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ChatGPT 10億ユーザーに対応するオンラインストレージの急速スケーリング（後編）
Learn how OpenAI scaled Habitat with reliable multi-tenancy, global caching, and Azure Cosmos DB to deliver 12× faster reads for ChatGPT.
LitPivot：文献ランドスケープ内の動的コンテキスト化による研究アイデアの開発
Gemini 4 Argonで5人のビルダーが何を作っているか
Collage showing five builds with Gemini 4 Argon
最先端モデルの訓練環境をセキュアに
OpenAI explains how we strengthened containment for frontier model training and evaluation, including offline environments and high-compute red-teaming.
感覚運動アライメント：具現化ポリシー成功のためのプラトニック代理
Robot foundation models are typically evaluated through costly closed-loop rollouts, motivating low-cost offline proxies for model capability. The Platonic Representation Hypothesis (PRH) suggests that as representations improve, modalities such as vision and language converge toward a shared statis…
MLLMの検索ヘッドに関する広角的分析
Locating relevant evidence in long inputs is a core capability of Multimodal Large Language Models. Prior studies attribute this capability to retrieval heads, a sparse set of attention heads that transfer information from the context to the output. However, these analyses are confined to a limited…
実環境の音響シーンにおける効率的なストリーミング音声映像目標話者抽出
Streaming audio-visual target speaker extraction (AVTSE) is essential for latency-sensitive applications. However, current causal systems face two coupled gaps. First, standard benchmarks fix the number of speakers at two and ignore the near-/far-field interference, reverberation, and sudden noise o…
テスト時メモリ進化は科学的発見でテスト時トレーニングを上回るか
Recent test-time training (TTT) frameworks have enabled open-weight large language models (LLMs) to outperform inference-only frameworks powered by frontier models on scientific discovery tasks. However, TTT introduces additional computational cost for online weight updates during the discovery proc…
AnimaがGPT-6とGPT-Liveで診療所の待機時間を75%削減
Anima expands what care teams can do with OpenAI models, giving them more capacity to respond to patients.
WorldCast：大型カメラ動作制御による世界一貫性キャラクタービデオ生成
Precise camera control is essential for cinematic character video generation, yet existing methods struggle to follow large-angle trajectories with combined rotation, translation, and radius variation from arbitrary initial azimuths. Such viewpoint changes also reveal character regions unseen in the…
トレースによる検証：AIエージェントハーネスの信頼性と障害要因の特定ベンチマーク
LLM agents are increasingly used to solve real-world problems, and their effectiveness depends on both the underlying models and the harnesses that support their operation. However, most existing benchmarks focus on model capabilities and overall agent performance, with limited attention to the eval…
RynnUnify：統一された実体化AIブレインに向けて
We introduce RynnUnify, a 16B unified embodied model that combines strong embodied understanding with long-horizon visual planning through interleaved video--language reasoning. With capabilities spanning spatial reasoning, physical prediction, and grounding, RynnUnify connects an understanding of t…
RSIHub：エージェント進化手法のための合成可能フレームワーク
Agent-evolution methods use execution feedback to improve prompts, skills, tools, and orchestration, but their implementations often rebuild the same experimental machinery. We present RSIHub, an open-source framework for building, comparing, and extending these methods on shared infrastructure. Rec…
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OpenAIとポーランドのNASKがAI安全保障推進で提携
OpenAI and Poland’s NASK are partnering on AI safety, security, and technical research to strengthen safeguards and support a more resilient digital ecosystem.
データベース評価をRL報酬に変換 - ThinkingBoxでエージェント後学習
Decisions APIでレスポンシブなアプリを構築
Fast, focused, low-cost decisions for any application.
OlmoEarth v1.3、全地球対応の最先端埋め込みモデル
樹冠を超えて：世界の森林タイプをマッピング
A global map categorizing every 10-meter patch of land on Earth into distinct forest types.
MLLM潜在表現を活用 - シネマティックビデオ生成のための因子考慮予測学習
Cinematic video generation requires both temporal inference from limited inputs (i.e., sparse rather than frame-by-frame guidance) and factor-aware control of character, scene, action, and camera. Multimodal large language models (MLLMs) offer useful priors for both capabilities, but their represent…
IBM Granite時系列モデルによるアンサンブル予測
OpenAIにおけるFDEの意味
What forward deployed engineering means at OpenAI
R^2Orch：スキル内在化ループ内のセルフプレイによるエージェント編成の再帰的自己改善
In recent years, agentic orchestration has been widely applied to solve complex human tasks. However, existing orchestration learning still faces key challenges, including hand-designed curricula, advantage collapse when a task's rollouts all reach the same outcome, and unreliable evaluation signals…
VibeGame：AI型エンジンと自己進化対抗エージェント群を活用したプロンプト・トゥ・ゲーム開発
Large language model agents have enabled software development through natural-language interaction, but extending this paradigm to end-to-end game development remains challenging. Building a playable game requires coordinating code, scenes, assets, animations, physics, and configurations, while allo…
HiP3R: ロングホライゾン3D再構成のための階層型ポーズグラフ
Feed-forward models accurately estimate camera motion and 3D geometry from short video windows. However, computational and memory costs prevent direct inference on sequences containing thousands of frames. Long videos must therefore be processed as overlapping chunks. This division produces independ…
すべての重みは共有された離散的決定の道
We introduce TWIG (Tree-structured Weights with Inherited Gates), a representation in which every weight of a neural network is the end of a path of small discrete decisions: a sign, a shift by a power of two, a zero gate, an index into a shared table. Weights that belong together share the upper pa…
動画を通じた読む、書く、共有する、世界とのインタラクション
Video foundation models have advanced rapidly in understanding and generating visual sequences, while video world models seek to capture the underlying dynamics of the world they depict. Despite their different objectives, both concern the relationship between video observations and an evolving worl…
異なるタスク、異なるタイムステップ：拡散言語モデルのための時間的タスク認識量子化
Diffusion Language Models (DLMs) introduce unique quantization challenges due to their iterative denoising process. In this work, we reveal that quantization sensitivity is both taskand time-dependent, with different downstream tasks exhibiting distinct precision requirements across denoising steps.…
HiSTEVE 1.0：オープンワールドゲーム向けヒューマンインターフェース VLAエージェント
Building virtual embodied agents that operate in open-ended games like human players is a long-standing goal requiring both long-horizon autonomy and reliable native-interface control. As a procedurally generated open world, Minecraft provides a natural testbed for studying the integration of these…
FilmFlow：3Dバーチャル映画撮影のためのエージェントシステム
Complex camera motion is central to visual storytelling, yet translating cinematographic intent into controllable, executable camera trajectories remains challenging. We introduce FilmFlow, an agentic framework that converts natural-language instructions or reference videos into explicit camera traj…
UserArena：長期目標の買い物エージェント向けインタラクティブユーザーシミュレーションのベンチマーク
Agentic recommendation pursues shopper goals through sequences of context-dependent decisions. Developing and evaluating such policies requires faithful recommendation world models that capture both the interactive shopping environment and users' behavioral responses over long interactions. Existing…
WeVisOne-VL: オブジェクトからピクセルまで統一された視覚認識
Existing vision-language models (VLMs) remain unreliable for fine-grained visual perception. In this report, we present WeVisOne-VL (WeChat Vision All-in-One), a powerful VLM that unifies object-level and pixel-level perception through structured next-token prediction. It supports multiple visual ta…
IQuest-Q1: エージェンティックCLIシステムの基盤能力を拡張
We present IQuest-Q1, a sparse Mixture-of-Experts (MoE) agentic foundation model with 320B total parameters (15B activated). IQuest-Q1 is developed through a three-stage process: (1) stable and efficient pre-training, combining Stable SplitNorm, Muon, and muP with a two-stage curriculum whose second…
OpenAI API 更新ログ 2026-10-22
Update gpt-6-luna v1/decisions The Decisions API is now generally available with gpt-6-luna . Cache shared input across requests for prompt-cache discounts, include images in individual question instructions, and pass structured data directly with input_json . Each request now supports up to 400 que…
UberがOpenAIとChatGPT Workを全従業員に導入
Uber is rolling out ChatGPT Work to more than 30,000 employees, helping teams research, analyze data, create presentations, and complete complex workflows.
一貫した標準による幅広いアクセス
How OpenAI works with distribution partners to uphold consistent safeguards, support responsible access, and clarify expectations in our Usage Policies.
NVIDIA Kumo Relational、教師あり機械学習を大幅上回る、学習不要
SLMの語彙を最適化すれば推論コスト77%削減、実装レベルでの実績
AT&TがOpenAIで社内法務を刷新
AT&T is working with OpenAI to make legal knowledge easier to access. Learn how its LegalEdge team is rethinking intake and scaling legal judgment.
TorchNeuronのプロファイリング(その1)、AWS Trainiumでシステムレベル分析
Granite Speech 5.0: より正確で高速な文字起こし、翻訳、属性付与
ChatGPT Adsが26カ国に拡大、10万以上の広告主が利用
From local businesses to global brands, more advertisers can now reach people as they explore, compare and decide what to buy in ChatGPT.
Mistral、NVIDIAと連携してエンジニアリング向けAIを強化
Mistral is collaborating with NVIDIA to develop a new generation of AI-native engineering workflows powered by NVIDIA accelerated computing.
OpenAIのモデルがGoogle Cloudで利用可能に
OpenAI and Google Cloud are bringing frontier models and Codex workflows to Gemini’s Model Garden, available through Google Cloud Marketplace.
ChatGPTの新しい広告スタック構築、ユーザー信頼と関連性を実現
Learn how OpenAI built ChatGPT’s LLM-powered ad stack to understand conversational intent, keep ads separate from answers, and deliver relevant ads at scale.
世界規模の対応調整：エージェントが重大な脆弱性を発見
Patch the Planet connects security researchers, maintainers, and incident responders to help address critical vulnerabilities across open source.
数千のAIエージェント活用で生物データの新たなリードを発見
See how OpenAI, PerturbAI, and Scripps Research used distributed AI agents to uncover promising research leads in data from millions of brain cells.
東南アジアのデジタル経済、3680億ドルに達する見通し
Cover image for the e-Conomy SEA 2026 report titled Building the intelligent economy by Google, Temasek, and Bain and Company. A 3D illustration features a glowing yellow star surrounded by miniature scenes representing digital sectors, including data cen
ベンチマークは難易度に関する経験的測度
A benchmark is not merely a collection of test questions; it naturally induces an empirical measure over difficulty. In this work, we develop this measure-based view of benchmark evaluation. This perspective allows us to identify and formalize two central failure modes: measure mismatch, where the b…