Lightwheel

@LightwheelAI

Data and Simulation Infrastructure for Physical AI

Santa Clara, U.S.A.

lightwheel.ai

Replies Reposts Media Articles

Lightwheel
@LightwheelAI
Sep 8
Why does a simulation company open-source 100,000 hours of egocentric data? Because training data is scaling fast and evaluation isn't. @bgxc explains on RoboPapers: ego data is the most scalable way to train, simulation is the only scalable way to test. EgoSuite-Open100k is
RoboPapers
@RoboPapers
Sep 8
Robotics has a data problem, and egocentric data is a compelling way to solve it because egocentric data is (1) scalable — it’s cheap to collect — and (2) easily captures the breadth and diversity of real human tasks, while (3) being true to real physics. Lightwheel recently
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Lightwheel
@LightwheelAI
Sep 2
We were on the ground this week at LEAP x DeepFest AI 2026. Martin Elbs spoke on Building the Continuous Learning System for Physical AI, and how closing the loop between data, simulation, evaluation, deployment, and real-world feedback can accelerate how robots learn. Louis
Lightwheel
@LightwheelAI
Sep 1
Scale alone doesn’t make egocentric data valuable. Diversity does. EgoSuite-Open100K, spans 15k+ tasks and 15k+ scenes across 7 environment categories and 18 task categories. The first 10k hours are open now, with more coming as we build toward 100K. egosuite100k.lightwheel.ai
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Lightwheel
@LightwheelAI
Aug 26
Most egocentric data at scale is private. We think that's worth changing. With @huggingface, we've released the first 10,000 hours of EgoSuite-Open100K — an open egocentric human dataset for Physical AI. huggingface.co/blog/Lightwhee… #Robotics
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Lightwheel
@LightwheelAI
Aug 21
The largest fully annotated open egocentric human dataset. Today we're open-sourcing EgoSuite-Open100K with @huggingface : 100,000 hours of egocentric human data, free for anyone to use. Physical AI has a scaling law of its own now, and its input is human data. That part is
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