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One World Model, Not One Control Language

TL;DR for operators Robotics teams often maintain separate models for navigation, arm manipulation, and hand interaction. That duplicates infrastructure and prevents each system from learning from the organization’s full pool of visual and physical experience. Worldscape-MoE1 shows that these controls can share one model without being forced through identical computation. Camera paths, robot commands, and hand-joint maps enter through pathways suited to their different structures, while the model activates shared computation alongside control-specific pathways. Under the reported shared training budget, this routed design outperforms dense mixed training in locomotion, manipulation, and hand-motion evaluation. The expected collapse from pooling unlike controls did not occur; performance weakened when every control had to use the same dense computation. ...

August 5, 2026 · 8 min · Zelina
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The Assistant Should Not Stop Watching to Speak

TL;DR for operators Live video assistants have a simple embarrassment problem: many of them stop watching while they talk. That is fine for a demo clip and disastrous for anything pretending to be real-time. The LyraV paper is useful because it treats this as a systems-control problem, not as a leaderboard beauty contest. The authors introduce Streaming Video-Language Synchrony: instead of processing frames, pausing, decoding a full sentence, and then resuming perception, the assistant interleaves incoming video frames with small chunks of generated tokens.1 The operational goal is not “say more words.” It is “keep seeing while speaking.” ...

June 29, 2026 · 19 min · Zelina