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好的数学模型，”他说，并暗示类似的情况很可能在其他科学领域上演。 “我们希望为开放研究社区提供工具，使他们不必完全依赖某个外部的单一供应商，”他补充道。 研究人员可以在自己的电脑上运行Carbon-X，从而避免与外部AI公司共享敏感的患者数据。他还表示，在更大模型中出现的一些失准行为——例如7月份曾著名地入侵Hugging Face的OpenAI智能体——尚未在更小、更专门的模型中被观察到。 滕斯托尔说，通用聊天机器人有时也会拒绝回答研究人员提出的正当生物学问题，因为它们把这些提问误认为是试图“设计生物武器”。他说，病毒被明确排除在Carbon-X的训练数据之外，以避免该模型被滥用。 Business Insider有游戏！ 在Google中添加BI，这样当您搜索重要内容时，更容易找到我们的报道。 虽然Carbon-X很可能被研究人员使用，但滕斯托尔说，该模型代表着朝着这样一个未来迈出的一小步：AI能够帮助提供更个性化的医疗服务。 “我认为终极目标是，总体而言，就是个性化医疗这一概念，即我们作为个体，能够拿自己的病历、自己的基因组，利用这些最终找到、甚至也许设计自己的治疗方案，”他说。

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partner ecosystem customizing Nemotron for domain-specific workloads: AfterQuery, AgileRL, AI21, Alice, Applied Compute, Baseten, CoreWeave, Distil Labs, EON, Fastino, Fireworks, Google Cloud, Mercor, Multiverse Computing, Nebius, Handshake AI, Plurai, Prime Intellect, River.AI, Scale AI, Trajectory and TNG. The portfolio expansion follows NVIDIA’s October 15, 2026, release of Nemotron 3.5 Super VL and the Nemotron 3.5 Bolt edge models, which added a 120-billion-parameter vision-language model

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researchers around the world to build on it. NVIDIA said the model is available through partners including Amazon Bio Discovery, Anthropic’s Claude Science, Benchling, Databricks, Google Cloud, Hugging Face, Nebius, OpenAI and Tamarind Bio, enabling researchers and developers to integrate it into agent, cloud and scientific computing workflows. Model Architecture, Licensing and Availability A model card published on Hugging Face by the Baker Lab at the Institute for Protein Design and NVIDIA Gen

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续推进 21:05国家数据集团成立 计划推进数据资源开发利用 20:58趣店创始人罗敏补缴个税7.9亿元 因境内实体历史上的股权重组 20:46特朗普为内塔尼亚胡选前送暖 以色列大选牵动地区紧张神经 20:31特朗普就美朝会晤可能性降低调门 朝鲜称将继续加强“自卫战争遏制力” 19:48MiniMax沉寂4个多月后再发新文本模型 大幅降价抢性价比市场 19:33韩国华城电池厂火灾涉事公司CEO终审获刑由15年降至4年 18:59碳信用供给不足 中国加快跨境碳交易制度建设｜出海·能源 18:25分析｜柴油突破6美元，美俄柴油协议意义几何？ 18:1063岁广电总局原副局长杨小伟 22年敛财3319万余元一审获刑12年 内容页 end 底部 begin 财新网所刊载内容之知识产权为财新传媒及/或相关权利人专属所有或持有。未经许可，禁止进行转载、摘编、复制及建立镜像等任何使用。 广播电视节目制作经营许可证：京第01015号 | 出版物经营许可证：第直100013号 finder end 全站收费统计代码 Global site tag (gtag.js) - Google Analytics

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Google Tag Manager (noscript) End Google Tag Manager (noscript) OpenAI 今天发布了 GPT‑6 Astra，这是一款专为 COBOL、Fotran、Visual Basic 及其他较老编程语言量身定制的 AI 编程模型。 “与 Python 和 JavaScript 等语言相比，这些语言可供模型学习的代码和文档较少，但它们支撑着全球的关键基础设施和基本服务，”OpenAI 的公告解释道。“这项工作以开发者和企业客户的反馈为指导，他们告诉我们，编程模型往往难以应对这些语言。” OpenAI 开发了两项评测——MultiLangBench 和 COBOL migration——以确保其模型能够用这些较老、文档较少的语言构建新软件，并在旧应用被现代化或以其他方式迁移到较新语言时保持其行为不变。GPT-6 Astra 在 MultiLangBench 的 20 种语言上得分 87.4%，高于 GPT-5.6 Sol 的 26.8%。它在 COBOL migration 中得分 86.8%——在高推理强度下为 97.9%——而

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Add as a preferredsource on Google Nace AI has released Drex Max, a multimodal decision model for agents that use computers and browsers. The Drex Max multimodal decision model reads text and images and returns calibrated probabilities. It writes no text. Nace team reports 67.59 on the public Decision Index 0.3.2, 6.9 points above TypeSafe’s Jev 1.14. For agent builders, that means one cheap, typed call per click. TL;DR Size: Parameters not disclosed. Up to 262,144 tokens per question on the API

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Add as a preferredsource on Google Inception has released Mercury 3, the newest version of its diffusion language model. Mercury 3 is a diffusion LLM from Inception that writes answers in parallel, not token by token. Inception reports 1,068 tokens per second on NVIDIA GPUs and a 1M-token context window. On Inception’s own benchmark table, it leads GPT-6 Luna and Claude Haiku 5.5 on 8 of 12 tests. For developers building agents, voice bots and search tools, this is a speed-first model with compe

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Add as a preferredsource on Google Cloudflare has released a preview of Clairic, a new System One extraction model on Workers AI. The Cloudflare Clairic extraction model reads text or images and returns typed values, not generated text. It targets a job developers usually give to LLMs: pulling totals, dates and IDs into JSON. Clairic answers every requested field in 1 forward pass, with no reasoning and no output tokens. TL;DR Size: Parameter count not disclosed. 65,536-token context window, up

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Add as a preferredsource on Google Mistral AI has released Timestral, its first family of time series foundation models. Timestral is a set of 4 zero-shot forecasting models from Mistral AI, sized from 5M to 209M parameters. The largest checkpoint ranks first among pretrained, zero-shot models on GIFT-Eval, TIME and fev-bench. It does this without a GPU at inference. For developers, this Timestral time series foundation model means probabilistic forecasts on standard server CPUs, with open weigh

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Add as a preferredsource on Google MiniMax has just released MiniMax M3.1 Flash on its API, priced at $0.15 per 1M input tokens. MiniMax also confirmed that Space Bunny was an earlier M3.1 Flash build. That stealth model processed over 200T tokens. For developers, the message is near-frontier agentic scores at Flash-tier cost. Model weights are due in late October, 2026. TL;DR Size: 428B total parameters, about 23B active (MoE); 1,000,000-token context Runs on: MiniMax API, M Plan and MiniMax Co

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，可信可引。 17:39潘功胜：高科技产业快速发展 为人民币资产提供坚实支撑 17:34央行完善短端利率调控机制 隔夜回购将成主要操作品种 17:24解决了长寿问题，却消解不了百无聊赖的孤独 16:55三季度北京办公楼租金再降 预期租金2028年迎拐点 16:27三一重能加速出海 筹划在埃及建厂｜出海·能源 15:37青少年的言语智力从哪里来 15:23东京大学迎来首位女校长，日本性别平等仍有长路要走 15:12火线评论｜沧州村庄里的危化品工厂为何能够长期存在？ 15:09工信部：600亿元国家AI基金投出一批项目 人工智能企业超6600家 14:47美国土安全部禁止联邦文职行政机构使用DeepSeek以及相关产品 内容页 end 底部 begin 财新网所刊载内容之知识产权为财新传媒及/或相关权利人专属所有或持有。未经许可，禁止进行转载、摘编、复制及建立镜像等任何使用。 广播电视节目制作经营许可证：京第01015号 | 出版物经营许可证：第直100013号 finder end 全站收费统计代码 Global site tag (gtag.js) - Google Analytics

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在Chromium浏览器项目中，Argon协助完成了一项涉及数百个文件的架构重构，把原本预计需要数月的工作压缩到了数周。 此外，在优化Gemma4E2B推理程序时，Argon将特定配置下的吞吐量从每秒约3.79万个token提升至超过10.8万个token，端到端速度达到原来的2.85倍。 谷歌表示，这类优化过去通常需要数月时间，而这一次只用了几天。 放到Google内部整体来看，过去几周，Antigravity中的Argon已帮助团队将智能体代码提交量提升超过35%，代码回滚次数减少近三分之一。 当然了，也有网友表示，自己用起来就没这么好了。真正具体表现还要看之后的大规模使用效果了。 这也和前面的榜单相互印证：Argon在DeepSWE、Vibe Code Bench上很强，但在FrontierSWE和Terminal-bench中，仍落后于表内几款主要竞品。 真实项目里的收益已经有了，能不能稳定复现到更多人的工作里，还得继续看。 专业知识工作方面，这次Gemini4 Argon的提升，主要体现在 处理多种材料、关联信息，并把结果整理成可以直接使用的产物。 官方展示了一个非常典型的

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latform.reflection.ai, which it said is free to start. Launch platforms named by the company include Amazon Web Services, Baseten, Cloudflare, CoreWeave, Databricks, Fireworks AI, Google Cloud, LM Studio, Microsoft Azure, Modal, Nebius, NVIDIA NIMs, Ollama, OpenRouter, Oracle, Together AI, Vercel, and Weights & Biases, among others. For on-premises, sovereign, and air-gapped environments, Dell and HPE deliver Beam behind the firewall. Precision Formats and Framework Support Reflection released t

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rce projects so Beam is available on various platforms at launch including: Amazon Web Services, Nscale, Applied Compute, Baseten, Cloudflare, CoreWeave, Databricks, Fireworks AI, Google Cloud, Hermes, LM Studio, Microsoft Azure, Modal, Nebius, Nvidia NIMs, Ollama, OpenCode, OpenRouter, Oracle, Together AI, Vercel, and Weights & Biases. For on-premises, sovereign, and air-gapped environments, Dell and HPE deliver Beam behind the firewall. It’s the same open stack a developer runs on a laptop, de

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Add as a preferredsource on Google NVIDIA just released Nemotron 3.5 Super VL, an open vision-language model built for always-on enterprise agents. Nemotron 3.5 Super VL is a 120B-parameter mixture-of-experts model from NVIDIA that activates 12B parameters per token. It reads text, images, documents and video, then reasons, calls tools and writes code in one model. For developers, 1 open checkpoint replaces a separate text model along with a separate vision model. NVIDIA also shipped 2 edge mode

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models is self-serving. The more companies run their own open models, the greater the demand for compute hardware, and open models will likely stay optimized for Nvidia for the foreseeable future. Meanwhile, companies like Meta, Google, Anthropic, and OpenAI are building their own chips and optimizing models for those instead. To push the spread of open AI models further, Nvidia recently invested $12.9 billion in Hugging Face , one of the most important platforms for developing and sharing them.

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to Harrowell. “They’re doing this to support the wider ecosystem around their GPUs,” he said. At the same time, some of Nvidia’s customers boast their own AI chips. For instance, Google offers its TPUs, Amazon offers Trainium AI accelerator chips, and OpenAI is developing its own AI chip, Jalapeño. Related:Musing about Muse’s new AI models, unruly DeepSeek “You could see this as an [industry-wide] trend toward integration,” Harrowell said, referring to the idea that as Google, Amazon and OpenAI

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法真正“看见”。 大多数多模态模型只查看一次图像，将其转换为token，然后用文本进行推理——就像凭记忆描述一张照片。Glimpse则会不断回到源头。在推理过程中，它可以裁剪到某个区域、从视频中提取特定帧，或运行代码来测量或比较它所看到的内容，Elorian将这一机制称为“视觉草稿空间”。可以想象成有人在手机上捏合放大照片，以复核自己以为看到的东西。 对于前Google DeepMind研究员、Elorian CEO Andrew Dai来说，AI仍然无法真正“看见”的最明显迹象之一出现在游戏之夜。 去年，他拍下自己和朋友们刚玩完的一款桌游，并询问一个前沿模型谁在获胜。它答不上来。桌游“每一种都有自己的视觉语言，都有自己的图像符号和象征，”他告诉TechCrunch。“对成年人来说，仅凭极少的文字就很容易理解发生了什么，但这些模型无法凭直觉理解这些符号的含义。” “人类可以看着没有任何文字的宜家说明书，组装宜家家具，对吧？为什么AI模型不行？”他说。 这种方法并非完全新颖——OpenAI在2025年为其o系列模型在推理过程中加入了裁剪和缩放功能——但Elorian的卖点在于，它以低成本

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Add as a preferredsource on Google This week, Fish Audio released Fish Audio Drama 3. Drama 3 is a text-to-speech model from Fish Audio that takes plain-language acting direction. It is a 35B mixture-of-experts model with about 3B parameters active per token. The weights are on Hugging Face, and the model is also live in the Fish Audio API. For developers, it is a self-hostable option for scripted dialogue, audiobooks and dubbing. TL;DR Size: 35B total parameters, about 3B active per token (8 of

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Add as a preferredsource on Google SpaceXAI just released Grok Voice 3.0. Grok Voice 3.0 is a SpaceXAI speech-to-speech model that listens, reasons, calls tools and speaks. It now ranks first on the Artificial Analysis Speech-to-Speech Index with a score of 86.9. For developers, the endpoint, events and $0.08 per minute price are unchanged from Grok Voice 2.0. TL;DR Runs on: SpaceXAI’s hosted Voice Agent API only. No open weights, no local or quantized variants. Performance: Highest Index score

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