Google DeepMind@GoogleDeepMind · 2月27日

We’re launching Nano Banana 2, built on the latest Gemini Flash model. 🍌 It’s state-of-the-art for creating and editing images, combining Pro-level capabilities with lightning-fast speed. 🧵

译我们推出 Nano Banana 2，基于最新的 Gemini Flash 模型构建。🍌 它在创建和编辑图像方面达到最先进水平，将专业级功能与闪电般的速度相结合。🧵

Saining Xie@sainingxie · 12月23日

not getting into a philosophical debate, but this book really changed how I see the topic and made me feel more humble. human intelligence is impressive, but calling it ‘general’ isn’t very objective. my cat would disagree. to me human intelligence is better seen as socially driven cognitive adaptations, and there’s a huge WORLD of intelligence we still don’t understand, and are nowhere near recreating with current AI

译不想陷入哲学辩论，但这本书确实改变了我对这个话题的看法，让我更加谦逊。人类智能令人印象深刻，但称其为"通用"并不太客观。我的猫会不同意。 在我看来，人类智能更应被视为社会驱动的认知适应，而且我们仍不理解、也远未用当前 AI 复现的智能领域还有巨大 WORLD。 [引用 @demishassabis]：Yann 在这里完全错了，他把通用智能和 universal intelligence 混淆了。 大脑是我们在宇宙中所知最精致、最复杂的现象（迄今为止），而且它们实际上极其通用。 显然，没有人能规避 no free lunch theorem，因此在实际且有限的系统中，总是必须围绕正在学习的目标分布有一定程度的专门化。 但关于通用性的要点在于，理论上，在 Turing Machine 的意义上，这种通用系统的架构能够在给定足够时间和内存（以及数据）的情况下学习任何可计算的东西，而人脑（和 AI foundation models）是近似 Turing Machines。 最后，关于 Yann 对国际象棋棋手的评论，人类竟然能发明国际象棋（以及现代文明的所有其他方面，从科学到 747s！），更不用说像 Magnus 这样的人能下得如此出色，这本身就令人惊叹。他可能不是严格最优的（毕竟他有有限的记忆和有限的决策时间），但考虑到我们的大脑是为狩猎采集而进化的，他以及我们能用大脑做到这些，实在令人难以置信。

Demis Hassabis@demishassabis · 10月7日

Excited to share early results about CodeMender, our new AI agent that automatically fixes critical software vulnerabilities. AI could be a huge boost for developer productivity and security. Amazing work from the team - congrats!

译CodeMender 是一款可自动修复关键软件漏洞的 AI agent，早期成果显示其有望大幅提升开发者生产力与安全性。

Google DeepMind@GoogleDeepMind · 10月2日

How can AI enhance the creative process of a world-renowned industrial designer? 🎨 We partnered with the visionary @RossLovegroveX and @modem_works to build a tool using Gemini and our image generation technology to translate his signature aesthetic into a new concept. 🪑

译Google 携手工业设计师 Ross Lovegrove 与 modem_works，利用 Gemini 及图像生成技术构建工具，将其标志性美学转化为全新家具设计概念。

Jeff Dean@JeffDean · 10月1日

The proof is in the evolutionary pudding!

译Google Research 利用 AlphaEvolve 迭代进化代码，自动生成可自动验证的复杂性理论证明元素，展示进化算法在数学证明发现中的应用。

Noam Brown@polynoamial · 9月28日

Julian was co-first author on AlphaGo, AlphaZero, and MuZero. He doesn't have a major twitter presence, but he's been at the forefront of AI exponential progress for more than a decade.

译AlphaGo、AlphaZero 和 MuZero 共同一作 Julian Schrittwieser 指出，公众对当前 AI 指数级进步普遍认知不足。他发布博客总结近期研究进展，并预测未来 1-2 年的发展趋势。

Demis Hassabis@demishassabis · 9月24日

Important updates to our Frontier Safety Framework, with expanded risk domains for advanced AI and refined assessment protocols.

译Google DeepMind 实施 Frontier Safety Framework 最新更新，扩展先进 AI 风险领域覆盖，完善评估协议，作为识别与预防新兴风险的最全面方案。

Google DeepMind@GoogleDeepMind · 9月22日

As we build increasingly powerful AI models, we’re committed to responsible development. We’re implementing our latest Frontier Safety Framework – our most comprehensive approach yet for identifying and staying ahead of emerging risks. Find out more → http://goo.gle/3W1ueFb

译正在实施最新的 Frontier Safety Framework，这是识别和提前应对新兴风险最全面的方法，确保在开发更强大 AI 模型时领先于潜在威胁。

Jeff Dean@JeffDean · 9月18日

Very excited to see our Gemini models getting better and better at coding! An advanced version of Gemini 2.5 Deep Think at the 2025 International Collegiate Programming Contest (ICPC) World Finals achieved gold-medal level performance! 🎉 https://deepmind.google/discover/blog/gemini-achieves-gold-level-performance-at-the-international-collegiate-programming-contest-world-finals/

译Gemini 2.5 Deep Think 高级版本在 2025 年 ICPC 世界总决赛中取得金牌级别成绩，标志着 Gemini 模型编程能力持续精进，在竞赛级编程任务中表现卓越。

Demis Hassabis@demishassabis · 9月12日

Helping to improve human health is one of the most important uses of AI. Insightful discussion with @TomMackenzieTV on Bloomberg Tech Europe of our great progress @IsomorphicLabs designing new drug candidates for challenging targets. https://www.bloomberg.com/news/videos/2025-09-12/bloomberg-tech-europe-9-12-2025-video

译IsomorphicLabs 在为挑战性靶点设计新候选药物方面取得重大进展。团队在 Bloomberg Tech Europe 与 Tom Mackenzie 深入探讨了 AI 在改善人类健康方面的应用，强调这是 AI 最重要的用途之一。

Saining Xie@sainingxie · 8月29日

good question... thinking back to pre-LLM interviews I experienced (before 2019)… they were all in-person on-site, no chance of ''llm cheating,'' very different across places, and somehow way more memorable. > old deepmind had brutal ''quizzes'' -- 2-hour marathons with 100+ math/stats/ML concept questions. > meta FAIR was basically academia interview with a bit of coding, but the highlight was chatting vision research with piotr, ross and kaiming. > google brain/research was similar. the @NoamShazeer was my coding interviewer, who kindly kept it simple with just a two-pointer q. we spent most of the time discussing research, where I explained how I had applied something called a transformer to visual data (point clouds) -- a topic that, at the time, hardly anyone cared about. > but the coolest? openai in 2018: whiteboard coding, a research talk, and a *~5-hour* session in a tiny room to work on an RL problem (variance collapse in cross entropy methods). I knew almost nothing about RL, but that was the point. They handed you a self-contained problem description, handwritten by @johnschulman2, and expected you to learn, research, solve, write up in a notebook, and present. feeling a bit nostalgic. makes me wonder if interviews like that still happen anywhere. If they do, I’d love to know. :)

译好问题...回想起我经历过的前 LLM 时代面试（2019 年之前）…都是现场面对面，没有「LLM 作弊」的可能，各个地方差异很大，而且不知怎的更令人难忘。

Google DeepMind@GoogleDeepMind · 8月22日

Why make explorable, AI generated worlds? @ShlomiFruchter and @JParkerHolder explain how creating diverse and challenging virtual environments can help test and train AI agents safely. 🦺 Watch their conversation about Genie 3 with podcast host, @fryrsquared ↓ Timecodes: 00:00 Coming up 00:54 Intro 02:00 What is Genie 3? 03:00 Demos 06:50 Physics 11:00 Possible scenarios 15:07 Emergent properties 20:35 Veo and Genie 25:00 Hunter's lodge 28:02 Memory 34:52 SIMA and Genie 3 39:13 Searching for interestingness 52:00 AGI and the future 59:23 Hannah's thoughts

译Google DeepMind 研究者 Shlomi Fruchter 与 Jack Parker-Holder 在播客中解析 Genie 3：通过生成多样化、可探索的虚拟世界，为 AI 智能体提供安全的测试与训练环境。对话涵盖物理模拟、涌现特性、与 SIMA 结合及 AGI 前景等议题。

Google DeepMind@GoogleDeepMind · 8月14日

On the road to AGI, @DemisHassabis believes breakthroughs like Genie 3, which can generate playable worlds, could help us better understand reality itself. 🌐↓

译Demis Hassabis 表示，在通往 AGI 的进程中，Genie 3 这类能够生成可玩世界的技术突破，将帮助我们更深入地理解现实本质。

Jim Fan@DrJimFan · 8月5日

This is game engine 2.0. Some day, all the complexity of UE5 will be absorbed by a data-driven blob of attention weights. Those weights take as input game controller commands and directly animate a spacetime chunk of pixels. Agrim and I were close friends and coauthors back at Stanford Vision Lab. So great to see him at the frontier of such cool research! Congrats!

译Google DeepMind 发布世界模型 Genie 3，支持从文本生成交互式世界，实现 720p 分辨率下 24fps 实时交互与数分钟一致性。作者认为这代表"游戏引擎 2.0"——未来 UE5 等复杂引擎的层级结构将被数据驱动的注意力权重取代，直接根据手柄输入生成像素时空块。

Noam Brown@polynoamial · 7月22日

Congrats to the GDM team on their IMO result! I think their parallel success highlights how fast AI progress is. Their approach was a bit different than ours, but I think that shows there are many research directions for further progress. Some thoughts on our model and results 🧵

译向 GDM 团队 IMO 成绩表示祝贺，认为这种并行突破印证了 AI 进步之快。GDM 方法与我们的不同，但这恰恰证明存在多种研究方向。后续将分享关于我们模型和结果的想法。

Ilya Sutskever@ilyasut · 10月10日

And congratulations to @demishassabis and John Jumper for winning the Nobel Prize in Chemistry!!

译并祝贺 @demishassabis 和 John Jumper 获得诺贝尔化学奖！！