@julianhquevedo is presenting WorldGym right now 4/25 10:30am-1pm at Pavilion 4 #4818. Come and check out how world models can be used to evaluate robot policies in the cloud!
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Super impressed by the Table Tennis robot from @SonyAI_global. As a TT player myself, I thought expert TT robot is decades away.
Amazed by how far state-estimation (ball location + spin) plus simulator RL could get us.
Proud of my student @mscard01 for being a part of this
For 40+ years, building a robot that could rally with an elite human table tennis player at full speed was an unsolved problem. Sony AI's Ace research project set out to change that—and the results are now accepted for publication in @Nature and featured on the cover.
Machine learning engineering (MLE) is the new agentic frontier. I'll be sharing our work on scaling RL for MLE agents at #ICLR2026:
1) RL of a small model outperforms a frontier model arxiv.org/abs/2509.01684
2) MLE-Smith: scale-up MLE tasks automatically arxiv.org/abs/2510.07307
Excited to share World-Gymnast: Training Robots with RL in a World Model.
Training a VLA policy in a world model with RL transfers to much improved real-robot success (according to third-party robot AutoEval).
Website: world-gymnast.github.io
Paper: arxiv.org/abs/2602.02454