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Gordon Wetzstein

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@GordonWetzstein

Professor at Stanford University & Co-founder at Rhoda AI
Joined January 2010
53 Following 5.7K Followers 290 Posts

Latest posts 5

Gordon Wetzstein Verified account @GordonWetzstein
Really exciting new work: pi-H3 uses data-free distillation to reach 2–4 sampling steps. Amazing video quality generated faster than you can watch!
Hansheng Chen Verified account @HanshengCh 8h
Introducing pi-H3⚡, the fastest MiniMax H3 yet. 10 s of 768p video with audio generated in 9.2 s on a single B200.

How we did it:
Direct pixel output in 2 or 4 steps, no video VAE decoder.

Blog: hanshengchen.com/blog/pi-h3/
App: huggingface.co/spaces/Lakonik…

@StanfordAILab @LumaLabsAI
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Gordon Wetzstein Verified account @GordonWetzstein
What excites me most about mobile DVA is how little additional robot data it takes to learn robust mobility and manipulation. A powerful example of how web-scale video pretraining can make new robot capabilities easy to learn.
Rhoda AI @RhodaAI Nov 3
We taught a robot how to move around in only 15 minutes.

That’s all the mobility data our Direct Video-Action-powered robot needed to accomplish a task that requires mobility and manipulation.
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Gordon Wetzstein Verified account @GordonWetzstein
Excited about this new direction! Tokenizers typically optimize reconstruction (VAEs) or discrimination (DINO), creating a mismatch with downstream generation. RePR introduces a principled, scalable approach to learning representations specifically as tokenizers for generation.
Alan Baade Verified account @BaadeAlan Oct 19
1/ The tokenizer is a new scaling axis!

We introduce an approach for diffusable representation learning that's principled, scalable, and works when DINO/LeJEPA collapse.

We get joint tokenizer+diffusion scaling laws and it's compute-optimal vs raw diffusion

w/ @drfeifei @GordonWetzstein @jcjohnss @ericryanchan @vincesitzmann @KyleSargentAI

Thread, Paper, and Blogpost below
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Gordon Wetzstein Verified account @GordonWetzstein
A secure grasp needs continuous feedback on contact forces. At Rhoda, we’re giving robots tactile sensing and teaching our models to predict what they’ll feel next—a step toward more efficient, reliable manipulation, even when vision is available.
Rhoda AI @RhodaAI Oct 14
What can a robot do without vision?

We gave our robot a sense of touch and showed it can recognize and retrieve objects with its cameras blindfolded.

Introducing Rhoda’s new tactile sensor—it feels pressure, texture, vibration, slip, and temperature, just like your fingertips.
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