Dyna-2.1 describes Taku, a semi-humanoid robot built to run an end-to-end workflow with minimal human intervention, demonstrated by doing uncut hotel laundry on camera. The approach relies on pre-training its improved DYNA-2 action policy on 1 million hours of human video. This results in faster acquisition of new skills and more reliable workflow execution through a full-stack design (robot hardware, unified action representation, reinforcement-learned control, and a workflow orchestrator).
Milepost launched an iOS driving journal app that adds an MCP server so ChatGPT, Claude, and other AI agents can interact with your car route records. Pro costs $0 to record, with a paid Pro tier unlocking older history, exports, and deeper insights. As a result, drivers can log and share “Roadbooks” and view 3D route replays plus monthly recaps with AI-agent support.
SCLATE was introduced as an execution substrate that lets continual-learning agent benchmarks and unmodified agents share one event scheduler, while also acting as a rollout engine that records model-call tokens and log probabilities. It compresses a month-long scenario into hours by using a hybrid simulated clock, and post-training Qwen3.5-4B cuts file-line reading by 6.8× while raising SWE-bench Verified by 16.7 points. As a result, the work enables head-to-head continual-learning evaluations and finds added memory systems do not consistently outperform native harness memory, even as a model can learn to use both harness and memory effectively.
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