Category Archives: AI/ML

A love letter to splats

Paul Trillo relentlessly redefines what’s possible in VFX—in this case scanning his back yard to tour a magical tiny world:

Here he gives a peek behind the scenes: 

And here’s the After Effects plugin he used:

Relighting via Midjourney

Check out this impressive use of the new “retexture” feature, which enables image-to-image transformations:

Here’s a bit more on how the new editing features work:

Ideogram Canvas arrives

I’ve become an Ideogram superfan, using it to create imagery daily, so I’m excited to kick the tires on this new interactive tool—especially around its ability to synthesize new text in the style of a visual reference.

You can upload your own images or generate new ones within Canvas, then seamlessly edit, extend, or combine them using industry-leading Magic Fill (inpainting) and Extend (outpainting) tools. Use Magic Fill and Extend to bring your face or brand visuals to Ideogram Canvas and blend them with creative, AI-generated elements. Perfect for graphic design, Ideogram Canvas offers advanced text rendering and precise prompt adherence, allowing you to bring your vision to life through a flexible, iterative process.

Project Perfect Blend promises game-changing compositing in Photoshop

Oh man, for years we wanted to build this feature into Photoshop—years! We tried many times (e.g. I wanted this + scribble selection to be the marquee features in Photoshop Touch back in 2011), but the tech just wasn’t ready. But now, maybe, the magic is real—or at least tantalizingly close!

Being a huge nerd, I wonder about how the tech works, and whether it’s substantially the same as what Magnific has been offering (including via a Photoshop panel) for the last several months. Here’s how I used that on my pooch:

But even if it’s all the same, who cares?

Being useful to people right where they live & work, with zero friction, is tremendous. Generative Fill is a perfect example: similar (if lower quality) inpainting was available from DALL•E for a year+ before we shipped GenFill in Photoshop, but the latter has quietly become an indispensible, game-changing piece of the imaging puzzle for millions of people. I’d love to see compositing improvements go the same way.

The ceiling can’t hold us stuffed animals

As I drove the Micronaxx to preschool back in 2013, Macklemore’s “Can’t Hold Us” hit the radio & the boys flipped out, making their stuffed buddies Leo & Ollie go nuts dancing to the tune. I remember musing with Dave Werner (a fellow dad to young kids) about being able to animate said buddies.

Fast forward a decade+, and now Dave is using Adobe’s recently unveiled Firefly Video model to do what we could only dimly imagine back then:

Time to unearth Leo & get him on stage at last. :->

Flair AI promises brand-consistent video creation

As soon as Google dropped DreamBooth back in 2022, people have been trying—generally without much success—to train generative models that can incorporate the fine details of specific products. Thus far it just hasn’t been possible to meet most brands’ demanding requirements for fidelity.

Now tiny startup Flair AI promises to do just that—and to pair the object definitions with custom styling and even video. Check it out:

Meta AI introduces conversational editing

I was super hyped last year when Meta announced “Emu Edit” tech for selectively editing images using just language:

Now you can try the tech via Meta.ai and in various apps:

In my limited experience so far, it’s cool but highly unpredictable. I’ll test it further, and I’d love to know how it works for you. Meanwhile you can try similar techniques via https://playground.com/:

“Jurassic Park – 1950’s Super Panavision 70”

Chaos reigns!

I have no idea what AI and other tools were used here, but it’d be fun to get a peek behind the curtain. As a commenter notes,

The meandering strings in the soundtrack. The hard studio lighting of the close-ups. The midtone-heavy Technicolor grading. The macro-lens DOF for animation sequences. This is spot-on 50’s film aesthetic, bravo.

[Via Andy Russell]

Flux goes realtime with Krea

And if that headline makes no sense, it probably just means your not terminally AI-pilled, and I’m caught flipping a grunt. 😉 Anyway, the tiny but mighty crew at Krea have brought the new Flux text-to-image model—including its ability to spell—to their realtime creation tool:

Behind the scenes: DIY Deadpool

I love seeing how scrappy creators combine tools in new ways, blazing trails that we may come to see as commonplace soon enough. Here Eric Solorio (enigmatic_e) shows how he used Viggle & other tools to create his viral Deadpool animation:

See also some of his luchador moves, plus more on his various feeds:

Riffing on the world through Ideogram

I’ve been having a ball using the new Ideogram app for iOS to import photos & remix them into new creations. This is possible via their web UI as well, but there’s something extra magical about the immediacy of capture & remix. Check out a couple quick explorations I did while out with the kids, starting from a ballcap & the fuel tank of an old motorcycle:

AI news flash: People prefer paying for things that are actually good

I love this level of transparency from the folks behind Photo AI. Developer @levelsio reports,

[Flux] made Photo AI finally good enough overnight to be actually used by people and be satisfied with the results… it’s more expensive [than SD] but worth it because the photos are way way better… Not sure about profitability but with SD it was about 85% profit. With Flux def less maybe 65%… Very unplanned and grateful the foundational models got better.

We’re arguably in something of a trough of disillusionment in the AI-art hype cycle, but this kind of progress gives reason for hope: more quality & more utility do translate into more sustainable value—and there’s every reason to think that things will only improve from here.

Generative AI: Nuance > Sanctimony

Listen, I know that it’s a lot more seductive & cathartic to say “I f*cking hate generative AI,” and you can get 90,000+ likes for doing so, but—believe it or not—thoughtfulness & nuance actually matter. That is, how one uses generative tech can have very different implications for the creative community.

It’s therefore important to evaluate a range of risk/reward scenarios: What’s unambiguously useful & low-risk, vs. what’s an inducement to ripping people off, and what lies in the middle?

I see a continuum like this (click/tap to see larger):

None of this will draw any attention or generate much conversation—at least if my attempts to engage people on Twitter are any indication—but it’s the kind of thing actual toolmakers must engage with if we’re to make progress together. And so, back to work.

PS—This, always this:

Ahnuld’s Fables

My friend Nathan has fed a mix of Schwarzenegger photos & drawings from Aesop’s Fables into the new open-source Flux model, creating a rad woodcut style. That’s interesting enough on its own—but it’s so 24 hours ago, and thus he’s now taken to animating the results. Check out the thread below for details:

Pixel 9 adds on-device image generation

It’s wild that capabilities that blew our minds two years ago—for which I & others spent months on a waiting list for DALL•E, which demanded beefy servers to run—are now available (only better) running in your pocket, on your telephone. Check out the latest from Google:

Pixel Studio is a first-of-its-kind image generator. So now you can bring all ideas to life from scratch, right on your phone — a true creative canvas.9

It’s powered by combining an on-device diffusion model running on Tensor G4 and our Imagen 3 text-to-image model in the cloud. With a UI optimized for easy prompting, style changes and editing, you can quickly bring your ideas to conversations with friends and family.

Days of Miracles & Wonder, as always…

Google Pixel introduces an interactive “Add Me” feature

Back when I worked on Google Photos, and especially later when I worked in Research, I really wanted to ship a camera mode that would help ensure great group photos. Prior to the user pressing the capture button, it would observe the incoming video stream, notice when it had at least one instance of each face smiling with their eyes open, and then knit together a single image in which everyone looked good.

Of course, the idea was hardly new: I’d done the same thing manually with my own wedding photos back in 2005, and in 2013 Google+ introduced “AutoAwesome Smile” to select good expressions across images & merge them into a single shot. It was a great feature, though sadly the only time people noticed its existence is when it failed in often hilarious “AutoAwful” ways (turning your baby or dog into, say, a two-nosed Picasso). My idea was meant to improve on this by not requiring multiple photos, and of course by suppressing unwanted hilarity.

Anyway, Googlers gonna Google, and now the Pixel team has introduced an interactive mode that helps you capture & merge two shots—the first one of a group, and the second of the photographer who took the first. Check out Marques Brownlee’s 1-minute demo:

For more details, check out his full review of Google’s new devices.

That’s all well and good—but wake me when they decide to bring back David Hasselhoff photobombs:

 

Uizard & the future of AI-assisted design

Uizard (“Wizard”), which was recently acquired by Miro, has rolled out Autodesigner 2.0:

We take the intuitive conversational flow of ChatGPT and merge it with Uizard generative UI capabilities and drag-and-drop editor, to provide you with an intuitive UI design generator. You can turn a couple of ideas into a digital product design concept in a flash!

I’m really curious to see how the application of LLMs & conversational AI reshapes the design process, from ideation & collaboration to execution, deployment, and learning—and I’d love to hear your thoughts! Meanwhile here’s a very concise look at how Autodesigner works:

And if that piques your interest, here’s a more in-depth look:

AI stuff I need to see in Photoshop

…and other creative imaging tools, stat!

Google Research has devised “Alchemist,” a new way to swap object textures:

And people keep doing wonderful things with realtime image synthesis:

“How To Draw An Owl,” AI edition

Always pushing the limits of expressive tech, Martin Nebelong has paired Photoshop painting with AI rendering, followed by Runway’s new image-to-video model. “Days of Miracles & Wonder,” as always:

Meta releases SAM 2 for fast segmentation

Man, I’m old enough to remember rotoscoping video by hand—a process that quickly made me want to jump right out a window. Years later, when we were working on realtime video segmentation at Google, I was so proud to show the tech to a bunch of high school design students—only to have them shrug and treat it as completely normal.

Ah, but so it goes: “One of history’s few iron laws is that luxuries tend to become necessities and to spawn new obligations. Once people get used to a certain luxury, they take it for granted.” — Yuval Noah Harari

In any case, Meta has just released what looks like a great update to their excellent—and open-source—Segment Anything Model. Check it out:

You can play with the demo and learn more on the site:

  • Following up on the success of the Meta Segment Anything Model (SAM) for images, we’re releasing SAM 2, a unified model for real-time promptable object segmentation in images and videos that achieves state-of-the-art performance.
  • In keeping with our approach to open science, we’re sharing the code and model weights with a permissive Apache 2.0 license.
  • We’re also sharing the SA-V dataset, which includes approximately 51,000 real-world videos and more than 600,000 masklets (spatio-temporal masks).
  • SAM 2 can segment any object in any video or image—even for objects and visual domains it has not seen previously, enabling a diverse range of use cases without custom adaptation.

Neural rendering: Neo + Firefly

Back when we launched Firefly (alllll the way back in March 2023), we hinted at the potential of combining 3D geometry with diffusion-based rendering, and I tweeted out a very early sneak peek:

A year+ later, I’m no longer working to integrate the Babylon 3D engine into Adobe tools—and instead I’m working directly with the Babylon team at Microsoft (!). Meanwhile I like seeing how my old teammates are continuing to explore integrations between 3D (in this case, project Neo). Here’s one quick flow:

Here’s a quick exploration from the always-interesting Martin Nebelong:

And here’s a fun little Neo->Firefly->AI video interpolation test from Kris Kashtanova:

AI in Ai: Illustrator adds Vector GenFill

As I’ve probably mentioned already, when I first surveyed Adobe customers a couple of years ago (right after DALL•E & Midjourney first shipped), it was clear that they wanted selective synthesis—adding things to compositions, and especially removing them—much more strongly than whole-image synthesis.

Thus it’s no surprise that Generative Fill in Photoshop has so clearly delivered Firefly’s strongest product-market fit, and I’m excited to see Illustrator following the same path—but for vectors:

Generative Shape Fill will help you improve your workflow including:

  • Create detailed, scalable vectors: After you draw or select your shape, silhouette, or outline in your artboard, use a text prompt to ideate on vector options to fill it.
  • Style Reference for brand consistency: Create a wide variety of options that match the color, style, and shape of your artwork to ensure a consistent look and feel.
  • Add effects to your creations: Enhance your vector options further by adding styles like 3D, geometric, pixel art or more.

They’re also adding the ability to create vector patterns simply via prompting:

Photoshop’s new Selection Brush helps control GenFill

Soon after Generative Fill shipped last year, people discovered that using a semi-opaque selection could help blend results into an environment (e.g. putting fish under water). The new Selection Brush in Photoshop takes functionality that’s been around for 30+ years (via Quick Select mode) and brings it more to the surface, which in turn makes it easier to control GenFill behavior:

Magnific magic comes to Photoshop

I’m delighted to see that Magnific is now available as a free Photoshop panel!

For now the functionality is limited to upscaling, but I have to think that they’ll soon turn on the super cool relighting & restyling tech that enables fun like transforming my dog using just different prompts (click to see larger):

Realtime face editing with LivePortrait

I wish Adobe hadn’t given up (at least for the last couple of years and foreseeable future) on the Smart Portrait tech we were developing. It’s been stuck at 1.0 since 2020 and could be so much better. Maybe someday!

In the meantime, check out LivePortrait:

And now you can try it out for yourself:

tyFlow: Stable Diffusion-based rendering in 3ds Max

Being able to declare what you want, instead of having to painstakingly set up parameters for materials, lighting, etc. may prove to be an incredibly unlock for visual expressivity, particularly around the generally intimidating realm of 3D. Check out what tyFlow is bringing to the table:

You can see a bit more about how it works in this vid…

…or a lot more in this one:

How I wish Photoshop would embrace AI

Years ago Adobe experimented with a real-time prototype of Photoshop’s Landscape Mixer Neural Filter, and the resulting responsiveness made one feel like a deity—fluidly changing summer to winter & back again. I was reminded of using Google Earth VR, where grabbing & dragging th

Nothing came of it, but in the time since then, realtime diffusion rendering (see amazing examples from Krea & others) and image-to-image restyling have opened some amazing new doors. I wish I could attach filters to any layer in Photoshop (text, 3D, shape, image) and have it reinterpreted like this:

Magic Insert promises stylistically harmonized compositing

New tech from my old Google teammates makes some exciting claims:

Using Magic Insert we are, for the first time, able to drag-and-drop a subject from an image with an arbitrary style onto another target image with a vastly different style and achieve a style-aware and realistic insertion of the subject into the target image.

Of course, much of the challenge here—where art meets science—is around identity preservation: to what extent can & should the output resemble the input? Here it’s subject to some interpretation. In other applications one wants an exact copy of a given person or thing, but optionally transformed in just certain ways (e.g. pose & lighting).

When we launched Firefly last year, we showed off some of Adobe’s then-new ObjectStitch tech for making realistic composites. It didn’t ship while I was there due to challenges around identity preservation. As far as I know those challenges remain only partially solved, so I’ll continue holding out hope—as I have for probably 30 years now!—for future tech breakthroughs that get us all the way across that line.

Day & Night, Magnific + Luma Edition

Check out this striking application of AI-powered relighting: a single rendering is deeply & realistically transformed via one AI tool, and the results are then animated & extended by another.

Meanwhile Krea has just jumped into the game with similar-looking relighting tech. I’m off to check it out!

Can you use Photoshop GenFill on video?

Well, it doesn’t create animated results, but it can work perhaps surprisingly well on regions in static shots:

It can also be used to expand the canvas of similar shots:

OMG: DALL•E -> LEGO

Much amaze, wowo wowo:

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!

DesignBoom writes,

Sten of the YouTube channel Creative Mindstorms demonstrates his very own robot printer 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.

Glif enables SD-powered image remixing via right click

Fun! You can grab the free browser extension here.

* right-click-remix any image w/ tons of amazing AI presets: Style Transfer, Controlnets… * build & remix your own workflows with full comfyUI support * local + cloud!

besides some really great default presets using all sorts of amazing ComfyUI workflows (which you can inspect and remix on http://glif.app), the extension will now also pull your own compatible glifs into it!

MimicBrush promises prompt-free regional adjustment

The tech, a demo of which you can try here, promises “‘imitative editing,’ allowing users to edit images using reference images without the need for detailed text descriptions.”

Here it is in action:

Runway introduces Gen-3 video

Good grief, the pace of change makes “AI vertigo” such a real thing. Just last week we were seeing “skeleton underwater” memes with Runway submerged in a rusty chair. :-p I’m especially excited to see how it handles text (which remains a struggle for text-to-image models including DALL•E):