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Thinking Machines - Inkling Thinking Machines Lab, the company founded by Mira Murati, has released Inkling, its first open-weights model under the Apache 2.0 license. Inkling is a mixture-of-experts transformer with 975 billion parameters in total, yet only 41 billion of them are active for any given token. Every layer contains 256 routed experts and 2 shared experts, and a router selects just the 6 most relevant experts per token. This means that only about 4 percent of the model performs computation during inference. The backbone is a 66-layer decoder-only transformer that combines local and global attention layers and supports a context window of one million tokens, which is roughly enough to fit eight novels or an entire codebase into a single prompt. The model was pretrained on 45 trillion tokens spanning text, images, audio, and video. Instead of relying on separate vision or audio encoders, it converts images into patches and audio into discrete tokens, then projects everything into one shared hidden space. All modalities are therefore fused from the very first layer. Inkling accepts text, images, and audio as input, while its output remains text only. On public benchmarks, it performs at the level of GPT 5.6 Sol and Claude Fable 5 in reasoning and agentic coding. The weights are available on Hugging Face, and the model can be fine-tuned through the Tinker API. #MiraMurati# #thinkingmachines# #inkling# #OpenSource#
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Thinking Machines发布Inkling:Mira Murati团队的首个开源多模态大模型 975B总参数、激活41B的MoE架构,Apache 2.0协议,支持文本、图像、音频输入,输出文本。 跑分处于开源第一梯队中上游,HLE带工具46.0%、SWEBench Verified 77.6%、GPQA 87.2%,与Kimi K2.6、DeepSeek V4 Pro同档,距离闭源模型还有差距。 这是首个1T参数级别的开源多模态模型,且支持在自家Tinker平台做微调定制。 模型:
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Mira Murati 自离开 OpenAI 以来首次接受全面采访,首次详尽披露了她在 AGI 初创公司 Thinking Machines 实验室正在打造的项目。 这位前 OpenAI 首席技术官阐述了她对未来的愿景:人类与 AI 将更紧密地协作 ——"就像双人自行车"—— 并且随着机器能力的提升,人类不会被排除在决策循环之外。
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I’ve left Google DeepMind. The last two years have been an incredible whirlwind. A couple years ago, I joined a small startup called Codeium. There, I got to ship Windsurf, train SWE-1 (a frontier agentic coding model), go to DeepMind in the $2.4B acquisition. Now, I decided to leave the acquisition money and DeepMind. I’m grateful to the mentors, teammates, and friends I worked with along the way. At Windsurf, thanks to @_mohansolo and Douglas Chen, I got to see what a fast moving startup that ships relentlessly and builds for the future looks like. I learned from @thenickmoy how excellent research leadership can drive outsized innovation. At DeepMind, I got to push the frontier of agentic coding, be part of the amazing team that shipped Antigravity and contributed to Gemini 3. DeepMind is a rare place: deeply curious people, exceptional research taste, and access to enormous compute and Google-scale infrastructure. A few things that I learned: 1. Finding the right hill to climb. Now more than ever, there are a multitude of directions to push the frontier in AI research. It’s easy to optimize for the wrong benchmark or capability. You should step back regularly to question if you are climbing the right hill, and adjust course often. 2. The secret to being a fast-moving team. Moving quickly is not just about working hard and long hours. It requires making concrete bets about where the world will be in 6 months, aligning around them, and cutting everything else. This was our journey from the Codeium Extension → Windsurf IDE → SWE-1 → Antigravity → Antigravity CLI 3. Silicon Valley is small. Since the split of Windsurf to DeepMind and Cognition, many of my colleagues have gone to other exciting places - Thinking Machines, OpenAI, xAI, Cursor, fast-moving startups, or started their own companies. I’m grateful to have worked with so many talented, hungry people whose stories are not yet finished. So what’s next? We are living in one of the most exciting and powerful times in human history. Just like we transformed software engineering, soon every industry, every unit of work will be radically transformed, democratized, accelerated. With this comes new challenges, and new doors of frontier research to be opened. More soon.
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你应该在 Twitter 上关注的 30 个与 AI 相关的账号: 英文: @karpathy,Andrej Karpathy,Eureka Labs创始人,OpenAI早期成员,前Tesla AI负责人,擅长把神经网络、LLM、Agent讲到普通工程师也能听懂。 @fchollet,François Chollet,Keras作者、ARC-AGI提出者,Ndea和ARC Prize联合创始人,长期讨论AGI、抽象推理和「智能到底是什么」。 @ylecun,Yann LeCun,图灵奖得主、CNN/深度学习代表人物,NYU教授,前Meta首席AI科学家,现在做AMI,长期主张开源、世界模型和非纯LLM路线。 @AndrewYNg,吴恩达, Fund、Landing AI创始人,Coursera联合创始人,AI教育和AI落地应用领域最有影响力的人之一。 @rasbt,Sebastian Raschka,LLM研究工程师、作者,写过《Build a Large Language Model From Scratch》,适合看模型原理、训练细节和代码实现。 @dair_ai, Engineering Guide背后的项目,适合看prompt、context engineering、agent相关资料。 @lilianweng,Lilian Weng,Thinking Machines Lab联合创始人,前OpenAI研究与安全VP,Lil’Log作者,agent、RL、AI安全综述写得非常系统。 @jeremyphoward,Jeremy Howard, @simonw,Simon Willison,Datasette作者、Django联合作者,长期追踪LLM工具、开源生态、prompt injection和AI Agent安全问题。 @_akhaliq,AK,AI论文信息流账号,机器学习背景,主要快速转发新论文、新模型、新项目,适合跟踪前沿动态。 @ID_AA_Carmack,John Carmack,id Software创始人、前Oculus CTO,现在在Keen Technologies做AGI,典型硬核工程派。 @gwern,Gwern Branwen,独立研究者和长文作者,写AI scaling、心理学、统计学、理性主义和长期主义相关内容。 @goodside,Riley Goodside,最早出圈的prompt engineer之一,曾在Scale AI和Google DeepMind,常发模型行为、prompt技巧和AI产品边界测试。 @drfeifei,李飞飞,Stanford教授、World Labs联合创始人兼CEO,ImageNet关键推动者之一,长期做计算机视觉、空间智能和human-centered AI。 @demishassabis,Demis Hassabis,Google DeepMind联合创始人兼CEO,AlphaGo、AlphaFold背后的核心人物之一,2024年诺贝尔化学奖得主。 中文: @dotey,宝玉,中文AI圈非常重要的信息源,长期翻译和整理LLM、Prompt Engineering、Context Engineering、AI工程实践内容,也会分享很多一手产品和技术判断。 @op7418,歸藏,AIGC周刊主理人,关注AI、LLM、AI图像视频和设计,适合追踪新工具、新模型和AI创作玩法。 @xiaohu,小互,中文AI新闻和工具资讯号,主打全球前沿科技、AI动态,也做小互AI日报社群。 @WaytoAGI,通往AGI之路,中文AI知识库和社区型账号,适合系统性补AI资料、工具、教程和行业信息。 @Khazix0918,数字生命卡兹克,AI自媒体和热点监控型账号,做了AIHOT这类AI热点监控网站,适合看中文AI圈正在炒什么、什么值得跟。 @Gorden_Sun,Gorden Sun,稳定更新AI资讯日报,适合当每日AI新闻索引看。 @FinanceYF5,Will,偏AI资讯和行业数据整理,会做AI网站流量、产品数据、行业观察,适合看数据型信息差。 @vista8,向阳乔木,关注LLM、Prompt、效率工具和AI产品落地,内容偏实用观察和产品判断。 @shao__meng,meng shao,关注上下文工程、AI智能体、企业AI落地和AI培训,也经常整理中文AI领域账号合集。 @oran_ge,橘子,前MiniMax AI工具产品负责人, @hanqing_me,汗青,AI Talk创始人,重点在AI短视频、AI数字人、AI艺术和内容创作方向。 @jesselaunz,遁一子,关注AI资讯、AI实际应用和Prompt探索,偏实践派,适合看普通人怎么把AI用起来。 @thinkingjimmy,JimmyWong, @xicilion,响马,西祠胡同创始人、老程序员,分享LLM实战、工程判断和开发者视角,对AI工具链的理解比较硬。 @AI_Jasonyu,鱼总聊AI,关注AI、出海、创业、独立开发和副业方向,经常整理AI博主、工具和产品机会。 有哪些我漏掉了?欢迎补充
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