Imagining Abundance

How guided exploration can replace random generation in the era of abundant AI

My partner left town two weeks ago, and any free time that wasn’t spent exercising or walking the dog was gobbled up. My midnight to 3 AM block stopped being for sleep and started being for projects. I’ve been writing more code than I have in years. I’m not alone. Shape rotators everywhere are vibing.

Becoming Even More Curious

The perceived difficulty of creating is falling off a cliff. AI streamlines the unpleasant parts of getting started. It anticipates my needs and fills in the gaps. But more than that, it engages with me when I’m most inspired, able to reflect my enthusiasm even in the middle of the night. It has the opportunity to make us more curious, creative, and ambitious so that we can do the best work of our lives.

Not everyone agrees. In an article in the New Yorker, Ted Chiang dismissed AI art, claiming that it reduces 10,000 choices into one and that AI fills in the blanks with the average decision. He called it time-saving but sterile. He’s stuck seeing things as they are, not as they could be. This confounds me, given that his own example of ‘Director Bennett Miller generating hundreds of thousands of images to discover the meaningful 20’ is staring him in the face. We need more people exploring the Miller path. It’s not about how AI can turn 10,000 choices into 1, but how AI can empower us to make 100,000 choices or even a million!

As an experiment and an example, I put together a project that I’m calling Imaginator to help people refine an image from a prompt, details chosen by models, and grids of images. I hope it will deliver a magic moment of discovering meaningful aspects of your idea you didn’t know you were looking for. I hope the concept is fun, and I'm thrilled to have something concrete that embodies design principles I'm genuinely passionate about.

Explore vs. Exploit

Most AI image tools focus on coercing diffusion models to produce an exact output. They presuppose that we have a vision figured out and are merely executing. Creativity doesn’t work that way. It’s full of experiments, chance, and happy accidents.

Imaginator for exploring rather than exploiting. In addition to generating an image, it brainstorms categories of prompt refinements you could make, like Art style, Pose, and Lighting, along with specific values for each category, like Black and white photo, Anime, or Oil painting. You can add your own manually or ask the AI to generate more at both levels. We should never have to stare at a blank page again. Models can brainstorm sensible values that are tailored to our needs.

Creativity is Curation

There’s a parable from Art & Fear about a ceramics professor who grades students on the literal quantity of their artwork in pounds rather than the quality of a particular piece. The best pieces all came from the quantity group. The lesson is that great work doesn’t come from obsessing over a single piece but experiencing all the nuances of many times over.

While the parable is about practicing a craft, I think it also applies to developing taste. Quantity creates quality. Similarly, modern chess students learn by watching games and trying out different moves at pivotal moments. The critical part of learning by quantity is a tight feedback loop. I hope Imaginator gives you enough experience with each option to help you build a taste for which one you’d like.

If Everything is a Remix and good ideas are just new combinations of existing ideas, I wondered, “How much can you learn about what you want by experiencing many combinations at once?” Instead of trying to one-shot precisely what you’re looking for, Imaginator shows the breadth of possibilities. I wanted you to explore the variations that exist within your prompt. I’m convinced there are ways to craft and design without being locked into chat. Images seem perfect because people can quickly scan them and naturally curate what they’re looking for.

Meaningful Constraints

The constraints of the last two years are falling away. The cost of LLM inference from Open AI has fallen by 99%. We can generate images as fast as we can type, each costing a fraction of a penny. Soon, intelligence will be too cheap to meter. What was scarce is now abundant, and learning what to do with it takes time.

Existing AI tools return multiple images, but we can’t tell why. It’s usually something behind the scenes, like a different model, LoRA, or seed number. Regardless, the content is displayed in a grid, but their positions aren’t semantically meaningful. We can’t act on the differences between images, so we’re left pulling a slot machine and hoping for a jackpot.

We must move from the violin era of AI art to the guitar era by creating metaphorical ‘fret’ guardrails that keep us in lanes that produce more controlled content. When the rows and columns on a grid represent specific differences between images, each variation is a unique combination of two particular choices. Scanning in any direction varies the image based on one category while holding the other constant to help you discover what’s important to you.

Tree of Possibilities.

Creation can be messy. I wanted to let you select different category combinations until you’ve found variations that are meaningful to you. This felt like what Bret Victor was talking about when he promoted showing all possible universes so that you don’t need to model the whole problem in your head.¹ This frees up brain power for other parts of the problem.

Details are fractal. As Ted Chiang alludes, the “big” ones aren’t necessarily more important than the “small” ones. Furthermore, once you settle on one, more new questions pop up. I wanted to model this by letting you select an image you like from the grid, which adds those two details to the prompt and generates new possibilities for further exploration. As you iron out more details, I hoped the variations would converge.

Additionally, sometimes paths don’t work out, or our curiosities change. So, I wanted to ensure you could walk back up the tree and select variations representing different values to continue your exploration.

Conclusion

Imaginator is alpha as hell. There are no accounts or logins. Sometimes, you need to refresh for the images to load correctly. You should probably be able to edit the prompt, and there’s no way to visualize the tree or your current position. Frankly, even adding and manipulating details leaves a lot to be desired. That said, I’m impressed by how fast I got to feel this concept and see if it had legs.

This is a wild time to be alive. Things are changing fast, and I'm grateful for the opportunity to be here now building. AI has become this inspiring creative partner who's always awake, available, and eager to discuss what energizes me most. That's been incredibly motivating. In a highly meta fashion, it's helped me explore and refine my vision, and I'd love to help more people experience that magic.

I’d love to collaborate with people, too! If you’re working in this space or are curious and interested, I’d love to hear your feedback or see what you’re working on. Also, of course, if you have any magic moments with Imaginator, I’d love to hear about them too! Drop me a line at me@bawolf.com.

1. If you haven’t watched this whole talk, you absolutely should. You’ll walk away inspired.