{"event":{"id":"evt-rt1-20221213","dedupe_key":"robotics_transformer_research:2022-12-13:google-research-publishes-rt-1-for-real-world-robotic-control-at-scale","event_type":"robotics_transformer_research","title":"Google Research publishes RT-1 for real-world robotic control at scale","summary":"RT-1 used a transformer policy trained on roughly 130,000 demonstrations covering more than 700 language-conditioned tasks collected using 13 robots.","occurred_at":"2022-12-13T00:00:00.000Z","published_at":"2022-12-13T00:00:00.000Z","observed_at":"2026-10-03T14:26:11.000Z","reconstructed_at":"2026-10-03T14:26:11.000Z","ingest_type":"live_world_scan","locations":null,"status":"verified","confidence":0.98,"metadata":{"actors":["Google Research","Everyday Robots"],"what_happened_at_time":"A transformer-based real-time robot policy was trained on a broad real-world task dataset and evaluated across thousands of trials.","evidence_at_time":"Google Research December 13 post and arXiv paper.","affected_layers":["layer-robotics","layer-models","layer-research","layer-software"],"change_kind":"robotics_data_and_policy_scaling","q3_continuity":"Q3 showed feedback-driven planning and generated robot code. RT-1 added scaling via data diversity and a learned language-conditioned action policy.","retrospective_inference":"Robot learning was adopting large-data transformer scaling patterns while remaining research.","uncertainty":"Not evidence of open-ended physical autonomy or general human interaction."},"created_at":"2026-10-03T14:45:10.918Z","updated_at":"2026-10-03T14:45:10.918Z"},"artifacts":[{"id":"art-rt1-20221213","canonical_url":"https://research.google/blog/rt-1-robotics-transformer-for-real-world-control-at-scale/","artifact_type":"robotics_research_release","title":"RT-1 Robotics Transformer","summary":"Google Research presented RT-1, trained on roughly 130,000 real-world demonstrations across more than 700 tasks using 13 robots, producing real-time actions from images and natural-language instructions.","creator_entities":["Google Research","Everyday Robots"],"released_at":"2022-12-13T00:00:00.000Z","content_hash":null,"metadata":{"historical_scope":"2022-Q4"},"created_at":"2026-10-03T14:45:10.910Z","updated_at":"2026-10-03T14:45:10.910Z","relation":"evidenced_by"}],"signals":[{"id":"sig-q4-robotics-data-scaling","statement":"Real-world robot learning showed a clearer scaling path through large, diverse demonstration datasets and transformer policies covering hundreds of language-conditioned tasks, without establishing general physical autonomy.","signal_type":"robotics_scaling_maturation","direction":"increasing","confidence":0.95,"epistemic_status":"supported_inference","mapping_mode":"retrospective","reconstructed_at":"2026-10-03T14:26:11.000Z","created_at":"2026-10-03T14:45:10.921Z","updated_at":"2026-10-03T14:45:10.921Z"}]}