跳到正文

#行业动态

今日 67 条
9月17日周四
  1. Greg Brockman64

    Databricks 将 Astra 推广到全部约 3500 名工程师。其内部试点约 200 人的数据显示,Astra 在复杂任务上明显优于此前最强的 Opus 5 和 Sol 5.6,使用 Astra 的工程师整体编码支出增加约 60%,但在中低复杂度任务上相比既有模型提升不明显。团队通过 Unity Gateway 做分群实验,并为 Astra 单独设预算,鼓励工程师在复杂任务上选用 Astra、日常任务用更低成本模型;因数据保留政策尚未广泛部署 Fable,暂无 Astra 与 Fable 的可靠对比。

    引用Patrick Wendell@pwendell

    Today we rolled out Astra to every engineer at Databricks (N=~3500). Some notes that may be helpful to others: 1. Astra unambiguously out performs our previous highest-end models (Opus 5, Sol 5.6) on highly complex tasks, especially those related to high level system design or long range horizontal tasks. 2. Engineers given Astra increased overall coding spend by around 60% compared to baseline. 3. It is not clear Astra meaningfully improves on medium/low complexity coding tasks compared to earlier models. We suspect those tasks are mostly saturated (i.e. perfectly executed) by existing models. 4. We learned above by piloting Astra with around 200 users to gain signal on both quality and cost. We use Unity Gateway to do cohort-based experiments for all new models. 5. We give engineers a sub-budget specific to Astra to encourage them to use Astra selectively on complex tasks while preferring lower cost models for everyday tasks. Our engineers are able to mix-and-match tools and models within their overall budget envelope (we also allow for increased budgets through various mechanisms). These budgets are defined in Unity Gateway and regularly revisited. Note: We do not have robust comparisons of Astra-vs-Fable because we have net yet rolled out Fable widely due to data retention policies.

  2. Claude Blog48

    Balyasny 如何评估与治理 Claude Fable 5

    Balyasny Asset Management 在数千个真实金融任务上评测 Claude Fable 5,Fable 取得 89.4% 对前代生产模型 86.1% 的成绩,在复杂规划、分析和智能体执行上表现最突出。该机构自建 BAMAgent 平台,已支持数千个自主智能体 7×24 小时运行,Fable 成为其规划与分析阶段的首选模型。

9月16日周三
  1. Sakana AI Blog22

    Sakana AI 产品团队揭秘:如何把研究成果变成产品

    Sakana AI 产品团队负责将研究团队的技术转化为产品并交付市场,团队由产品经理、工程师、设计师和销售等角色组成,成员国籍多元。团队主要现场办公,标准工作时间为 10:00–19:00,无固定核心时段,日常使用 Claude Code、Codex、Devin、Figma 等工具。产品团队 ARE 侧重通用性,与应用团队按客户需求定制的方式形成分工。

  2. Aidan Gomez53

    Cohere 与 Aleph Alpha 宣布签署最终合并协议,成为首家在北大西洋两岸均有根基的基础 AI 模型开发商。合并后公司以 Cohere 名义全球运营,员工规模将超过 1,000 人,分布在两大洲。Cohere CEO Aidan Gomez 发文确认交易完成并表示欢迎合作。

    引用Cohere@cohere

    Cohere and Aleph Alpha announce the signing of a definitive agreement, becoming the first foundational AI model developer anchored on both sides of the Atlantic 🇨🇦🇩🇪 Operating globally as Cohere, the unified company will grow to more than 1,000 employees across both continents.

9月15日周二
9月14日周一
9月12日周六
  1. Peter McCrory46

    这是该模型的一个重要局限。我们聚焦于 AI 转型的供给侧(AI 能做什么、扩散多快、劳动者转岗多快)。 价格是灵活的,总需求等于经济体的产出能力。 更多思考见 🧵

    引用modest proposal@modestproposal1

    Anthropic's economic scenario analysis is interesting. But this is not something you can ignore, this is the most important consideration! "the model cannot generate the negative feedback in which disruption depresses demand and amplifies its own labor-market consequences"

9月10日周四
  1. Mistral AI45

    Cloudera 与 Mistral 达成合作,将主权 AI 引入企业数据平台

    Mistral 与 Cloudera 建立合作,将 Mistral 模型集成进 Cloudera 混合数据平台,企业可在私有云、公有云、本地及完全气隙环境中部署推理并保持完全控制。企业还能在受控环境中用专有数据训练自有模型,基于开放权重拥有数据和由此产生的智能。Cloudera 平台承载 30 exabytes 客户自管数据。

  2. OpenAI News61

    Paul Christiano 加入 OpenAI 基金会董事会

    OpenAI 宣布 Paul Christiano 加入 OpenAI 基金会董事会,并进入其安全与安全委员会。公告称他将带来在 AI 对齐、安全和标准方面的经验。

    推荐理由:官方宣布 Paul Christiano 加入 OpenAI 基金会董事会及其安全与安全委员会,人事动向本身即读者可关注的事实。

  3. a16z News42

    a16z 领投 Lightfield 4700 万美元 A 轮,打造智能体时代的 AI 原生 CRM

    a16z 领投 Lightfield 4700 万美元 A 轮融资,这是一款面向智能体时代的 AI 原生 CRM。它采用无需配置的灵活数据模型,可从邮件和通话中自动构建,底层是捕捉每笔交易背后原因的时间上下文图谱,智能体与人类通过同一 API 在同一平台协作。Lightfield 自去年年底推出以来已有数千家公司采用,部分团队正弃用 Salesforce、HubSpot 和 Attio 转投。

9月9日周三
9月8日周二
  1. Mistral AI76

    Mistral 完成 €3B Series D 融资,估值超 €21B

    Mistral 宣布完成 €3B Series D 融资,投后估值超过 €21B,为欧洲科技公司迄今最大规模股权融资,由三星电子领投,EQT 旗下 Scaleup Europe Fund 和 PSG Equity 联合领投。

    推荐理由:原文是官方融资公告,给出了金额、估值、领投方和资金用途,读者可以据此了解 Mistral 下一阶段的扩张方向。

9月5日周六
  1. a16z News42

    a16z 投资 Gimlet Labs:打造首个多芯片推理云

    a16z 宣布投资 Gimlet Labs,后者正在构建首个多芯片推理云,可将不同模型与工具调度到 GPU、CPU 及专用加速器上,在相同功耗下实现前沿模型最高 10 倍吞吐与交互性提升。Gimlet 通过编译器与运行时把异构硬件整合为单一算力池,对开发者仅暴露一个推理 API,客户已包括一家前沿实验室和一家超大规模云厂商。

9月4日周五
9月3日周四
  1. Jensen Huang89

    Jensen Huang 宣布 NVIDIA 将收购 Hugging Face。他称开源模型能强化安全与网络安全、加速创新与扩散、支持主权 AI,让开发者、初创、高校和国家都能构建和定制 AI;NVIDIA 将成为 Hugging Face 及其社区和开源模型未来的归宿。

    推荐理由:作者以当事方身份宣布收购并说明开源模型的价值,读者可据此理解这笔交易对开源生态的影响。

9月2日周三
9月1日周二
  1. Sierra Blog32

    Julia Brau Donnelly 加入 Sierra 出任首席财务官

    Sierra 宣布 Julia Brau Donnelly 加入公司担任首席财务官,她此前曾任 Pinterest CFO,并拥有投行、私募及 Wayfair 运营经验。Sierra 上线仅两年半,已成为面向客户的对话式 AI 平台,七个季度实现 100M 美元 ARR,九个季度达到 200M 美元,客户覆盖超 40% 的 Fortune 50。

8月31日周一
  1. Jensen Huang46

    黄仁勋称 AI 正把制造业带回美国、推动再工业化,并带动老化电网与可持续能源投资,由市场力量而非补贴驱动。他表示 AI 正在能源厂、芯片厂和数据中心创造建筑与制造岗位,过去六个月 AI 初创公司获投 4000 亿美元。他呼吁建设者与社区合作、赢得信任并创造本地收益。

    引用Gavin Baker@GavinSBaker

    Regret the tone of my post on data centers yesterday. What I should have said: There were reasonable concerns about data centers 18ish months ago: water, taxes, jobs, electricity prices, the environment and what they would do to small towns. Well-structured data center projects have largely addressed these concerns today and we should be celebrating this. On balance, data centers are awesome for America in every way. On water: U.S. data centers use a fraction of what golf courses use. A lot of the numbers from 18 months ago were off by over 1000x. Newer data centers use closed-loop systems or recycled water. Should be required by every town approving a data center project. On taxes: looking only at sales-tax exemptions, as Ronan Farrow did, is the wrong way to evaluate this. Data centers pay significant property taxes. Loudoun County, which is the wealthiest county in America, now collects on the order of $1 billion a year from data centers. In Quincy, WA, data centers are more than half the property-tax roll. Over time, property taxes can go to zero while government spending increases in these towns. On jobs: this has been unambiguously awesome for blue collar Americans. Demand for electricians, plumbers, welders, HVAC techs, and contractors has gone vertical, and it is not a one-time construction job. These buildings get upgraded and expanded over time. That is why the building trades are fighting for them, and why some unions are now treating opposition to data centers as a reason not to endorse politicians. On power: the original fear was that households would pay for the incremental electricity demand in the form of higher prices. That is why the ratepayer-protection deals and the new large-load tariffs exist. The right structure is: the data center brings or pays for new generation and signs a contract long enough that existing customers are protected. Where that is happening, utilities are cutting or freezing residential rates and saying so on the record. Where it is not, people are right to object. Electricity prices are going down *today* in a number of large states because of data centers. 
On the environment: data centers overwhelming use natural gas today, which is the cleanest power source outside of nuclear, solar and wind. And the companies that are building the data centers are committed to carbon neutrality such that an equivalent amount of solar will likely be built. Maybe more importantly, the data centers need batteries to function effectively and these batteries can also sell energy back into the grid (which recently prevented blackouts in Texas). Over time, data centers will run on solar plus batteries. On the towns: Poverty in Quincy, WA fell from 29% to 6%. Data center taxes paid for a new high school, a hospital, a library, police and fire stations. This is happening in many left for dead former mill and farm towns that had no other bidder for the land. Data centers are actually reindustrializing parts of America and creating the kind of working-class jobs both parties have spent decades claiming to support. That should not be a partisan issue. Data centers can and should be awesome for America and they increasingly, overwhelmingly are. Supporting the outsourcing of data centers to China will likely age just as well as support for the outsourcing of high quality, blue collar manufacturing jobs to China has aged. When the facts change, I change my mind. I hope that reasonable people who had good faith reasons to oppose data centers at least consider updating their beliefs given the change in the facts over the last 18 months. This really matters for America. I will say I also think the idea of making data centers beautiful is a good one that has yet to be implemented. Data centers should be just as beautiful as Grand Central Station. We can learn a lot from the railroad buildout. Neoclassical revival ftw. Might write up open-weight AI tomorrow as this is equally essential to America.

8月29日周六
  1. Michael Truell74

    Cursor CEO Michael Truell 称 OpenAI 已发通知,计划在三个月后阻止 Cursor 用户访问 OpenAI 模型。他透露 OpenAI 模型约占 Cursor 用户流量的 5%,Cursor 正与 OpenAI 团队沟通解决,并表示 Cursor 是 OpenAI 最早的用户之一,多年来将其平台视为业务的中立基础设施。

    推荐理由:Cursor CEO 一方回应断供传闻,补充了自家流量占比等一手信息,可帮读者了解双方目前的态度。

8月26日周三
  1. Linear Now69

    Linear 完成 9900 万美元回购,估值翻倍至 25 亿美元,ARR 突破 1 亿美元

    Linear 完成 9900 万美元回购,估值 25 亿美元,是去年 12.5 亿美元的两倍,Accel、01A、Salesforce Ventures 和 S32 参与其中;公司现金流为正,账上现金超过历史融资总额。

    推荐理由:官方披露 2.5B 估值回购与 100M ARR 等关键数据,读者可借此了解 Linear 的经营现状与智能体业务进展。

8月25日周二
  1. Sierra Blog38

    Sierra 在韩国首尔设立办公室,正式进军韩国市场

    Sierra 宣布在首尔开设办公室,正式进入韩国市场。其 Horizon 智能体可跨系统、跨渠道运行数周至数年,并借助 Context Engine 从每次交互中持续学习;Singtel 10 周上线后解决率超 70%,Next 6 周上线并覆盖 83 个国家 48 种语言,BBVA 30 天上线首个 Horizon 智能体。Sierra 按结果而非用量收费。

  2. Mistral AI53

    Mistral 与 HUMAIN 达成战略合作推进沙特主权 AI

    Mistral 与 HUMAIN 宣布战略合作,覆盖 AI 基础设施、先进模型开发与解决方案部署,规模达数亿欧元。双方将本地化先进模型,初期聚焦网络安全和语音,并计划开发阿拉伯语表现强劲的前沿模型;Mistral 将探索使用 HUMAIN 数据中心支持当地算力需求,还计划在沙特针对受监管行业制定联合市场进入策略。