{"schema_version":"onlylabs.public_signal.v1","title":"OpenAI Writing: Scaling laws for neural language models","description":"OpenAI writing signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/47e8fd57-6f1b-48be-be83-17555443b8d7","json_url":"https://onlylabs.fyi/signals/47e8fd57-6f1b-48be-be83-17555443b8d7/signal.json","generated_at":"2026-06-08T15:46:57.828+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/47e8fd57-6f1b-48be-be83-17555443b8d7","signal_json":"https://onlylabs.fyi/signals/47e8fd57-6f1b-48be-be83-17555443b8d7/signal.json","source":"https://openai.com/index/scaling-laws-for-neural-language-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":{"radar":"https://onlylabs.fyi/data-radar","radar_json":"https://onlylabs.fyi/data-radar.json","opportunities":"https://onlylabs.fyi/opportunities","opportunities_json":"https://onlylabs.fyi/opportunities.json","lanes":[{"key":"infrastructure","label":"Infrastructure","url":"https://onlylabs.fyi/data-radar/infrastructure","json_url":"https://onlylabs.fyi/data-radar/infrastructure/signals.json"}]}},"answer_pack":{"answer":"OpenAI published Scaling laws for neural language models. This talking signal gives public context for research themes, product direction, policy, or launch framing. High-signal details: Scaling laws for neural language models | OpenAI January 23, 2020 Scaling laws for neural language models Loading… Share Abstract We study empirical scaling laws for.... onlylabs links this event to 1 captured evidence page and 6 related writing signals. 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themes are labs choosing to explain publicly?","Which posts are attracting outside discussion?","Which writing reframes a recent release, model, hiring wave, or policy stance?","Which posts mention data, evals, infrastructure, safety, or deployment workflows?"],"signal_questions":["What public theme, launch framing, or research direction does this writing signal expose?","Which themes are labs choosing to explain publicly?","Which posts are attracting outside discussion?","Which data-business lane explains this signal: Infrastructure?","Do the 6 related writing signals show a repeated pattern?"],"output_fields":["org","theme","public_framing","traction","data_business_lane","evidence_url"],"data_business_relevance":"Public writing supplies the narrative layer over raw signals and helps identify which frontier-lab priorities are becoming externally 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models\" for frontier lab strategy and data-business implications."},"semantic_triples":[{"subject":"OpenAI","predicate":"published","object":"Scaling laws for neural language models","text":"OpenAI published Scaling laws for neural language models."},{"subject":"Scaling laws for neural language models","predicate":"is classified as","object":"writing signal","text":"Scaling laws for neural language models is classified as writing signal."},{"subject":"Scaling laws for neural language models","predicate":"belongs to","object":"talking desk","text":"Scaling laws for neural language models belongs to talking desk."},{"subject":"Scaling laws for neural language models","predicate":"has evidence coverage","object":"1 captured evidence page","text":"Scaling laws for neural language models has evidence coverage 1 captured evidence page."},{"subject":"Scaling laws for neural language models","predicate":"matches data-business lanes","object":"Infrastructure","text":"Scaling laws for neural 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of research themes, product framing, policy posture, launch narratives, and market attention.."},{"subject":"Scaling laws for neural language models","predicate":"has source host","object":"openai.com","text":"Scaling laws for neural language models has source host openai.com."},{"subject":"Scaling laws for neural language models","predicate":"has lab","object":"OpenAI","text":"Scaling laws for neural language models has lab OpenAI."},{"subject":"Scaling laws for neural language models","predicate":"has signal desk","object":"talking","text":"Scaling laws for neural language models has signal desk talking."},{"subject":"Scaling laws for neural language models","predicate":"has source host","object":"openai.com","text":"Scaling laws for neural language models has source host openai.com."},{"subject":"Scaling laws for neural language models","predicate":"has radar lane","object":"Infrastructure","text":"Scaling laws for neural language models has radar lane 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This talking signal gives public context for research themes, product direction, policy, or launch framing. High-signal details: Scaling laws for neural language models | OpenAI January 23, 2020 Scaling laws for neural language models Loading… Share Abstract We study empirical scaling laws for.... onlylabs links this event to 1 captured evidence page and 6 related writing signals. 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The loss scales as a power-law with model size, dataset size, and the amount of compute used for training, with some trends spanning more than seven orders of magnitude. Other architectural details such as network width or depth have minimal effects within a wide range. Simple equations govern the dependence of overfitting on model/dataset size and the dependence of training speed on model size. These relationships allow us to determine the optimal allocation of a fixed compute budget. Larger models are significantly more sample-efficient, such that optimally compute-efficient training involves training very large models on a relatively modest amount of data and stopping significantly before convergence. Authors Jared Kaplan, Sam McCandlish, Tom Henighan, Tom Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, Dario Amodei Related articles Deep double descentPublicationDec 5, 2019 How AI training scalesMilestoneDec 14, 2018 Embedding AI into..."},"evidence_pages":[{"url":"https://openai.com/index/scaling-laws-for-neural-language-models","final_url":"https://openai.com/index/scaling-laws-for-neural-language-models","title":"Scaling laws for neural language models","http_status":200,"content_type":null,"capture_method":"exa","fetched_at":"2026-06-08T15:46:57.828+00:00","bytes":null,"raw_path":null,"content_hash":null,"excerpt_chars":1200,"truncated":true,"excerpt":"Scaling laws for neural language models | OpenAI January 23, 2020 Scaling laws for neural language models Loading… Share Abstract We study empirical scaling laws for language model performance on the cross-entropy loss. 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