Pho

We simulate the world @Pranalabs_ . Prev: @Anuttacon_ @miHoYo @PKU1898 @erasmusuni

[Pho @Jsavetheworld]

@hamedinsf for example？

[Pho @Jsavetheworld]

@yiliuai 抽象

[Pho @Jsavetheworld]

Can we actually build a digital Earth now?

[Pho @Jsavetheworld]

@jongranskog congrats!

[Pho @Jsavetheworld]

@jsiegz good luck on new journey

[Pho @Jsavetheworld]

@RenLeanna 经常看以至于忘了fo

[Prana Labs @PranaLabs_]

Great to work with @tripoai at SIGGRAPH 2026!

Their industry-leading 3D generation, our real-time contact physics. Together we showed a generated world can hold up under grasping and contact, not just look good.

Intelligence needs environments that push back. Excited for more.

[Pho @Jsavetheworld]

Excited to announce our SIGGRAPH Stage Session next Wed, July 22, co-hosted by Tripo × @PranaLabs_

Topic: "Seeing is Believing, Grasping is Physics" — a deep dive into how perception meets physical interaction.

Come witness it live. Be there. 🚀

[Tripo @tripoai]

We're excited to be part of SIGGRAPH 2026, a world-leading conference for computer graphics and interactive technology.

This year, Tripo is heading to Los Angeles with five accepted papers, a featured keynote, and technical sessions. During SIGGRAPH week, we will also take part in the Worlds in Action Hackathon and host various side events.

Meet the Tripo team and explore generative 3D, world models, and the future of interactive media.

See our full SIGGRAPH 2026 schedule: https://t.co/NKKxAOBSTU

[Changyi Lin @changyi_lin1]

Contact does not always deform surfaces, especially when interacting with liquids and soft objects. However, most existing tactile sensors rely on surface deformation to infer contact.

Excited to share LightTact, a visual-tactile fingertip sensor that makes contact directly visible. It provides:

- Deformation-Independent Sensing: contact is detected optically, not inferred from surface deformation.
- High-Contrast Raw Images: non-contact pixels stay near-black.
- Pixel-Level Contact Segmentation: robust across materials, forces, appearances, and external lighting conditions.

This project was co-led with Boda (https://t.co/LknVoGsVYi). Grateful to all co-authors for their contributions, and many thanks to @yxyang1995 for the insightful discussions.

We will present LightTact at RSS 2026 in Sydney next week!
Paper: https://t.co/YX3bf9H4Vd
Open-source: https://t.co/67NTIXOuJO

[Pho @Jsavetheworld]

Indeed. Gaming world is a natrual bridge between software and the real physical world. So much unexplored.

[Michael Black @Michael_J_Black]

The term “world model” is tossed around a lot but this is the real deal. From video and actions, the model learns a consistent representation of the physics, 3D environment, and game state of Rocket League.

I'm excited to have been part of this project because I see this as a step towards learning world models that can generalized to the real world. I’m a believer in learning from synthetic data (Sintel, SURREAL, AGORA, BEDLAM, BEDLAM2) and I’ve seen how models trained on synthetic data can generalize.

MIRA is an important step because it’s learned from video gameplay generated completely by bots. This provides a pathway to scaling and scaling is key to real-world generality. Traditional graphics and games provide a path to learning rich models of the world.

Check out the detailed tech report: https://t.co/C9aJPY8XRX

[Pho @Jsavetheworld]

Plenty of people chase the "world model" label for the fundraising narrative.
Very few simulate the world it's supposed to describe.

[Pho @Jsavetheworld]

@pmddomingos What about Ilya?

[Pho @Jsavetheworld]

@KangfuM def

[Pho @Jsavetheworld]

Emotional Intelligence is one of the hardest problems worth solving. Probably no real breakthrough until robotics catch up.

[Pho @Jsavetheworld]

Not making a decision is itself a decision.

[Pho @Jsavetheworld]

@Physion_Labs cool

[Physion Labs Official @Physion_Labs]

We've spoken with hundreds of ad creatives, marketing designers, filmmakers, and animation teams — and heard the same thing: the outputs look great… until they don't 😅. When they fail, it's incredibly hard to tell why. Is it the prompt, the model, or the world itself quietly breaking? That ambiguity is the real bottleneck.

Physion-Atlas 1.0 introduces a more objective, diagnostic way to evaluate video world models — moving beyond high-level comparisons to surface what actually matters. It disentangles prompt misalignment from physical and visual inconsistencies, grounding every judgment in explicit spatiotemporal evidence. Not just which output is better, but what breaks, when, where, and why. From abstract comparisons → diagnosable reality 🔍

📄 Blog: https://t.co/9aKSKfR7yS
📝 Evaluate your model: https://t.co/Jm1fshiF4a

[tamrat @tamrrat]

Introducing the mint mcp

Your coding agent can now generate fully immersive 3D worlds and 3D models

No Blender required :)

[Pho @Jsavetheworld]

@s_seele_ nice