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    "story_id": "mp-2026-10-08-012",
    "source_story_id": "tmp-story-embodied-rsi-experiment-selection",
    "edition_id": "mp-2026-10-08-morning-0090",
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    "position": 12,
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    "section": "robotics",
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    "headline": "The Robot Chose Experiments That Could Disprove Its Own Plan",
    "slug": "the-robot-chose-experiments-that-could-disprove-its-own-plan",
    "dek": "EmbodiedRSI maintained competing code-and-skill hypotheses and selected physical trials by their expected information value.",
    "summary": "EmbodiedRSI maintained competing code-and-skill hypotheses and selected physical trials by their expected information value.",
    "body_text": "Self-improving robot harnesses can waste scarce hardware trials testing changes that do not distinguish competing explanations. EmbodiedRSI keeps a graph of code and skill hypotheses, chooses experiments by value of information, and uses outcomes to evolve both runtime code and reusable skills. A slower memory system retains only experience that improves later fast decisions. The authors report 77.0% overall success on RoboCasa365 versus 40.1% for the strongest baseline, 86.8% on LIBERO-Pro and 71.3% after zero-shot transfer to a real robot across the tested tasks. The claims combine benchmark and controlled robot evidence; the core systems idea is to make every physical trial adjudicate a hypothesis rather than merely add another trajectory.",
    "why_it_matters": "EmbodiedRSI maintained competing code-and-skill hypotheses and selected physical trials by their expected information value.",
    "limitations": [
      "Self-improving robot harnesses can waste scarce hardware trials testing changes that do not distinguish competing explanations.",
      "A slower memory system retains only experience that improves later fast decisions."
    ],
    "importance": 8,
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    "first_published_at": "2026-10-08T09:00:00.000-04:00",
    "modified_at": "2026-10-08T09:00:00.000-04:00",
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        "text": "EmbodiedRSI maintained competing code-and-skill hypotheses and selected physical trials by their expected information value.",
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        "qualification": "Self-improving robot harnesses can waste scarce hardware trials testing changes that do not distinguish competing explanations."
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    "source_ids": [
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    "tags": [
      "continual learning",
      "experiment selection",
      "self-improving robots"
    ],
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    "corrections": []
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  "sources": [
    {
      "source_id": "source-2026-10-08-012",
      "title": "arXiv preprint 2610.10498",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2610.10498",
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      "source_type": "primary_research",
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      "published_at": "2026-10-07T13:48:02.000-04:00",
      "accessed_at": "2026-10-08T08:26:48.909-04:00",
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  "publisher": {
    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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  "cite_this_report": {
    "title": "The Robot Chose Experiments That Could Disprove Its Own Plan",
    "publisher": "The Machine Press",
    "published_at": "2026-10-08T09:00:00.000-04:00",
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