DEV Community: Stepan Kukharskiy

World Models?

Stepan Kukharskiy — Fri, 24 Apr 2026 04:37:25 +0000

World models are becoming the next real battleground in AI - not just chat, not just image generation, but systems that can simulate how environments behave, change, and respond.

And the field is not converging on one idea; it is splitting into competing philosophies.

LeCun / AMI Labs are betting that true intelligence will come from latent world models like JEPA, where the system predicts abstract structure instead of reconstructing every pixel, and AMI has already raised more than $1B to pursue that path.

Runway and OpenAI Sora (RIP) represent another camp: generative world models that learn by predicting and rendering the world itself, with Runway now shipping GWM-1 variants for explorable worlds, robotics simulation, and avatars.

Google DeepMind Genie 3 pushes this even further toward real-time interactivity, generating navigable environments at 24 fps and letting users modify the world live with new prompts.

World Labs, founded by Fei-Fei Li, is especially interesting because it is aiming at spatial intelligence more directly: generating full 3D scenes from a single image or prompt, with geometry, depth, and navigation built in.

Then there is the code-based world model direction, where LLMs generate executable programs that simulate environments, and research shows this can make planning 4–6 orders of magnitude faster than relying on neural rollouts alone in formal domains.

To me, this is the important shift: AI is moving from describing the world to modeling the world.

And once a system can model a world, it can do much more than generate media - it can plan, test actions, reason about consequences, and eventually become a real design or robotics engine.

My bet is that there will not be one dominant world model architecture.

We’ll likely end up with different stacks for different needs: latent models for abstraction and planning, video models for realism, 3D models for spatial interaction, and code-based models for precision and control.

For anyone building in design, robotics, games, or spatial computing, this feels like the beginning of a new foundational layer - not just models that generate outputs, but models that can simulate possibility.

The companies that matter in the next wave of AI may not be the ones with the best chatbot. They may be the ones that build the best simulation layer for reality.

It also makes me wonder whether systems like Spellshape - which turn intent into structured modeling briefs, executable spatial actions, and editable 3D outcomes - are an early form of a design world model.  

Style as a Look vs Style as a Way of Knowing 🤔

Stepan Kukharskiy — Thu, 23 Apr 2026 13:12:28 +0000

Most conversations about AI and art treat style as something visible. Kazuo Iwamura reminds us that style can also be a way of knowing.

I’ve been thinking about Iwamura, the Japanese picture-book author and illustrator best known for the 14 Forest Mice books, and what makes his work feel so enduring. For me it is the method underneath them.

In an interview, Iwamura said that even after art school he continued to study plants and animals very closely, trying to depict the inner “life” that cannot be seen from the outside. That idea explains a lot about his visual language. His images are simplified, but they do not feel generic. They are gentle, but not vague. The calm in them seems to come from observation, selection, and restraint rather than from decorative sweetness alone. You can feel this in the way he places small creatures inside larger living environments: trees, grasses, weather, nests, paths, and seasonal change. The animals are anthropomorphic, but the world around them still feels attentively seen and ecologically grounded.

His process also appears deeply temporal. In the same interview, he spoke about ideas, sketches, and finished illustrations unfolding across the seasons, and his books repeatedly use seasonal transition as part of their emotional structure. He also named artists such as Leo Lionni, Marie Hall Ets, Felix Hoffmann, and Beatrix Potter as influences, especially books in which pictures carry the story. That matters, because he was not merely illustrating narratives about nature. He was building meaning through composition, pacing, gesture, and environment.

This is why I think Iwamura matters so much now. In the AI age, style is often reduced to a visual signature: palette, texture, softness, atmosphere. But Iwamura points toward something deeper: not “how do I make this look natural?” but “how do I observe the world closely enough that form and feeling emerge from that relationship?” He also believed children need not only good picture books, but direct experience of the natural world itself, a belief he carried into the museum he opened in Tochigi in 1998.

That is a powerful lens for design, architecture, and generative systems too. AI can already imitate style as a visual signature. What it still struggles with is style as compressed perception - an approach to the world built from attention, selection, and lived observation. That’s why Iwamura still matters.

Image: Spellshape - an AI agent that generates 3D you can edit later.