adobe is managing the AI copyright dilemma, with general counsel Dana Rao”

Honestly, if you asked, “Hey, wanna spend an hour+ listening to current and former intellectual property attorneys talking about EU antitrust regulation, ethical data sourcing, and digital provenance,” I might say, “Ehmm, I’m good!”—but Nilay Patel & Dana Rao make it work.

I found the conversation surprisingly engrossing & fast-moving, and I was really happy to hear Dana (with whom I’ve gotten to work some regarding AI ethics) share thoughtful insights into how the company forms its perspectives & works to put its values into practice. I think you’ll enjoy it—perhaps more than you’d expect!

Adobe’s hiring a prototyper to explore generative AI

We’re only just beginning to discover the experiential possibilities around generative creation, so I’m excited to see this rare gig open up:

You will build new and innovative user interactions and interfaces geared towards our customers unique needs, test and refine those interfaces in collaboration with academic research, user researchers, designers, artists and product teams.

Check out the listing for the full details.

Adobe Firefly named “Product of the Year”

Nice props from The Futurum Group:

Here is why: Adobe Firefly is the most commercially successful generative AI product ever launched. Since it was introduced in March in beta and made generally available in June, at last count in October, Firefly users have generated more than 3 billion images. Adobe says Firefly has attracted a significant number of new Adobe users, making it hard to imagine that Firefly is not aiding Adobe’s bottom line.

AI Holiday Leftovers, Vol. 3

AI Holiday Leftovers, Vol. 2

  • 3D:
  • Typography:
    • Retro-futuristic alphabet rendered with Midjourney V6: “Just swapped out the letter and kept everything else the same. Prompt: Letter “A”, cyberpunk style, metal, retro-futuristic, star wars, intrinsic details, plain black background. Just change the letter only. Not all renders are perfect, some I had to do a few times to get a good match. Try this strategy for any type of cool alphabet!”
    • As many others have noted, Midjourney is now good at type. Find more here.

AI Holiday Leftovers, Vol. 1

Dig in, friends. 🙂

  • Drawing/painting:
    • Using a simple kids’ drawing tablet to create art: “I used @Vizcom_ai to transform the initial sketch. This tool has gotten soo good by now. I then used @LeonardoAi_’s image to image to enhance the initial image a bit, and then used their new motion feature to make it move. I also used @Magnific_AI to add additional details to a few of the images and Decohere AI’s video feature.”
    • Latte art: “Photoshop paint sent to @freepik’s live canvas. The first few seconds of the video are real-time to show you how responsive it is. The music was made with @suno_ai_. Animation with Runways Gen-2.”
  • Photo editing:
    • Google Photos gets a generative upgrade: “Magic Eraser now uses gen AI to fill in detail when users remove unwanted objects from photos. Google Research worked on the MaskGIT generative image transformer for inpainting, and improved segmentation to include shadows and objects attached to people.”
    • Clothing/try-on:
      • PICTURE: PhotorealistIC virtual Try-on from UnconstRained dEsigns: “We propose a novel virtual try-on from unconstrained designs (ucVTON) task to enable photorealistic synthesis of personalized composite clothing on input human images.”
      • AnyDoor is “a diffusion-based image generator with the power to teleport target objects to new scenes at user-specified locations in a harmonious way.”
    • SDXL Auto FaceSwap enables to create new images using the face of a source image (example attached).

AI: Tons of recent rad things

  • Realtime:
  • 3D generation:
  • 3D for fashion, sculpting, and more:
  • AnimateDiff v3 was just released.
  • Instagram has enabled image generation inside chat (pretty “meh,” in my experience so far), and in stories creation, “It allows you to replace a background of an image into whatever AI generated image you’d like.”
  • Did you know that you can train an AI Art model and get paid every time someone uses it? That’s Generaitiv’s Model Royalties System for you.”

Pika Labs “Idea-to-Video” looks stunning

It’s ludicrous to think that these folks formed the company just six months ago, and even more ludicrous to see what the model can already do—from video synthesis, to image animation, to inpainting/outpainting:

Our vision for Pika is to enable everyone to be the director of their own stories and to bring out the creator in each of us. Today, we reached a milestone that brings us closer to our vision. We are thrilled to unveil Pika 1.0, a major product upgrade that includes a new AI model capable of generating and editing videos in diverse styles such as 3D animation, anime, cartoon and cinematic, and a new web experience that makes it easier to use. You can join the waitlist for Pika 1.0 at

“Emu Edit” enables instructional image editing

This tech—or something much like it—is going to be a very BFD. Imagine simply describing the change you’d like to see in your image—and then seeing it.

[Generative models] still face limitations when it comes to offering precise control. That’s why we’re introducing Emu Edit, a novel approach that aims to streamline various image manipulation tasks and bring enhanced capabilities and precision to image editing.

Emu Edit is capable of free-form editing through instructions, encompassing tasks such as local and global editing, removing and adding a background, color and geometry transformations, detection and segmentation, and more. […]

Emu Edit precisely follows instructions, ensuring that pixels in the input image unrelated to the instructions remain untouched. For instance, when adding the text “Aloha!” to a baseball cap, the cap itself should remain unchanged.

Read more here & here.

And for some conceptually related (but technically distinct) ideas, see previous: Iterative creation with ChatGPT.

NBA goes NeRF

Here’s a great look at how the scrappy team behind has helped enable beautiful volumetric captures of Phoenix Suns players soaring through the air:

Go behind the scenes of the innovative collaboration between Profectum Media and the Phoenix Suns to discover how we overcame technological and creative challenges to produce the first 3D bullet time neural radiance field NeRF effect in a major sports NBA arena video. This involved not just custom-building a 48 GoPro multi-cam volumetric rig but also integrating advanced AI tools from Luma AI to capture athletes in stunning, frozen-in-time 3D visual sequences. This venture is more than just a glimpse behind the scenes – it’s a peek into the evolving world of sports entertainment and the future of spatial capture.

Phat Splats

If you keep hearing about “Gaussian Splatting” & wondering “WTAF,” check out this nice primer from my buddy Bilawal:

There’s also Two-Minute Papers, offering a characteristically charming & accessible overview:

Iterative creation with ChatGPT

I’m really digging the experience of (optionally) taking a photo, feeding it into ChatGPT, and then riffing my way towards an interesting visual outcome. Here’s a gallery in which you can see some of the journeys I’ve undertaken recently.

  • Image->description->image quality is often pretty hit-or-miss. Even so, it’s such a compelling possibility that I keep wanting to try it (e.g. seeing a leaf on the ground, wanting to try turning it into a stingray).
  • The system attempts to maintain various image properties (e.g. pose, color, style) while varying others (e.g. turning the attached vehicle from a box truck to a tanker while maintaining its general orientation plus specifics like featuring three Holstein cows).
  • Overall text creation is vastly improved vs. previous models, though it can still derail. It’s striking that one can iteratively improve a particular line of text (e.g. “Make sure that the second line says ‘TRAIN’“).

Hands up for Res Up ⬆️

Speaking of increasing resolution, check out this sneak peek from Adobe MAX:

It’s a video upscaling tool that uses diffusion-based technology and artificial intelligence to convert low-resolution videos to high-resolution videos for applications. Users can directly upscale low-resolution videos to high resolution. They can also zoom-in and crop videos and upscale them to full resolution with high-fidelity visual details and temporal consistency. This is great for those looking to bring new life into older videos or to prevent blurry videos when playing scaled versions on HD screens.

Adventures in Upsampling

Interesting recent finds:

  • Google Zoom Enhance. “Using generative AI, Zoom Enhance intelligently fills in the gaps between pixels and predicts fine details, opening up more possibilities when it comes to framing and flexibility to focus on the most important part of your photo.”
  • Nick St. Pierre writes, “I just upscaled an image in MJ by 4x, then used Topaz Photo AI to upscale that by another 6x. The final image is 682MP and 32000×21333 pixels large.”
  • Here’s a thread of 10 Midjourney upsampling examples, including a direct comparison against Topaz.

Demos: Using Generative AI in Illustrator

If you’ve been sleeping on Text to Vector, check out this handful of quick how-to vids that’ll get you up to speed:

Reflect on this: Project See Through burns through glare

Marc Levoy (professor emeritus at Stanford) was instrumental in delivering the revolutionary Night Sight mode on Pixel 3 phones—and by extension on all the phones that quickly copied their published techniques. After leaving Google for Adobe, he’s been leading a research team that’s just shown off the reflection-zapping Project See Through:

Today, it’s difficult or impossible to manually remove reflections. Project See Through simplifies the process of cleaning up reflections by using artificial intelligence. Reflections are automatically removed, and optionally saved as separate images for editing purposes. This gives users more control over when and how reflections appear in their photos.

What’s even better than Generative Fill? GenFill that moves.

Back in the day, I dreaded demoing Photoshop ahead of the After Effects team: we’d do something cool, and they’d make that cool thing move. I hear echoes of that in Project Fast Fill—generative fill for video.

Project Fast Fill harnesses Generative Fill, powered by Adobe Firefly, to bring generative AI technology into video editing applications. This makes it easy for users to use simple text prompts to perform texture replacement in videos, even for complex surfaces and varying light conditions. Users can use this tool to edit an object on a single frame and that edit will automatically propagate into the rest of the video’s frames, saving video editors a significant amount of texture editing time.

Check it out:

Adobe Project Posable: 3D humans guiding image generation

Roughly 1,000 years ago (i.e. this past April!),  I gave an early sneak peek at the 3D-to-image work we’ve been doing around Firefly. Now at MAX, my teammate Yi Zhou has demonstrated some additional ways we could put the core tech to work—by adding posable humans to the scene.

Project Poseable makes it easy for anyone to quickly design 3D prototypes and storyboards in minutes with generative AI.

Instead of having to spend time editing the details of a scene — the background, different angles and poses of individual characters, or the way the character interacts with surrounding objects in the scene — users can tap into AI-based character posing models and use image generation models to easily render 3D character scenes.

Check it out:

Generative Match: It’s Pablos all the way down…

Here’s a fun little tutorial from my teammate Kris on using reference images to style your prompt (in this case, her pet turtle Pablo). And meanwhile, here’s a little gallery of good style reference images (courtesy of my fellow PM Lee) that you’re welcome to download and use in your creations.