{"schema_version":"onlylabs.public_signal.v1","title":"OpenAI Writing: Prediction and control with temporal segment models","description":"OpenAI writing signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/d09ec76a-31e9-4269-82dd-8a9ab84d981e","json_url":"https://onlylabs.fyi/signals/d09ec76a-31e9-4269-82dd-8a9ab84d981e/signal.json","generated_at":"2026-06-08T15:47:17.128+00:00","org":{"slug":"openai","name":"OpenAI","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/openai","dossier_json_url":"https://onlylabs.fyi/labs/openai/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/d09ec76a-31e9-4269-82dd-8a9ab84d981e","signal_json":"https://onlylabs.fyi/signals/d09ec76a-31e9-4269-82dd-8a9ab84d981e/signal.json","source":"https://openai.com/index/prediction-and-control-with-temporal-segment-models","lab_dossier":"https://onlylabs.fyi/labs/openai","lab_dossier_json":"https://onlylabs.fyi/labs/openai/dossier.json","analysis":"https://onlylabs.fyi/analysis/openai","analysis_json":"https://onlylabs.fyi/analysis/openai/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/openai/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":"https://onlylabs.fyi/topics/talking","topic_signals_json":"https://onlylabs.fyi/topics/talking/signals.json","topic_feed":"https://onlylabs.fyi/topics/talking/feed.xml","data_business":null},"answer_pack":{"answer":"OpenAI published Prediction and control with temporal segment models. 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High-signal details: Prediction and control with temporal segment models | OpenAI March 12, 2017 Prediction and control with temporal segment models Loading… Share Abstract We introduce a.... onlylabs links this event to 1 captured evidence page and 6 related writing signals.","signal_desk":"talking","source_context":{"source_url":"https://openai.com/index/prediction-and-control-with-temporal-segment-models","source_host":"openai.com","occurred_at":"2017-03-12T08:00:00+00:00","first_seen_at":"2026-06-05T05:42:57.832854+00:00","date_source":"rss.item_date","context":null},"context_markers":[{"label":"Lab","value":"OpenAI","source":"signal"},{"label":"Signal desk","value":"talking","source":"signal"},{"label":"Source host","value":"openai.com","source":"source"},{"label":"Watch term","value":"Safety and 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writing and discussion into a readable map of research themes, product framing, policy posture, launch narratives, and market attention.."},{"subject":"Prediction and control with temporal segment models","predicate":"has source host","object":"openai.com","text":"Prediction and control with temporal segment models has source host openai.com."},{"subject":"Prediction and control with temporal segment models","predicate":"has lab","object":"OpenAI","text":"Prediction and control with temporal segment models has lab OpenAI."},{"subject":"Prediction and control with temporal segment models","predicate":"has signal desk","object":"talking","text":"Prediction and control with temporal segment models has signal desk talking."},{"subject":"Prediction and control with temporal segment models","predicate":"has source host","object":"openai.com","text":"Prediction and control with temporal segment models has source host openai.com."},{"subject":"Prediction and control with temporal segment models","predicate":"has watch term","object":"Safety and alignment","text":"Prediction and control with temporal segment models has watch term Safety and alignment."}]},"intelligence":{"signal_desk":"talking","answer":"OpenAI published Prediction and control with temporal segment models. This talking signal gives public context for research themes, product direction, policy, or launch framing. 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Unlike dynamics models that operate over individual discrete timesteps, we learn the distribution over future state trajectories conditioned on past state, past action, and planned future action trajectories, as well as a latent prior over action trajectories. Our approach is based on convolutional autoregressive models and variational autoencoders. It makes stable and accurate predictions over long horizons for complex, stochastic systems, effectively expressing uncertainty and modeling the effects of collisions, sensory noise, and action delays. The learned dynamics model and action prior can be used for end-to-end, fully differentiable trajectory optimization and model-based policy optimization, which we use to evaluate the performance and sample-efficiency of our method. Authors Nikhil Mishra, Pieter Abbeel, Igor Mordatch Related articles Hierarchical text-conditional image..."},"evidence_pages":[{"url":"https://openai.com/index/prediction-and-control-with-temporal-segment-models","final_url":"https://openai.com/index/prediction-and-control-with-temporal-segment-models","title":"Prediction and control with temporal segment models","http_status":200,"content_type":null,"capture_method":"exa","fetched_at":"2026-06-08T15:47:17.128+00:00","bytes":null,"raw_path":null,"content_hash":null,"excerpt_chars":1200,"truncated":true,"excerpt":"Prediction and control with temporal segment models | OpenAI March 12, 2017 Prediction and control with temporal segment models Loading… Share Abstract We introduce a method for learning the dynamics of complex nonlinear systems based on deep generative models over temporal segments of states and actions. Unlike dynamics models that operate over individual discrete timesteps, we learn the distribution over future state trajectories conditioned on past state, past action, and planned future action trajectories, as well as a latent prior over action trajectories. Our approach is based on convolutional autoregressive models and variational autoencoders. It makes stable and accurate predictions over long horizons for complex, stochastic systems, effectively expressing uncertainty and modeling the effects of collisions, sensory noise, and action delays. The learned dynamics model and action prior can be used for end-to-end, fully differentiable trajectory optimization and model-based policy optimization, which we use to evaluate the performance and sample-efficiency of our method. Authors Nikhil Mishra, Pieter Abbeel, Igor Mordatch Related articles Hierarchical text-conditional image..."}],"related_signals":[{"id":"b3668d3b-26d2-40c0-9d4f-ed1a67927aa4","url":"https://onlylabs.fyi/signals/b3668d3b-26d2-40c0-9d4f-ed1a67927aa4","source_url":"https://openai.com/index/supporting-eu-trustworthy-ai-ecosystem","title":"Supporting Europe’s work in ensuring a trustworthy AI ecosystem ","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"openai","name":"OpenAI","category":"frontier-lab"},"occurred_at":"2026-06-11T00:00:00+00:00","first_seen_at":"2026-06-11T08:00:56.140796+00:00","date_source":"rss.item_date"},{"id":"2638c0a7-b372-409c-ac72-f6d81d6464dc","url":"https://onlylabs.fyi/signals/2638c0a7-b372-409c-ac72-f6d81d6464dc","source_url":"https://openai.com/index/using-codex-to-simulate-black-holes","title":"How an astrophysicist uses Codex to help simulate black holes","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"openai","name":"OpenAI","category":"frontier-lab"},"occurred_at":"2026-06-11T00:00:00+00:00","first_seen_at":"2026-06-11T07:01:16.936464+00:00","date_source":"rss.item_date"},{"id":"509ea784-51ec-4ede-855b-5a4d1b27d3be","url":"https://onlylabs.fyi/signals/509ea784-51ec-4ede-855b-5a4d1b27d3be","source_url":"https://openai.com/index/openai-on-oracle-cloud","title":"Access OpenAI models and Codex through your Oracle cloud commitment","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"openai","name":"OpenAI","category":"frontier-lab"},"occurred_at":"2026-06-10T20:00:00+00:00","first_seen_at":"2026-06-11T07:01:16.936464+00:00","date_source":"rss.item_date"},{"id":"4f051449-87f2-466e-941e-b5918381a8fe","url":"https://onlylabs.fyi/signals/4f051449-87f2-466e-941e-b5918381a8fe","source_url":"https://openai.com/index/prc-linked-influence-operations-ai-debates","title":"PRC-linked influence operations are targeting AI debates in the US","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"openai","name":"OpenAI","category":"frontier-lab"},"occurred_at":"2026-06-10T12:00:00+00:00","first_seen_at":"2026-06-11T07:01:16.936464+00:00","date_source":"rss.item_date"},{"id":"4507c0c1-cb74-4bb3-b62b-5f6c2d37e20d","url":"https://onlylabs.fyi/signals/4507c0c1-cb74-4bb3-b62b-5f6c2d37e20d","source_url":"https://openai.com/index/lseg","title":"From data to decisions: how LSEG is scaling trusted AI","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"openai","name":"OpenAI","category":"frontier-lab"},"occurred_at":"2026-06-10T00:00:00+00:00","first_seen_at":"2026-06-10T09:18:54.26094+00:00","date_source":"rss.item_date"},{"id":"fb16aa7a-c4ef-4859-b514-0839c2f1330d","url":"https://onlylabs.fyi/signals/fb16aa7a-c4ef-4859-b514-0839c2f1330d","source_url":"https://openai.com/index/nextdoor","title":"How engineers at Nextdoor use Codex to build without limits","context":null,"kind":{"key":"post_published","label":"Writing"},"org":{"slug":"openai","name":"OpenAI","category":"frontier-lab"},"occurred_at":"2026-06-09T12:00:00+00:00","first_seen_at":"2026-06-10T07:01:28.700378+00:00","date_source":"rss.item_date"}]}