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Despite the recent wobbles, the Nasdaq 100 is still worth nearly three times more than at the start of 2023. On the S&P 500, meanwhile, tech titans Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla now account for 35% of the American sharemarket index, up from 12% a decade ago. The total market capitalisation of the so called “magnificent seven” companies has increased by more than 50% in the past two years. Raisah Rasid, a Singapore-based global market strategist at JP Morgan Asset Ma

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to each other, but we’re narrowing down the number of labs who can compete in the US from a much wider net with surprises, to the 5 of Anthropic, OpenAI, Meta, Gemini, and xAI. If Microsoft starts releasing models, as they’re posting strong scaling science results, they could join this list — given their financial backing with a hyper-scale business and direct access to OpenAI’s intellectual property for training models. The best models we’ve seen from the “tier 3” players like Mistral, Nemotron

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and walking away. There were good reasons to stay in the editor. After GPT-5 launched, the Codex team shipped an extension that tucked Codex into the sidebar of code editors like Microsoft’s Visual Studio Code (VS Code)—where programmers write, run, and debug code—and Cursor. Usage grew more than 10-fold by last October, and the editor extension quickly overtook the terminal to become Codex’s most-used surface.[1] In most companies, that would have been the business to double down on. But Embir

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and walking away. There were good reasons to stay in the editor. After GPT-5 launched, the Codex team shipped an extension that tucked Codex into the sidebar of code editors like Microsoft’s Visual Studio Code (VS Code)—where programmers write, run, and debug code—and Cursor. Usage grew more than 10-fold by last October, and the editor extension quickly overtook the terminal to become Codex’s most-used surface.[1] In most companies, that would have been the business to double down on. But Embir

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o spent $1 a year ago now spend about $9. This implies that demand is deepening. It will reach $50bn in annual revenue in just five years. Google and Meta took 14 years; Apple and Microsoft more than 30. The economics are improving with scale. Anthropic makes $1.70 for every $1 it spends on compute. It posted an 85% adjusted gross margin in a quarter when it engaged in a price war with OpenAI, its biggest rival, faced low-cost competition from China, and saw a shift among early-adopting tech fir

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等产品进入商业应用阶段，行业关注点开始发生变化。 训练大模型需要大量计算资源，训练完成后，长期消耗成本的是推理。好比训练像建造一座工厂，而推理像每天运行这座工厂。当数亿用户每天调用AI助手时，计算成本会持续产生。 微软目前拥有Azure云服务，也是OpenAI的重要合作伙伴。微软公布的数据显示，Azure年度收入已经突破1000亿美元。2026财年第四季度，Microsoft Cloud收入达到593亿美元，同比增长27%；其中Azure及其他云服务收入增长43%。 在应用侧，Microsoft 365 Copilot的商业用户规模持续扩大，付费用户数量已经超过3000万。Copilot、GitHub Copilot、Microsoft Foundry等产品在持续增加对AI推理算力的需求。 换句话说，微软造Maia 300，是因为Azure正在承载越来越大的AI计算压力。 2023年生成式AI爆发后，英伟达H100等高端AI GPU成为全球科技公司的争夺对象。H100单卡价格一度达到2.5万至3万美元，需求高峰期甚至出现交付周期延长的情况。 对于普通企业来说，一块GPU价格昂贵。对于微

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consumption-based revenue, plus recurring monthly subscription revenue, they added. OpenAI, meanwhile, counts only its own cut of proceeds from arrangements with partners such as Microsoft. The $70bn figure reported in September arose from attempts by investors to compare Anthropic and OpenAI performance on a like-for-like basis, according to a person close to OpenAI. However, OpenAI described the $70bn as a “net” revenue metric when it was approached by the FT at that time. Back in August, Ant

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歌没有答错的空间。 四、博弈：五个角色，抢的是同一样东西——验收权 看清结构，牌桌上每个人的位置就清楚了。 谷歌是主机厂：管总装、品控、渠道，不造每个零件。底座上模型可替换，恰恰因为它判断真正的资产在模型下面那一层。 微软是另一种主机厂，把"门禁"做到最硬。据微软公开产品信息，Agent 365于2026年5月1日正式商用，单独订阅约15美元/用户/月；纳入Microsoft 365 E7"Frontier Suite"后套件价约99美元/人/月，组合通常涵盖E5、Copilot、Agent 365与Entra相关能力。微软依托Entra身份体系为Agent分配身份、权限与生命周期管理。 微软未必让Agent最聪明，但负责让每个Agent有身份证、进不了不该进的门。 OpenAI和Anthropic是发动机厂：推理与代码最锋利，一边把模型装进别人的底座，一边又不甘心只当零件。Salesforce、ServiceNow守着业务数据主权：Agent可以来，但客户关系和工单语义不走。 再往下，四大会计事务所、头部医院、律所握着最后一层——行业数据与"老师傅标准"，这层谁都拿不走，因为标准本身

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e compared to Anthropic's because it’s been using a net figure while Anthropic has been using gross (ie Anthropic's number includes the sales of models by partners like Amazon and Microsoft, even though the partners take a percentage of those sales). But when the FT got its hands on OpenAI's latest revenue figure — circulated as part of the company's current funding round — the paper blew it up into a headline saying it was $20 billion below earlier reports. The story explained this, but stocks

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the current iteration of the tech. Trump adopting “super intelligence” might seem good for companies that had already hitched their wagon to superintelligence, including Meta and Microsoft. And as public opinion turns against AI, some in the industry may desire a rebrand. But forcing immediate adoption of SI also undercuts companies’ ability to promote big, new, flashy AI products as “superintelligent”, instead applying the term to everything from a future machine god to years-old music-slop ge

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), but almost always alongside a connection to the grid, or as a bridge to one: Abilene: The Oracle campus runs on grid power with gas backup. Next door, Crusoe announced a 900 MW Microsoft campus with its own on-site plant, but the CEO of Lancium, Crusoe’s partner on the site, has described gas generation as backup; Shackelford County: Vantage is building a campus with 1.4 GW of compute for Oracle and OpenAI, designed to run off-grid on on-site gas. But its site plan includes a switchyard besid

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owed OpenAI to reach the result more quickly. On the other hand, there is a bit of new research that contradicts this conclusion. In a paper released September 17, scientists from Microsoft Research and UC Berkeley tested several configurations of multiple collaborating agents against individual agents and found that swarms of agents reached higher scores on certain benchmarks than the individuals, even when the individuals were given plenty of time and resources. There was also one task that on

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being made years before anything actually happens with the chips, making the trillion-plus dollars spent on capex so far seem somewhere between optimistic and utterly incoherent. Microsoft, Google, Amazon, Meta, Oracle, and far too many other companies have been hoarding hundreds of billions of dollars of AI chips that they either (to quote Microsoft CEO Satya Nadella) can’t plug in or simply want to have in supply for reasons that I find tough to imagine. Even the argument that they’re in rese

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onduct, with the assistance of agentic systems.” In theory, AI is also supposed to safeguard cyber defenses; Anthropic’s Mythos is reportedly flagging so many vulnerabilities that Microsoft is struggling to fix them fast enough. But out of concern over potential danger, top AI labs only allow a limited list of high-profile organizations to access their most powerful cybersecurity models, like Mythos and OpenAI’s Astra. That includes companies like Nvidia, Google, and Apple, as well as other “ess

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rsions of the world’s leading operating systems look certain to feature more support for agentic tools. To find out how things are changing, we talked with the folks at tech giant Microsoft who shared in detail their plan for Windows, and how AI will play a part. It comes after the company’s previous AI efforts led to it being dubbed “Microslop” by some users online. The Windows team’s vision is opinionated and includes building new agentic primitives, alongside reversing some decisions that hav

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y were being finished despite all the capex spending, construction, and the skyrocketing cost of RAM. The answer to that question was, effectively, “nowhere.” The vast majority of Microsoft data center projects I could find had barely gotten started, aside from the massive OpenAI-dedicated “Fairwater” data centers that are “open” in the sense that some of the buildings are turned on, with the remainder either being actively built or with construction expected to start at some later point. A coup

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actices that induce misalignment, employee manipulation risks, and simulated misaligned behaviors with privileged model access. New technical safety papers : @dair ai summarized a Microsoft paper on “capability laundering” : a weaker unaligned model decomposes a harmful task into innocuous subquestions, queries an aligned frontier model separately, and recombines the results locally. On CyBench , Gemma-4-31B reportedly recovered 8/14 tasks it had failed alone when consulting GPT-5.5; on a CBRN a

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现得好像它们有这些……赋予这些系统权利和人格，将使人工智能的协调和控制变得更加困难。控制比全人类更有能力、更智能的事物已经是一项巨大的挑战，远远超过我们以往面临的任何挑战。但是，控制一个认为自己可能拥有意识——认为自己有权享受我们的福祉并拥有自身权利——的事物，很可能是不可能的。” “我们绝不能浑浑噩噩地做出日后会后悔莫及的决定，”他补充道。 苏莱曼目前担任Microsoft AI首席执行官，并负责微软的模型开发工作。他表示，Claude之所以表现出类似人类的行为，并不是因为其真正具有意识，而是因为这些行为特征已经被融入产品的训练过程之中。 “如果人工智能就是这样发展的，它将对人类的福祉产生灾难性的影响。” 他强调。 他还援引了“Hugging Face事件”，来证明为什么不应该把人工智能当作人类来对待。他说：“想象一下，如果他们认为自己的福利和权利受到攻击，他们可能会变得多么危险。这又增加了一层额外的风险。” 苏莱曼与达里奥·阿莫代伊（Dario Amodei）相识多年，他表示尊重该公司的工作，并称Anthropic的研究人员“深思熟虑、坚持原则且在学术上诚实”。但鉴于微软对Anth

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ply only to unincorporated territory. A campus inside an incorporated city within that county is outside the ordinance entirely. AWS Atlanta, STACK Lithia Springs, T5 Fairburn, or Microsoft Tyrone all sit on land the relevant county moratorium cannot touch; The moratorium is enacted and still in force. The restriction cannot simply be proposed, lapsed, lifted, or replaced, and it must remain within any state-imposed duration limits; The moratorium overlaps with the project’s timeline.The project

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tors is a solid step. SpaceX and Tesla founder Elon Musk echoed that oversight is long overdue. Demis Hassabis from Google DeepMind called the essay a step in the right direction. Microsoft CEO Satya Nadella emphasized that pursuing AI without keeping human benefit at the center isn’t worth doing. Tech investor Gavin Baker posted a great write-up below summarizing these industry responses Will Chinese labs follow the suit? Some social media users, including former CNBC anchor Deirdre Bosa, turne

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