AI各社の公式発表を1画面に。各社のページを個別に開かなくても最新の動きが追えます。
SpatialBlock：合成ブロック積み重ね問題でLVLMの空間インテリジェンスを強化
Large Vision-Language Models (LVLMs) have achieved strong performance on diverse visual tasks, yet their ability to reconstruct and reason about the 3D structure of the scene depicted in 2D images -- referred to as spatial intelligence -- remains limited. Existing approaches attempt to address this…
ロボットポリシーにおける言語転移の測定: Cosmos3ビジョンランゲージアクションポリシーへのギリシャ語追加
Robot foundation models are trained and evaluated predominantly in English, and robot demonstration corpora do not exist for most languages. We study the addition of Greek to an open vision-language-action stack using only machine-rephrased instructions and no architecture changes. The main challeng…
OpenWAM：体系的ワールドアクションモデル事前学習へのオープンでモジュール型なアプローチ
World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are monolithic: the generative backbone, visual representation, architecture, information flow, inference procedure, and tr…
ウクライナの独立ジャーナリズムを支援
OpenAI, AIRPPU and WAN-IFRA launch an AI program to help Ukrainian news organizations strengthen innovation, resilience, and independent journalism.
異星人の思考
Jakub Pachocki reflects on increasingly capable AI and the challenge of keeping it aligned. He calls for stronger safeguards and international coordination.
研究の加速：OpenAIの内部を探る
Inside OpenAI, coding agents are reshaping AI research. Explore early data on agent usage, experiment velocity, task complexity, and research acceleration.
DataFlex-RL:RLVR データポリシーの評価プラットフォーム
Data policies for reinforcement learning with verifiable rewards (RLVR) determine which rollouts are used, how strongly they are weighted, and which domains contribute to subsequent training batches. We introduce DataFlex-RL, an evaluation platform for comparing these choices under a common GRPO rec…
EvoSafeHarness：エージェント保護のためのモデル・ドメイン固有テストハーネスの進化
Large Language Model (LLM) agents are turning language into real-world effects, making safety necessary against both indirect prompt injections and direct harmful requests. System-level safety harnesses add an enforcement layer beyond model-level defenses, but existing harnesses are usually designed…
VDiff-Bench：画像の細部差異識別を評価するベンチマーク
Multimodal Large Language Models (MLLMs) perform strongly on general visual understanding tasks such as visual question answering, yet they often struggle with a basic comparative skill: identifying what has changed between two similar images. We introduce VDiff-Bench, a challenging multiple-choice…
DriveZero:人間のデモンストレーションを超えたエンドツーエンド運転
Most end-to-end autonomous-driving systems learn by imitating human driving logs, leaving their learned behavior constrained by the quality and behavioral coverage of the recorded trajectories. This report presents DriveZero, an end-to-end system that learns driving behavior beyond human demonstrati…
Gemini内のLyria 3.5で最高の楽曲を制作
Lyria 3.5, our best-sounding music generation model, is now available in the Gemini app and the Gemini API. Lyria 3.5 brings more expressive vocals and richer musical ar…
エージェント型インテリジェンスのための大規模コード統合スキル合成
Reusable skills give agents transferable procedural knowledge, making scalable acquisition essential for extending agents beyond prior experience. Existing methods face two limitations: trajectory-based synthesis requires interactions with specific environments, while document-derived skills may lac…
Occamy-1.0：協働向けオープンパレート最適境界35B知能
Co-work agents execute complex workflows that combine information gathering, tool use, coding, and file manipulation across many model invocations. Because cost and latency accumulate over the full episode, their practical value depends not only on peak capability but also on how efficiently that ca…
自分の発言を聞く: フルデュプレックス音声モデル向けセルフリスニング
Full-duplex spoken language models can listen and speak simultaneously, enabling them to handle interruptions and backchannels in human conversation. However, text generation, speech synthesis, and audio playback proceed asynchronously. As a result, what a model believes it has said may not match wh…
WearableQA：実世界のウェアラブルデータを用いた健康推論ベンチマーク
Recent advances in wearable sensing enable continuous monitoring of physiological and behavioral signals, yet existing benchmarks rarely evaluate whether AI systems can reason over a real user's longitudinal wearable record. We introduce WearableQA, a benchmark comprising 4,084 10-option multiple-ch…
BeaconKV：ビーコンクエリガイド方式のキャッシュ圧縮で大規模推論モデルの推論効率向上
Large Reasoning Models (LRMs) achieve superior problem-solving through extended Chain-of-Thought (CoT) generation, but the resulting key-value (KV) cache grows linearly with sequence length and creates severe memory bottlenecks, often exceeding GPU capacity for long reasoning traces. Existing KV cac…
GE-Act 2.0:ロボット操作向けワールドアクションモデルのプリトレーニングとスケーリング
World-action models (WAM) predict future states to guide robot actions, enabling learning from both action-free video and action-labeled interaction. Most inherit pretrained video generators, leaving WAM pretraining and scaling underexplored. We introduce Genie Envisioner Act 2.0 (GE-Act 2.0), a wor…
エンタープライズAI変革はエンドツーエンドプラットフォームに依存、Azureはこの瞬間のために構築された
The recognition for Microsoft over the past couple of weeks comes down to models, infrastructure, data, applications, and developer tools working as one system when AI moves into production. The post Enterprise AI transformation relies on the end-to-end platform: Azure was built for this moment appe…
GPT-6 Astra：Microsoft Foundryで業務向けフロンティア知能が一般利用可能に
GPT-6 Astra, OpenAI's newest frontier model, begins rolling out today through the Microsoft Foundry Limited Access Program, with availability expanding to participating customers over the coming days. The post GPT-6 Astra: Frontier intelligence for work, now generally available in Microsoft Foundry…
WeatherNext 3を発表、最も高度で正確なグローバル気象AI モデル
Daybreak for Frontline Defenders：重要インフラ保護に10億ドル
OpenAI introduces Daybreak for Frontline Defenders. A $1 billion commitment expands access to frontier cyber AI, training, and support for essential services.
NeoMME：効率的なマルチモーダル・ネイティブ多言語エンコーダ
PlaycoがGPT-6 Astraでゲーム試作における手作業修正を50%削減
Using GPT-6 Astra, Playco built three themed game prototypes from one grey box foundation and reported 50% fewer manual fixes than with the previous model.
LegoraがGPT-6 Astraで41のドキュメントを数分でレビュー
Legora used GPT-6 Astra to review 41 documents in minutes, find all four planted errors, and improve performance by nearly 40% in this financial-review workflow.
GPT-6 Astra: 次世代のインテリジェンス
Introducing GPT-6 Astra, our most intelligent and aligned model yet, with state-of-the-art capabilities across computer use, coding, cybersecurity, and science.
Percept-Lens: AI生成画像検出の詳細分析
ENEAS:適応的セグメンテーションのための埋め込みガイド型ニューラルアンサンブル
We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-promptable segmentation models, including the latest foundation models such as SAM 3, still suffer from temporal hallucinations, spatial fragmentation, and semantic misclassification: they fail to…
オーディオビデオモデルにおける注意三角形
Audio-video diffusion models rely on cross-modal attention to coordinate text, sound, and visual content, yet this same mechanism can introduce subtle and systematic semantic leakage. We study these models by probing and analyzing the ``attention triangle,'' comprising the three cross-attention edge…
FlowBalance：ポリシーオンの推論経験からの検証器ベース自己改善
A reasoning model can improve from its own on-policy experience, but this inner loop is fragile: terminal verifiers provide reliable yet sparse supervision, while dense same-model guidance can reinforce false confidence or overconcentrate learning on a narrow solution mode. We introduce FlowBalance,…
離散拡散によるLLMでのロスレス高速化を実現
Large Language Models (LLMs) owe much of their success to next-token prediction (NTP), but their autoregressive (AR) structure requires slow, sequential token generation. To overcome this bottleneck, we introduce diffusion-augmented LLMs, a new class of models that defines an AR model distribution w…
最後の翻訳ベンチマーク
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, standard benchmarks for machine translation are approaching saturation. Further, automatic translation metrics are unreliabl…
Iris：検索の最前線へ
We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe behind them. Tasks are reverse-constructed from the hyperlink structure of a web corpus: we author multi-hop chains over an entity graph distilled fro…
Scal3R: スケーラブルなオンライン3D再構成のための効率的なマルチ相対ポーズクエリの学習
Online 3D reconstruction models perform poorly on long videos. This happens because regressing poses relative to a fixed first-frame anchor forces extrapolation far beyond the training distribution. Small drifts accumulate and amplify into significant geometric collapse. However, we observe that per…
Puffin-World：3Dワールド状態をネイティブに統合したマルチモーダルモデルのスケーリング
We propose Puffin-World, a unified multimodal architecture that integrates physical understanding, spatial simulation, and 3D world generation and reconstruction without relying on external offline modules. To reliably construct and interact with 3D worlds, our framework jointly models three native…
大規模言語モデルのオンポリシー蒸留の再考 II：単一の訓練例
On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a teacher. Existing work has mainly studied its algorithmic behavior, leaving the role of training data unclear. We examine this role at the data-minimal limit by training on a single query. One-…
訓練による一括化：自然言語仕様をローカルニューラルネットワーク関数に変換
Many recurring text functions are easy to describe but difficult to implement with rules, while calling a large remote model for every input introduces repeated cost, latency, and dependency on a provider. We present compile by training, which turns a natural-language specification into a reusable n…
Gated DeltaNetが4ビット量子化で耐える理由: ハイブリッド27B LLMの再帰層向けNVFP4 W4A4
Hybrid LLMs pair softmax attention with linear-attention layers such as Gated DeltaNet (GDN), whose recurrent state summarizes the context in fixed size. Early community 4-bit quantizations of Qwen3.8-27B (48 GDN layers, 16 attention layers) left the GDN block in 8- or 16-bit precision -- especially…
Random Attention: 効率的な推論のためのKVキャッシュ削除戦略の再検討
Large language models achieve superior performance on tasks that require extended reasoning, but long chains of thought make the KV cache a severe memory bottleneck. Existing KV cache compression methods share one paradigm: score each cached token by some estimate of how much it will matter later, a…
Terminal-Universe: エージェント軌跡をスケーラブルなターミナル環境に変換
As terminal-based code agents become prevalent, agent trajectories have accumulated at scale, while realistic, executable environments remain scarce. However, environments are what agent post-training actually requires: each can be re-queried into many verifiable tasks and provides execution feedbac…
LLaDA-Image: 完全オープンなトレーニング手法で強力な画像生成モデルを構築
We introduce LLaDA-Image, a unified framework that pairs a 6B Diffusion Transformer (DiT) trained from scratch with a frozen vision-language understanding module built on the LLaDA2.0-Mini diffusion language model backbone. Instead of relying heavily on paired image-text data from the beginning, we…
自社管理できるメモリをコーディングエージェントに統合
350Mモデルのファインチューニング：100 GRPO ステップで構造化出力を改善
Lyria 3.5 in public preview : Released the next generation of Google's music generation models: lyria-3.5-clip-preview : Optimized for 30-second clips, loops, and rapid experimentation. lyria-3.5-pro-preview : Full-length song generation with improved musical coherence, natural vocals, and fine-grai…
OpenAI API Changelog 2026-09-03
Feature gpt-6-astra v1/responses v1/chat/completions Released GPT-6 Astra , our most capable model, built for the hardest end-to-end work. Use GPT-6 Astra for reasoning, coding, computer use, research, and document creation. It combines these capabilities to carry complex tasks from an initial reque…
安全性概要：GPT-6 Astra
GPT-6 Astra is our most capable broadly deployed model and our first to reach the Critical level of cybersecurity capability under our Preparedness Framework.
TRLとOpenEnvを使ってコーディングモデルを水彩画に
エージェント最適化の経済学：エンタープライズAIエージェント向けコンテキストエンジニアリング
AI cost optimization goes beyond model selection. Discover how context engineering in Microsoft Foundry helps lower AI costs by improving knowledge retrieval, tool selection, memory, and agent performance at scale. The post The Economics of Agent Optimization: Context engineering for enterprise AI a…
政府と企業のための積極的なサイバー防御
Introducing Fairwind Program
Gemini 3.8 FlashおよびGemini 3.8 Flash Cyberを発表
a hero image reading "Gemini 3.8 Flash and 3.8 Flash Cyber"