Patrick Rim @PatrickRim
Co-Founder & CEO @buildpbc Prev. @GoogleDeepMind, @NVIDIA, @Meta, @Caltech, @Yale patrickqrim.github.io SF Bay Area Joined June 2024-
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Incredible, wouldn't have bet against @kevinbanghe and glad to be proven right
Today we introduce Kairos 1: the world's first model built to simulate individual human behavior. Frontier models only understand population averages, ignoring the individual differences that make us human. Kairos beats Persimmon, Astra, Fable, and Gemini across 13 simulation
@shawnshenjx maui is peak, glad you enjoyed 🌴🥥
See you in Sydney for NeurIPS 2026! 😃
Check out our new work on deconstructing spatial intelligence 🧠
oom more data coming in hot 🔥
Introducing Midcentury. We’re building the data and simulation infra for physical AI. Today, we’re coming out of stealth with a $15M Series Seed to scale robotics beyond polished demos. We’re already supporting frontier labs with: → The world’s largest egocentric dataset:
throwback to when I collected a million distorted and occluded digits off football jerseys models don't fail on clean data, they fail on the wrinkles. now we collect wrinkles at scale!
@paigeinsf @zhen_do_ob once you submit to the scaling laws, it becomes shockingly lucid!
Gotta give props to Build AI for holding the record for so long on this too; it was an awesome early release for the open source community
@eddybuild @aliteracy aged like fine wine
The best way to celebrate Labor Day is by creating jobs
@RyanMWexler Hammering the 9s needed for manipulation into LLMs is unwise. But distilling from them is a great starting point.
@_mbanani This is awesome, congrats to you and the team!
@eddybuild @cutie11_c she could be real you're hurting her feelings
pre-trained on Egocentric-1M data!
Today we are introducing Dyna-2, a world-action model pre-trained on one million hours of human video. At this scale, for the first time, we discovered several new scaling laws: • world-action models exhibit scaling law on human data across four orders of magnitude, from 1000
A personal update: I've left Berkeley to lead the development of human potential at Build AI. There are a million things that AI will be able to do in the near future. The most important of which is to create a world in which it allows us to become more human.
I’ve left DeepMind to lead research at Build AI Our first bet: scale monocular vision. We haven’t even scratched the surface :D
1M hours of human video sounds insane. That’s roughly 170 years of continuous waking experience. If you had people wear cameras specifically to collect it: 1,000,000 hours ÷ 8 hours/day = 125,000 person-days That’s ~343 people collecting 8 hours a day, every day, for an entire year. That’s a massive data operation. So I’m really curious: how exactly did Dyna-2 collect its 1M+ hours of egocentric human video?
Dyna-2, a World Action Model (WAM) — not a Vision-Language-Action (VLA) model — pre-trained on one million hours of human activity data. WAM is starting to show promising products. Excited to see its generalization capabilities improve dramatically.
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