building autonomous robots | @spacex | prev @aws @amazon

Joined October 2022
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what if we treated robot actions like audio waveforms? introducing neural action codec (NAC) a method for creating a compressed action vocabulary to train VLA policies
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the current step of robotics is figuring out a scalable robotic training recipe that can scale to widest distribution of tasks and embodiments
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yup, suprisingly audio codec models are good action tokenizer recipes! will presenting this work at corl in november!
Two of our arms striking a match, fully autonomous. Ahad Jawaid pulled this off for his CoRL 2026 paper on our previous generation arms. Our 2026 lineup is built for even more dexterous work, with academic discounts for research labs: buff.ly/nNrnn7K
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i’m going to be presenting this work at CoRL in Austin on novemeber 9-12th! would be cool to chat with people who are working on scaling robot foundation models and multimodal tokenization
what if we treated robot actions like audio waveforms? introducing neural action codec (NAC) a method for creating a compressed action vocabulary to train VLA policies
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i joined @SpaceX ! we need self replicating autonomous robots to make us a multi-planetary civilization
we will need robots building robots if we are going to have a space civilization. this is true even with agi or asi
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introducing hierarchical implicit q-chunking (HIQC) long-horizon offline reinforcement learning is hard the more steps an agent takes, the more value estimation errors compound i reduce this by decomposing the horizon into smaller segments with subgoals and action chunks
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this simple idea leads to an increase of nearly 10%+ average compared on 9 long horizon simulation task xitter.cf/ahadj0/status/20723344…
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i found by simply using a high level policy predicting latent subgoal and a low level policy prediciting action chunks you can reduce the number of bootstrapped value estimates to O((T/k)^(1/2)) xitter.cf/ahadj0/status/20723344…
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Check out Ahad's work on leveraging neural audio codec architectures for VLA action tokenization. An interesting direction that adapts ideas from audio compression to represent continuous robot actions.👇
what if we treated robot actions like audio waveforms? introducing neural action codec (NAC) a method for creating a compressed action vocabulary to train VLA policies
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introducing lattice a low-cost robot arm with a modular, detachable gripper so the robot can swap its own tools the adapter is $14 if you already have an so101 arm, and about $140 to build the full system from scratch it’s now fully open source
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also want to acknowledge @jeluna20 as a core contributor on this project, and the open source repos it’s built on: @lerobothf @uma_robots @vectorwang2
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