全部动态

ML4 is now open-weight! Frontier capabilities on code agents & cyber, way more efficient and compact than its Preview version three weeks ago (!) and cherry on the cake: technical report telling its epic backstory. Check it out: https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B/blob/main/assets/technical_report.pdf

Sakana AIシンポジウム：日本から挑む言語モデル・世界モデル・Physical AI 開催レポート https://sakana.ai/symposium-2026/ 10月26日、東京・一橋講堂でシンポジウム「From World Models to Real-World AI」を開催しました。9月にChief Scientific Advisorとしてお迎えしたJürgen Schmidhuber教授の基調講演 と、2018年に教授と論文「World Models」を共著したCEOのDavid Haとの対談に、400名を超える方にご参加いただきました。 基調講演では、甘利俊一氏や福島邦彦氏をはじめとする日本の研究者を含め、世界各地の研究者の功績に触れながら、自身による1990年の世界モデルや人工好奇心の研究まで、いまのAIにつながる流れをたどりました。 また、チーフサイエンティストの秋葉拓哉が、事前学習から自社で開発する言語モデルシリーズ「Sakana Sawara（仮称）」を発表しました。最初のモデルとなる小規模な「Sawara Small（仮称）」は、順調に進めば2027年春に公開する予定です。 Jürgenが思い描いてきたAIのうち、生成AIが実現したのはおそらく半分です。自ら実験を考える人工科学者や、実世界で働くPhysical AIといった残りの半分は、まだスケールに至っていません。その機会は大型ラボ以外にこそ開かれていて、日本はその有望な場所の一つだと考えています。このシンポジウムが、日本の企業や研究機関の皆さんとともに、日本のAIの次の時代を切り開いていく出発点の一つとなれば幸いです。 後日動画も公開する予定です。 ご来場いただいた皆さま、ありがとうございました！

Google’s Gemini 4 Carbon is the new #1 on the Artificial Analysis Intelligence Index v5, and second only to Claude Opus 5.5 on the Artificial Analysis Coding Agent Index Gemini 4 Carbon scores 59 on Intelligence Index v5, driven by leading performance in complex reasoning, knowledge, and scientific tasks. It also has large gains in coding and knowledge work, particularly when compared to other Gemini models, but it is not leading in all these areas. As with launch of Gemini 4 Argon, Gemini 4 Carbon is being rolled out to selected users and is not yet publicly available. Google is offering a 50% launch discount, with no confirmed end date. All our charts and figures use standard pricing for both Gemini 4 Carbon and Argon. Key results for Gemini 4 Carbon with high reasoning: ➤ Gemini 4 Carbon leads the Intelligence Index v5, with the #1 score in 4 of the 9 Index evaluations: HLE-Diamond, Terminal-Bench-Science, AA-Omniscience, AutomationBench-AA. Carbon makes substantial gains elsewhere but is not leading in coding and knowledge work ➤ Behind only Claude Opus 5.5 on coding agents: With Antigravity CLI, Gemini 4 Carbon (high) scores 59 only 3 points behind Claude Code with Claude Opus 5.5 (max, 62) on the Artificial Analysis Coding Agent Index. Carbon ranks second on both Terminal-Bench 4.0 (64%) and FrontierCode v1.1 (51%), behind Claude Opus 5.5 (max) at 56%. Google has historically underperformed in this area and so this improvement stands out ➤ Improved agentic knowledge work, but not yet leading: On AA-Briefcase, Gemini 4 Carbon (high) scores 1609 Elo, a 126-point improvement over Gemini 4 Argon (high, 1483), but still behind models including Grok 4.7 (xhigh, 1638), Muse Wonder (max, 1659) and Kimi K3.1 Pro (1678). The largest gain comes from Presentation, up 293 Elo to 1598, alongside a 120-point improvement in Analytical Quality to 1671 ➤ Lower Cost per Task than Claude Opus 5.5 for comparable overall intelligence: Gemini 4 Carbon costs $7.76 per Intelligence Index task, ~23% less than Claude Opus 5.5 (max, $10.04) but ~1.2x GPT-6 Astra (max, $6.25). It uses 123k output tokens per task, 29% fewer than Claude Opus 5.5 (max, 173k). At the same $4/$20 standard pricing, its Cost per Task is in line with Gemini 4 Argon ($7.68), while scoring 9 points higher on the Intelligence Index ➤ Leading AA-Omniscience v1.1 score, with low hallucination: Gemini 4 Carbon scores 54 on our recently updated AA-Omniscience v1.1, 6 points ahead of Claude Opus 5.5 (max, 48) and 8 points ahead of Gemini 4 Argon (46). Accuracy (% correct) rises 10 points over Argon to 58%, while its hallucination rate rises from 4% to 11%. This is still the second lowest of any model, behind only Argon, compared with 50% for both Claude Opus 5.5 (max) and GPT-6 Astra (max) Key model details: ➤ Context Window: 1M tokens ➤ Multimodality: Text, image, video, and speech input, with text output ➤ Pricing: $4/$20 per 1M input/output tokens, the same as Gemini 4 Argon’s standard pricing, with a 50% discount. Cached input tokens receive a 95% discount ($0.20 per 1M) Congratulations to the @GoogleDeepMind team!