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。
Agora：集団自動研究の共有メモリとしてのGit
Autonomous research loops such as AutoResearch show that one coding agent can improve a training setup unattended. Run several of them and each session starts from scratch, so more agents tend to mean more duplicated search rather than more discovery. Agora is a shared memory for such agents: resear…
PPOにおける評論家学習の再考：値の平坦化理解と緩和
In reinforcement learning for large language models, Proximal Policy Optimization (PPO) commonly uses a critic to estimate state values and reduce the variance of policy updates. However, we uncover a systematic failure mode in PPO critics, which we call Value Flattening: state values, estimated fro…
ProgramDistill：インタラクティブウェブアプリから検証可能な参照ガイド型SWEタスクへ
Coding agents are typically evaluated with desired behavior specified through issues or instructions. In practical web development, however, agents may need to infer behavior from working software and implement it in an incomplete application. We introduce ProgramDistill, a benchmark evaluating codi…
ScienceIDE：世界の科学コードベースをエージェント学習環境へ変換
Scientific code repositories encode decades of human knowledge in executable models, methods, and tools. Yet fragmented toolchains, implicit domain conventions, and specialized correctness criteria make this knowledge difficult to convert into reliable learning experience-a challenge we call the sci…
Gemini 3.8 Live と 3.8 Live Extended Thinking を発表
Text "Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking" with the Gemini Spark, all on a light blue background
エージェントがタスクを完璧にこなした。次も成功するか？
Gemini で家事をこなす 4 つの方法
A photo of a broken doorknob with the prompt: How can I fix this?
あらゆる言語で万人のための AI
Animation of several words in different languages slowly zooming past
科学を加速し生活を向上させる AI の構築
B-roll showing diverse environments and people, including a teacher and students in a classroom and a patient with a doctor
社会的インパクトのための AI
Explore this collection to see how experts and local leaders are using AI breakthroughs to ensure everyone can share the opportunity of AI.
Googleの「AI & Economy ATLAS」から得られた新たな知見
Text "AI & Economy Atlas v1.0 2026" with the Google G and a spinning globe illustration
LLMアシスタント向けの検証可能なソーシャル推論
LLM assistants are widely used for daily social advice, yet evaluating their social reasoning in such consultation settings remains challenging since (i) it requires setups where the assistant learns about social situations from subjective user narratives, and (ii) social properties, such as others'…
経験からの確信：推論からエージェントまでの経験的確信度推定
Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that an output is correct decides what to ship, what to escalate, and what to retry. Existing confidence estimators, however, share one design premise: th…
LimiX-2：構造化データ汎用インテリジェンスの文脈メカニズムネットワーク
We introduce LimiX-2, a new model in the LimiX family, developed through model and data scaling guided by our previously established scaling laws. LimiX-2 adopts the Contextual Mechanism Networks (CMNs) paradigm and is pretrained with Context-Conditional Masked Modeling (CCMM). CMNs shifts the organ…
OpenAI API Changelog 2026-09-15
Feature Added API key creation governance controls at the organization and project levels. Administrators can allow only service-account keys, allow only user-owned project keys, or disable all new API key creation. Organization restrictions take precedence over project settings, and existing API ke…
基盤モデル時代のゲーム向けAI
Foundation models, alongside advances in learned game-world models, are reshaping AI across the game lifecycle. Beyond playing games, recent systems model players and game dynamics, support design and development, adapt player-facing experiences at runtime, and evaluate resulting artifacts. Yet thes…
Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking generally available (GA) : Released two new audio-to-audio models for real-time voice applications using the Live API: Gemini 3.8 Live ( gemini-3.8-live ): The default option for most low-latency voice agent experiences and real-time dialogue wit…
宇宙飛行士クリスティナ・コッホとGoogleのジェームス・マニイカが宇宙・技術・発見について語る
Christina Koch sits down with James Manyika, Google’s Senior Vice President of Research, Labs, Technology & Society.
DevFestが帰ってきた
Animation of the text "{DevFest} 2026 Join us! Google Developer Groups" with a globe icon, asterisk icon, icon
逆伝播なしで1000層ネットワークを訓練
Bellman Policy Optimization
Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models (LLMs). We introduce Bellman Policy Optimization (BPO), a critic-free method derived from Policy Mirror Descent (PMD). For autoregressive generation with terminal rewards, BPO uses the…
EvoOntology：データエージェント向け自己進化型オントロジーレイヤー
Data agents aim to fulfill natural-language instructions over heterogeneous data, including tables, files, and databases. However, data agents face a challenging agent-data gap: heterogeneous data resides outside the agent, while the agent can access it (e.g., column names and file paths) only throu…
RSIAgent：新環境での再帰的自己改善に向けた自律探索
Digital agents must often adapt to new environments whose interfaces, tools, and failure modes are not fully captured by pretrained models. We introduce RSIAgent, a training-free multi-agent framework for recursive self-improvement through autonomous memory construction. RSIAgent coordinates curricu…
LynnReal-Omni：エージェント向け視覚ワークフロー用ネイティブマルチモーダル動画生成
Video diffusion models are stochastic and hard to control: precise content often requires repeated sampling without guaranteed success, and long-horizon scenes drift in appearance, interactions, and temporal coherence. Agentic visual creation provides explicit references, editable 3D scenes, or exec…
PhysBrain 1.5：ビジョン言語モデルから物理基盤モデルへ
We present PhysBrain 1.5, a unified model for understanding physical environments, generating actions, and predicting future states. Motivated by the physical loop of observation, interaction, and environmental change, we bring these capabilities into a common learning framework. Starting from a gen…
Dream-RSI：進化する世界を通じた再帰的自己改善
Recursive self-improvement is becoming increasingly vital for autonomous AI agents, where progress hinges on discovering high-value solutions across complex domains. The driver of this process is effective exploration, however, managing and improving exploration strategies remains a major bottleneck…
Atria Dawn：エージェント型スーパーインテリジェンスの夜明け
As AI agents become participants in the development of their successors, they reshape both the production of intelligence and the role of human researchers. We introduce Atria Dawn Preview, a foundation agentic language model designed for scientific research and engineering workflows, with the goal…
Perplexity、GPT-6 Astraをエンドツーエンドシステムに採用
Perplexity uses Astra to write communications, change software, and monitor production systems, and checks in much less frequently than with earlier models.
Realtime-Venus：非同期委譲を備えた全二重相互作用システム
Natural interaction in digital and physical environments requires continuous perception and timely responses. Spoken dialogue relies on acoustic and linguistic cues, while video interaction also requires grounding the conversation in evolving visual context. We present Realtime-Venus, a proactive fu…
StepAudio 3 Realtime Technical Report
Realtime spoken interaction demands deep reasoning, prompt responses, and fluid turn-taking. We present StepAudio 3 Realtime, an audio-language foundation model organized around a continuous listen-converse-think-act loop. Deep Perception captures rich acoustic cues to interpret user intent, while S…
Cognition、Devinが自動テストをGPT-6 Astraで実行可能に
GPT‑6 Astra improves Devin’s ability to test software and show that it works, with the goal of helping engineers review less code and ship more.
ChatGPT 10億ユーザー超を支えるオンラインストレージの急速スケーリング
Learn how OpenAI evolved Habitat from a Python library into a globally distributed storage platform serving 1 billion ChatGPT users and 22M requests per second.
汎用エージェント反復：反復的方針改善と再帰的自己改善のための統一フレームワーク
When we speak of recursive self-improvement (RSI), are we speaking of a phenomenon, a mechanism, or a prospect? Towards autonomous and evolving intelligence, RSI is being claimed at many scales, while no single framework that formally describes these emerging instances exists. Its counterpart in the…
StepAudio 3 Music Technical Report
We introduce StepAudio 3 Music, a large-scale, long-form music generation model that supports explicit musical planning and open-domain text-controlled generation. The StepAudio Music Tokenizer represents audio as a 50-Hz stream from a 65536-entry single codebook, using semantically informed self-su…
ZGCM-1：数学とエージェント検索のための完全オープンで高効率な基盤モデル
In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on a core premise: compact models cannot passively memorize the open web, but can overcome parametric capacity limits by coupling deli…
ビジョン-アクション近道を打破：ロボティクス基礎モデルの汎化に向けたレイテントインターフェーストレーニング
Robot foundation models achieve strong in-distribution performance but often degrade under visual distribution shifts. When learning to generate actions from pretrained visual representations, models may exploit task-irrelevant visual cues that correlate with demonstrated actions within the training…
Fugu MaxとFugu Ultra v2のご紹介：パレート最適境界を調整
Microsoftが2026年Gartner Magic Quadrantコンテナ管理部門でリーダーに認定
Microsoft was named a Leader in the 2026 Gartner® Magic Quadrant™ for Container Management. Discover how AKS, Azure Arc, and Azure Container Apps help organizations run AI and hybrid workloads at scale. The post Microsoft named a Leader in the 2026 Gartner® Magic Quadrant™ for Container Management a…
エージェント最適化の経済学：AIエージェント統治がコストをコントロールしROIを実証
This blog post is the fourth and final installment of The Economics of Agent Optimization, which shares the strategies, capabilities, and proof points that can help you optimize agent costs and run AI as a managed investment system on Microsoft Foundry. The post The Economics of Agent Optimization:…
GeminiアプリがWindowsで利用可能に
Gemini is now on windows
Searchで次のレースに向けた3つの準備方法
Illustration on a blue background of technicolor runners with a magnifying glass and Gemini spark overlaid
研究者がCodexとChatGPTを使い新しい抗菌分子の探索に取り組む
César de la Fuente’s lab uses Codex and ChatGPT to search living and extinct genomes for antimicrobial candidates to fight drug-resistant infections.
誰もがデータを活用できるようになった
Meet the Data agent in ChatGPT Work. Connect company data, uncover insights, and build interactive dashboards with AI using natural language.
ClouderaとMistralが提携、エンタープライズデータ向けの独立型インテリジェンスを提供
Cloudera and Mistral join forces to bring specialized, sovereign AI intelligence to enterprise data, helping regulated industries innovate on their own terms.
連邦・州・地方・先住民政府向けのAIアクセスとサイバー防御を拡大
OpenAI and GSA will offer eligible federal, state, local, and tribal governments $0 license fees, 50% off usage, and expanded cyber defense support.
ChatGPT for Financial Servicesを発表
Introducing ChatGPT for Financial Services, combining built-in financial data and GPT-6 Astra for research, modeling, and client-ready materials.
人類が構築した最後のAI：真の再帰的自己改善へ向けて
Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and the process of future improvement. We first use the Headroom-Closed Index (HCI) to reveal the problems of existing LLMs, then introduce the RSI concept…