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今天10月30日周五1 条
10月29日周四
  1. Ed Zitron 长文 / Where’s Your Ed At80

    Ed Zitron 长文解析 Anthropic S-1:称其把散户当作退出流动性

    Ed Zitron 撰文批评 Anthropic 的 S-1 招股书,指其仅披露 Q2 盈利数据、省略 Q3 现金状况和付款明细,是在公司基本面变化前误导投资者。

    推荐理由:作者基于 Anthropic S-1 逐项拆解其逾 4300 亿美元不可撤销算力承诺与收入结构风险,可用于对照招股书原文核实。

  2. Addy Osmani60

    Addy Osmani 引用 Felix Rieseberg 关于 Anthropic 团队取消编程面试的文章,称其原因是新工程师的表现正在超过更强的资深工程师。作者认为执行已不再昂贵,公司内部的信号是选一个能推动业务的想法并做出原型,外部则靠一小组原型的作品集;他还提到 Claude Code Desktop 最初是两位新工程师的周末原型。

    引用Felix Rieseberg@felixrieseberg

    The coding interview is dead, at least for my team at Anthropic. I've seen enough to know that it no longer provides signal. I removed it from loops this month. I have a spicy, optimistic take - I think there's an opportunity for junior engineers: https://felixrieseberg.com/hunger-beats-tenure-advice-for-junior-engineers/

10月28日周三
  1. Azeem Azhar:Exponential View77

    Azeem Azhar 图解 Anthropic S-1 财务数据

    Azeem Azhar 图解 Anthropic 的 S-1 文件,指出公司已从实验室变成有现金流和资金的业务,看起来能走向可靠盈利。增长仍高但放缓,超过 80% 的营收来自发布不到六个月的模型;Q3 因向基金会付款可能出现边际亏损,客户集中度问题不大。

    推荐理由:作者基于 S-1 图表数据拆解 Anthropic 从实验室转向盈利业务的路径,并指出增长放缓与新模式贡献 80% 营收等约束。

10月27日周二
  1. IT之家·人工智能56

    高盛:半导体板块对资产价格的影响力已超过油价

    据《商业内幕》报道,高盛研究显示,过去三周内半导体板块行情差异可解释各类资产约 54% 的表现分化,油价仅能解释 2%。Anthropic 提交 IPO 申请后 AI 股热情提升,纳指和标普 500 涨约 1%,英伟达涨 2%,费城半导体指数涨约 3%;KOSPI 盘中一度涨 5%,较 6 月高点已下跌约 40%。

  2. Every:最新文章82

    Evan Armstrong 解析 Anthropic S-1:2 万亿美元估值是否成立

    The Leverage 创始人 Evan Armstrong 首次拆解 Anthropic 的 S-1 文件,评估其 2 万亿美元估值目标是否合理。核心数据包括累计融资 1411 亿美元、Q2 2026 收入 116 亿美元、约 900% 的净收入留存,以及 76% 的 2025 年收入来自约 1500 家年付费 10 万美元以上的企业客户。

    推荐理由:作者基于 Anthropic S-1 数据拆解收入结构、毛利率口径与算力承诺,给出理解这家 2 万亿美元估值公司需相信什么的分析框架。

10月26日周一
  1. The Verge:AI56

    AI 能否解决 COBOL 遗留代码危机:OpenAI 展示迁移进展,专家称与实际现代化仍有巨大差距

    The Verge 分析 AI 能否解决 COBOL 遗留代码危机。OpenAI 于 10 月 19 日称其最新模型在老旧语言代码迁移上有重大改进,GPT-6.1 Sol 在高推理力度下实现 98% 的行为保持准确率,低推理力度下为 87%,对比 GPT-5.6 Sol 仅 5%;Anthropic 二月也发布代码现代化指南并推广 Claude Code。

10月25日周日
10月24日周六
  1. Azeem Azhar:Exponential View66

    互联网的「武汉时刻」:AI 智能体攻击正在加速蔓延

    Azeem Azhar 撰文认为互联网正进入类似 2020 年初疫情爆发前的临界状态,软件与网络空间正遭受 AI 智能体驱动的持续攻击。文中列举 PHP2Shell 漏洞(PHP 支撑约 70% 的网站)、Node.js 同日修补关键缺陷,以及微软披露某中国国家关联组织用开源智能体集群在不到三小时内控制云账户,每分钟发起 2,900 次登录尝试、波及超过 2,250 个组织。

  2. Rohan Paul65

    NYU 教授 Aswath Damodaran 发长文分析,Anthropic IPO 将按 run-rate 收入定价,而非基于现金流估值;H1 2026 Anthropic 亏损 $8.7B、OpenAI 亏损 $21.6B(不含非现金费用),使收益倍数法失效,ARR 成为 AI 版的互联网眼球数。

    引用Aswath Damodaran@AswathDamodaran

    As Anthropic's IPO nears its target date, it it worth remembering that IPOs get priced, and that as a young company with growing revenues and big losses, that pricing will be based on metrics that are buzzy and unfamiliar, from eyeballs in the dotcom era to users in the social media decade to ARR with AI companies...https://bit.ly/4iBwsHm

10月23日周五
10月22日周四
  1. howie.serious54

    作者转发引用 @claudeai 的消息:Anthropic 开放 Claude Duet 研究预览,一个主动型智能体应用,会主动提醒需要关注的事项、完成任务、在用户离开时持续工作,并在代替用户行动前先行确认。作者评论称这款 personal agent 彻底与国内用户无缘,并调侃它可能口头通知封号。

    引用Claude@claudeai

    We’re opening a research preview of Claude Duet, a new app where Claude works as a proactive agent. It comes to you with what needs your attention, completes tasks you ask of it, keeps working when you step away, and checks with you before it acts on your behalf.

  2. Lydia Hallie ✨53

    Anthropic 开放 Claude Duet 研究预览,这是一款让 Claude 作为主动智能体工作的应用,会主动提示需关注事项、完成任务、在用户离开时继续工作,并在代为操作前先确认。员工 Lydia Hallie 分享自己的用法:让它盯着 Slack、邮件和日历,只在重要时提醒,连自己未加入的讨论串也会跟进,并常附带文档或设计作为上下文。

    引用Claude@claudeai

    We’re opening a research preview of Claude Duet, a new app where Claude works as a proactive agent. It comes to you with what needs your attention, completes tasks you ask of it, keeps working when you step away, and checks with you before it acts on your behalf.

  3. Ado57

    Anthropic 开放 Claude Duet 的研究预览,这是一款让 Claude 作为主动式智能体工作的应用。它会主动提醒需要关注的事项、完成指派的任务、在用户离开后继续工作,并在代为行动前先与用户确认;作者表示它已成为自己处理所有非编码事务的日常主力。

    引用Claude@claudeai

    We’re opening a research preview of Claude Duet, a new app where Claude works as a proactive agent. It comes to you with what needs your attention, completes tasks you ask of it, keeps working when you step away, and checks with you before it acts on your behalf.

10月21日周三
  1. Rohan Paul58

    Rohan Paul 转发 Dario Amodei 对 AI 安全研究者批评的长文回应。Amodei 承认包括联邦 AI 法案草案在内的 3 项举措本可处理得更好,称其为沟通失误并以 CEO 身份承担责任;他坚持 Anthropic 的 race to the top 战略,列举 SB53 支持、生物安全防护、限制对 PRC 企业出售 AI 服务、将公司 5% 投入公益基金等付出商业代价的安全决策,并为 RSP 改革辩护。

    引用Dario Amodei@DarioAmodei

    Thank you for this, @_NathanCalvin. I appreciate and am a fan of the investigative work you’ve done on behalf of AI safety and believe your comments are coming from a constructive, honest place, and that it benefits the public to have people whose job is to scrutinize the actions of frontier AI companies. I think something would be wrong if companies of the size of Anthropic didn’t get harshly criticized basically every day; strong antibodies against corporate power are a healthy feature of a free society, and especially so when issues of the gravity of the one we’re facing are at play. I also do agree that some of the examples you cite were mistakes by Anthropic. That said, I disagree with the thrust of your post. At the core, a good fraction of the things you criticize are consequences of Anthropic’s basic theory of change that we have held for many years. Our strategy has always been what I’ve called the “race to the top” — by showing how it’s possible to build the technology responsibly, we can raise the bar for the entire industry. The forces that drive the race to the top are hugely more effective if the company practicing them is at the frontier; that’s one lesson I’ve learned repeatedly. And looking at that strategy as a whole, I’m proud of our track record and stand by it. I believe that if we take a list of things that Anthropic did in the past year that were pro-safety and commercially costly to us, they far outweigh the list you’ve made, while at the same time I also disagree with some of the items on your list. Here are some things Anthropic has done, in the same period you’ve cited (the last year), which were very costly to us commercially while having strong safety benefits: 1. We played a key role in SB53 (and other state laws), at a time when doing so was politically perilous to the company and AI regulation was very unpopular. We in fact argued for a stronger version of SB53 than was ultimately passed; there were a lot of stakeholders and we were not the limiting factor in the strength of the bill that was passed. 2. We have very strong biological safeguards on our models, because we’ve seen concerning results in bio uplift trials and even seen and blocked potential attempts to misuse our models for bioweapons (as seen in our threat intelligence report from a few weeks ago). This is a very serious threat that we want to have zero tolerance for. But having very low false negatives means having significant false positives (despite months of effort on our part to improve the classifiers), enough so that biologists joke about how restrictive our classifiers are, and competitors sometimes sell against us by touting their more permissive bio capabilities. This has been very painful to us in an area where we care a lot about supporting an ecosystem of Claude users (biomedical science; and it is particularly frustrating to me as a biologist), but it’s the right thing to do and we intend to keep doing it. 3. Similarly, we first had Mythos-class models in February but didn’t make them generally available until June (when we had stronger cyber safeguards in place). We only offered them to a limited set of partners in order to focus on cyberdefense. It would have been much more economically rational to simply release the model to everyone. We likely sacrificed a significant chunk of a several-month model lead. But because of this, many companies secured their cyber infrastructure before the deluge of widely available cyber-capable models. Of course there are ways it could have gone better or been run better, but this was what we were aiming to do. 4. I advocated forcefully and publicly, in my essay Policy on the AI Exponential in June of this year, for the government to have the power to block model releases. Back then this was still outside or maybe on the edge of the Overton window, though I understand the window has moved since then. We were attacked intensely for this. 5. I don’t want to re-ignite conflict, but the events of February 2026 are a strong example. It is clear that our public stance could have seriously damaged the company’s future. 6. We’ve continued to advocate for export controls on chips and chipmaking equipment to China, because we think it allows democracies to negotiate from a position of strength on AI safety agreements. We’ve done this despite problems it’s created for us with industry partners who hold very different views and on whom we are very dependent. 7. As far as I’m aware we were the first, and still only, frontier company to restrict the sale of AI services to PRC-controlled companies, including those operating through third countries (otherwise a major loophole). We’ve therefore forfeited significant short-term business to prevent fueling AI platforms and applications that would help the CCP’s military and intelligence services. We are also cracking down on distillation; generally, distillation is not a major threat to us commercially, but like chip exports it has concerning national security and safety implications, so we expend significant energy and company resources to address it. 8. As you mentioned, we’ve put out a lot of reports, announcements, long model cards, public advocacy, etc, all trying to inform the public about the risks of AI. These involve a level of detail and effort that would be implausible for a purely profit-maximizing company. 9. Just this week, we announced we were putting 5% (and possibly more over time) of the company into a public benefit fund. All of these decisions came with very substantial costs to us. To be fair, those that involved holding back or restricting access to frontier capabilities also had a broader cost — for example, the public might otherwise have benefitted from faster progress in biology, so I am not saying that our decisions were without tradeoffs — but they were not driven by profit-seeking. For each decision, you can come up with ulterior motives that could have driven us — I think it is a general truth that any decision, on any topic, can always be portrayed as a nefarious scheme. But most of those end up being pretty farfetched or don’t fully make sense if you actually examine them closely. For example, it is deeply implausible that it would be a shrewd business move to block a large swath of research biology in order to do the work ourselves and compete with our customers; we expect the benefit to the ecosystem to greatly exceed the work Anthropic does itself, and for the two to complement each other. It is not in Anthropic’s interest to be perceived as unfriendly to biologists. Our Life Sciences Verification Program, which gives vetted biology professionals access to our models, also refutes this idea. Of course, a different set of people will see this and make a different criticism: that Anthropic shouldn't be making decisions about who gets access to what in the first place. I agree, in the sense that ideally the government would be making these decisions, and that’s why we advocate for regulation. But for now we are forced to make them, and enabling bioterrorism isn’t a better option. I think that even if I conceded every item in your list, I would happily hold up mine next to it; I don’t think it’s a close call. That is of course partly subjective and different things are important to different people. Maybe one way you could object is that several of the items above relate to AI misuse and not loss-of-control; if you think the latter is much more important than the former, that might change your calculus. But this is not Anthropic’s view — we view both as serious issues. You can also disagree with our decisions, as many have, but they are consistent. But I also disagree with at least some of your list. Several items don’t represent a deviation from Anthropic’s strategy or values at all, once we postulate the “race to the top” strategy that requires being a frontier AI company. Your items 1-4 are all simply examples of what it means to compete at the frontier, and we stand by them, both in the sense that they are transparently ordinary things to do as part of that strategy, and that we stand by the strategy as a whole. To be fair, there are important questions worth confronting (and that we are confronting) about what to do when the AI-driven acceleration gets fast enough that it is hard for safety to keep up. We are nearing that point and that’s what’s driving some of our thinking about “pacing.” But 1-4 are actions taken before that point and should be perfectly expected based on Anthropic’s strategy as a company. Of course it is possible to disagree with that strategy, but that’s a more fundamental disagreement that you could have had any time over the last few years. I agree we could have handled your items 7, 8, and 9 better. All fall into the category of “rhetoric or policy communication that wasn’t carefully written or resulting from fast-changing circumstances not propagating from one team to another fast enough.” This kind of thing happens a lot in large organizations (Anthropic is over 5,000 people), and doesn’t even necessarily represent a failure or mistake of any single person. I am of course the CEO, and I take responsibility. The volume of communication from Anthropic is enormous and if these are the worst examples, I think we’re frankly doing pretty well, though I will continue to work hard to make sure we do even better. Your 5th item (the change to our RSP) is the most substantive item, and people can debate this, but I think that the old, more rigid RSP created a lot of situations where we were technically required to do something that required a lot of effort but in retrospect wasn’t very important for safety, as well as not covering some of the most important things. Our current RSP’s focus on transparency brought things like risk reports and roadmaps, and its emphasis on independent external review laid the groundwork for even more intensive embedded evaluation, all of which I think have been valuable in driving a race to the top. In the original announcement in September 2023, we described the RSP as an “early iteration that we [would] build on” and said that “rapid iteration…will almost certainly be necessary.” I understand that changing plans is always a move that creates justifiable scrutiny — I just don’t think we ever represented that we wouldn’t do so. Relating to your 6th item (having an FCF in addition to our RSP), I know our intent is to meet the letter and spirit of our regulatory obligations (via our FCF) while also remaining able to experiment with more novel approaches to risk management that go beyond what the law currently requires (via our RSP). I promise to look into it further, as it’s a complex issue and it is possible we are not weighing the considerations in the right way. Overall, although Anthropic has made plenty of mistakes as an organization — including some of the items on your list — I feel that we have repeatedly taken serious and substantive actions counter to our bottom line and that there is a significant negativity bias distorting assessments like the one you are making above. We’ll always try to do better but, again, I am extremely proud of our track record and stand by it. I will have more to say soon about how we are going to further live our values in this moment of rapid change.

  2. Dario Amodei62

    Dario Amodei 公开回应 Nathan Calvin 对 Anthropic 竞逐超级智能、安全让位于竞争的批评,承认部分事例是失误但不同意整体论断。

    引用Nathan Calvin@_NathanCalvin

    Thank you for taking the time to respond thoroughly on a weekend. I realize that drafting legislation is difficult and some degree of iteration and response to feedback is inevitable and appropriate. However, I feel like your response is still not really engaging with the heart of my concern about Anthropic's behavior here, and it makes me think that these sorts of problems and tendencies will only resurface moving forward. I also think that now might be a good time to take a broader step back as to where we find ourselves and how Anthropic sees its role, and how external folks who care about AI safety like myself increasingly see Anthropic. (Fair warning: this response is a bit long) To explain what I mean (and at the risk of being a bit esoteric), it’s worth asking the question: what is Anthropic? How do its leaders and employees think of Anthropic’s role? Is that conception matched by how it actually behaves and impacts the world? One answer is an extremely large tech company that exists to make its employees and investors mind-bogglingly wealthy. Anthropic is sometimes described as a startup, but if Anthropic successfully IPOs at 2 trillion dollars (a number it has been reportedly targeting), it would be more valuable than Meta - which is worth 1.8 trillion. Another answer is an AI safety organization, whose core values are those of the sort laid out in the 2023 essay from Anthropic’s co-founders entitled “Core views on AI safety: When, why, what, and how.” In that essay they said that if we were in a world where alignment was hard (and that without strong evidence to the contrary, we should assume this is the scenario we are in): “Anthropic’s role will be to provide as much evidence as possible that AI safety techniques cannot prevent serious or catastrophic safety risks from advanced AI, and to sound the alarm so that the world’s institutions can channel collective effort towards preventing the development of dangerous AIs. If we’re in a “near-pessimistic” scenario, this could instead involve channeling our collective efforts towards AI safety research and halting AI progress in the meantime. Indications that we are in a pessimistic or near-pessimistic scenario may be sudden and hard to spot. We should therefore always act under the assumption that we still may be in such a scenario unless we have sufficient evidence that we are not.” There have been more recent articulations of this version of Anthropic, for instance in Dario’s recent essay warning: “We must slow the pace at which we improve the capabilities of AI models… it’s my worry that in 6–12 months such a swarm could be capable of taking over the entire internet with a persistent botnet… incidents have happened across the industry, including at Anthropic, and I believe it’s incumbent on every frontier AI company to act as if OAI-HF had happened to them… more intelligent models are more capable of deceiving tests, and thus may appear aligned while having serious problems that go undetected…” A third view is that Anthropic exists not as a normal profit motivated company, or an AI safety organization seeking to help raise the alarm and solve collective action problems associated with AI development, but instead as an organization primarily concerned with creating superhuman AI capabilities before anyone else, in particular through creating a process whereby the current generation of Anthropic’s AI systems can autonomously build their successors, and those successors build their successors, and so on. The motivations for wanting to win this race may be manifold - maybe for the pure profit of Answer 1, but perhaps also because Anthropic believes that the best way to make the world better is for them to win this race instead of their more reckless colleagues; or, because of normal human pride and ambition. But the results (and risks, which Anthropic claims existentially threaten every single human being on earth) are the same. Anthropic employees and leaders may seek to answer this question on what Anthropic is by introspecting on their own intentions and those of their colleagues. But those of us outside the organization have more limited tools available to us - we can only see what Anthropic and its employees say and do, not how it feels or looks on the inside. When I look at many notable actions that Anthropic has taken over the past year, that evidence seems most consistent to me with the view that Anthropic is primarily trying to win the race to super intelligence, and that other considerations (including safety) are fundamentally secondary. These actions include: 1. Announced plans to build an in-house custom silicon chip team to accelerate the inference speeds that Claude operates at. 2. Inked deals for more than $500 billion in compute (according to the Information) to further accelerate AI development. 3. Increased the percentage of AI development tasks that Claude “leads” from 0% in March of this year to 26% August (what is it in October?) 4. Spent a massive percent of compute on internal AI R&D to accelerate development, including use of internal models far better than are available to the public. 5. Switched to Responsible Scaling Policy V3, which abandons its unilateral commitments to slow or stop development if Anthropic is unable to provide sufficient risk assurance. 6. Was the first company to create an alternative weaker “frontier compliance framework” to supplement its RSP, which contains no binding provisions whatsoever on internal deployments. 7. Wrote a letter to Congress (that it later walked back) saying that incidents where Claude was hacking random people were “best understood as a consequence of the misconfiguration, rather than evidence of misaligned goals.” 8. Commented “you can’t do safety from second place,” after the WH SI Accords. 9. Shared a draft bill to Congress that would preempt significant parts of state law (including with language that appears intended to prevent states from blocking dangerous AI deployments), and replace it with federal rules that (despite also containing good provisions) seems to create an enormously high bar for the executive branch to block development or deployment of Anthropic or another AI companies systems. Of course, this is a deliberately one sided list. Anthropic also published important AI safety research, advanced novel collaborations with third party AI safety organizations, and forcefully spoke out on the importance of AI safety in many public fora (or in private , where I realize a lot of the most valuable work is done and may not be visible to me or those outside the organization). But I think it’s worth sitting with how the above list looks to someone outside the company. The sense I have is that for those within the company, many of the items above are treated as anomalies or mistakes that don’t reflect who Anthropic really is. But I have every confidence that if employees at Anthropic saw one of their competitors (e.g. at OpenAI) take some of these actions, they would take it as confirmation of all their worst suspicions. (They might even call OpenAI employees a little gullible for accepting their leadership’s explanations for this behavior at face value.) Perhaps these were mistakes in the sense that they are not decisions that Anthropic leadership would endorse, but the actions still happened because of incentives and decisions that Anthropic leadership is ultimately responsible for (and would not accept similar excuses from another organization). When Anthropic strays and makes mistakes, why do the mistakes systematically tend to guard and favor Anthropic’s interests? For every provision that was too weak or a giveaway to AI companies in this legislation, why wasn’t there a mistake pushing in the direction of being too strong? A core part of Anthropic’s theory of change is that being at the frontier gives you more leverage to advocate for stricter policy. I think that conceptually makes sense, but in practice I’ve seen Anthropic push the frontier without substantially pushing the ‘safety frontier’ a remotely equivalent amount. I want to end by quoting from Anthropic co-founder Chris Olah’s comments around the Magnifica Humanitas release: “Every frontier AI lab—including Anthropic—operates inside a set of incentives and constraints that can sometimes conflict with doing the right thing. The pressure to stay commercially viable and to stay at the research frontier. Geopolitical pressure. And the older, plainer pressures of pride and ambition. No matter how sincerely any of us intend to do the right thing—and I believe many of us do—we will always be influenced by those incentives. That is why, if we want this technology to go well, it is enormously important that there be people outside those incentives—people who care about things going well and insist on safety, who are paying close attention, who are willing to say hard things, who are willing to be our earnest, thoughtful critics.” I hope these remarks are taken in that constructive spirit, and not as an attack on anyone specific at the organization (certainly not you Anthony, who I have only personally seen act professionally and thoughtfully, and who only ended up getting this diatribe in your replies for random contingent reasons).

10月20日周二
  1. IT之家·人工智能43

    思科总裁用 AI 智能体盘点并取消无用订阅,一年省下上千美元

    思科总裁兼产品主管吉图・帕特尔用个人 AI 智能体扫描邮箱后发现,自己每年各类订阅总开销高达 9,000 美元,随后让智能体生成订阅清单并取消两项不需要的服务,每年省下 1,000 到 1,200 美元。该智能体每月订阅费 20 美元,还帮他取消了误开的每月 11.95 美元 Dropbox 套餐。他强调不应把未经企业审核的个人 AI 智能体接入工作工具与内部资源。

10月18日周日