Introducing PRM (Physical Reasoning Model): a foundation model that infers and outputs an uncertainty-calibrated physical state from robot experience, so downstream policies can train on physics-complete signals — not just pixels and actions.
@unsupervizedai@Ranita_Jana
who wants bounding boxes and segmentations? we’re launching next week, and researchers in academia are eligible to receive our datasets for free. drop a comment and i’ll dm you
Hi @danfei_xu just finished reading your Article titled "To summon a Sensorimotor Ghost", really insightful, thought I should invite you to read my take on the data problem.
Humans have evolved an intuitive understanding of physical laws—not by learning from scientific books, but through rich, multisensory experience of the world.
Now we want machines to acquire a similar understanding purely from video data. Is it working?
https://t.co/uOykaLGrTg
“What once felt magical now felt inefficient. What was left were nostalgic memories of the good old days, which in hindsight weren’t that good. That’s how paradigm shifts work.”
A few best lines from the @Alfred_Lin essay!
Compare that to AI
LLMs → trillions of tokens (free-ish)
Vision → billions of images (internet-scale)
Robotics → ~10⁵–10⁶ trajectories (painfully collected)
We’re 6–9 orders of magnitude behind.