搜索“Anthropic”

Adrian Sanborn Sep 24, 2026 46 4 1 Share What does the future of science look like in the world of AI? Anthropic has some lofty goals for science and is even opening a wet lab . Meanwhile a quiet transformation 1 is happening all across AI x Science. In this guest post, Adrian Sanborn talks about the less flashy but more immediate ways he sees AI transforming front-line scientific research in his own company, Endura Therapeutics. Adrian did a CS PhD at Stanford and spent much of it running exper

匹配字段正文

ls Oracle, or even my Hater's Guides To the SaaSpocalypse, Private Credit, and Private Equity. If you want to get in touch — and especially if you have any juicy information about Anthropic, OpenAI, or any other companies in the AI bubble — hit me up on Signal at ezitron.76. I’m also on IB on your Bloomberg Terminal. Soundtrack: Flobots - Handlebars A few months ago, I asked where all the data centers were, because I was struggling to find proof that very many were being finished despite all the

匹配字段正文

做用户想要的事。这对软件工程师来说太棒了。他们希望自己的东西做那件事，而且它越可预测，他们就越不需要测试和摆弄它。Jeb 还远没到那个程度。它可以做到，但就像，我们想要多得多的可靠性九数，才能让它好到像数据库查询一样，你甚至都不用去想它。它就在那里，当你需要智能的时候。但安全对齐，就像，是指令遵循的反面。它是当你想要遵循别人的指令时，比如 OpenAI 和 Anthropic Swyx [00:14:13]：RAG 的价值栈。 Diogo Almeida [00:14:14]：正是。而这对一个产品来说非常合理。再说一次，就像，ChatGPT 应该这么做。你——你应——就像，如果他们不想，比如，跟 ChatGPT 搞什么不适合工作场合的角色扮演，那是他们的事，因为，就像，也许那正是他们那些有父母和孩子的用户想要的。就像，那没问题。但在 API 里，那太疯狂了，对吧？就像，那完全不可接受，因为，就像，人们需要，就像，围绕这个来编程，而那太反用户了，以至于它。它。我。哈。我可能是个容易生气的人，所以我应该试着冷静下来。 Swyx [00:14:52]：这，人们能感受到你的热情，我觉得这非常好

匹配字段正文

K3 , some of the latest, leading Chinese models, have enacted a step change in the commercial viability of open models — crossing a similar threshold in agentic capabilities that Anthropic’s Claude Code crossed in December of 2025. America was the early leader in open language models, primarily through Meta’s Llama models, which were used extensively across research and commercial tasks. Chinese open-weight models surpassed American open-weight models in these two key areas about 18 months ago.

匹配字段正文

Jev’s launch on Wednesday , and they have completely taken over the timeline, with 36M views of their launch video (by comparison, OpenAI’s Navier Stokes result got 74M views, and Anthropic’s Fable 5 got 57M views) in just two days. Vercel @vercel Jev was adopted faster than any other model in AI Gateway history. In the first day, @typesafeai reached 13% of teams, 2x the GPT-5.6 family and 6x Fable 5.1. 10:34 PM · Sep 18, 2026 · 21.3K Views 15 Replies · 18 Reposts · 220 Likes It wasn’t open sour

匹配字段正文

expertise. It also helps you adapt to change because deep knowledge makes it easier to switch from being someone who does the work to someone who manages it. And recent work from Anthropic suggests that expertise also shapes the quality of what AI gives back . Experts not only get better work out of AI, they get more work out of it. But you don’t just need deep knowledge, you also want wide knowledge. The training data for LLMs is a large swath of humanity’s vast output. The AI has learned some

匹配字段正文

this support would be limited and on a project-by-project basis. Though there are few details on what such a program could look like, we drew inspiration from the Google-Broadcom-Anthropic-Apollo TPU structure to surmise how deals could be structured. In the TPU backstop structure, if Anthropic is unable to continue to service lease payments to the TPU SPV, then the structure can be resolved by Broadcom assuming the lease or by the racks being sold. If the racks are sold, then the residual valu

匹配字段正文

s at the frontier. (Or a broad swathe of data, at least. RL environments give you mid-training data for free, so the argument is the same either way.) The reasoning is as follows. Anthropic can distill Sonnet 5 and Opus 5 from Mythos, and they can do it on logits. Kimi K3 and GLM 5.3 can at best do token distillation off the frontier models’ outputs. And yet Kimi K3 and GLM 5.3 are the better models. The naive read is that distillation just isn’t worth much. An alternative reading is that distil

匹配字段正文

previously took several steps and occasional intervention. One extract below: Extract of an analysis I ran with Fable 5.1 But Astra really is very good—and mostly cheaper than the Anthropic alternative. On difficult math problems, Astra’s time horizon is 30.9 minutes vs 3.6 minutes for GPT 5.6 Sol. Mathematician Bartosz Naskręcki says : “For a mathematician it feels like finally we arrived in the era where we can focus entirely on the ideation and exploration”. Real-world demos show a capability

匹配字段正文

it won’t be long until the same is true for every other organization in the world. At the same time, it’s become abundantly clear that access to frontier models is at the mercy of Anthropic, OpenAI, and the United States government. Fable 5 was temporarily banned by the USG, and GPT 5.6 and Astra were similarly delayed. Both models have cyber, bio, and other safety safeguards that, though well-intentioned, often prevent good users from completing harmless tasks. Given recent security incidents a

匹配字段正文

ation infrastructure of these AI companies is about to have tens if not hundreds of thousands of extremely superhuman hackers constantly bombarding it. If the next training run at Anthropic or OpenAI is about to happen, not only would maybe rogue instances of Mythos or Astra or whatever have an incentive to interfere with it… Other AIs who have some reason to inject some part of themselves into this training or manipulate it in some way, who are just externally roguely deployed, would also have

匹配字段正文

The AI industry is begging for a slowdown. Maybe we should listen? Casey Newton This is a column about AI. My fiancé works at Anthropic. See my full ethics disclosure here. By now I’ve written enough about the OpenAI agents’ autonomous attack on Hugging Face that saying more smacks of piling on. OpenAI acknowledged it had a problem, undertook an investigation, and last week announced a series of changes it is making to its research infrastructure, testing, and monitoring in an effort to improve

匹配字段正文

ly whether the answer was right. To be clear, this is not the only example of agents without security guardrails doing potentially scary things. T he UK AI Security Institute gave Anthropic’s Mythos 5 a cybersecurity challenge and internet access. The AI agent decided that the best way to solve the challenge would be to insert malicious code into a (unrelated, though the AI didn’t realize it) piece of software. It submitted malicious code as part of a bug fix to that software, realized that an a

匹配字段正文

odels for free….The price looks insane until you see who Nvidia is defending against.Its biggest customers are all building escape routes. OpenAI is designing chips with Broadcom. Anthropic trains on Amazon’s Trainium. Google has run its own TPUs for a decade. The labs writing Nvidia the largest checks are the ones working hardest to stop.” — Aakash Gupta; “Every day i read about some chip that is superior to Nvidia. And every year i see no real competitors” — Jim Cramer; “Here is another exampl

匹配字段正文

how AI will soon displace the first few rungs on the career ladder — and why she left Big Tech to do something about it Casey Newton This podcast touches on AI. My fiancé works at Anthropic. See my full ethics disclosure here. Three months ago, we began our podcast miniseries by asking how likely artificial intelligence is to take large numbers of jobs. Our first guest, Box CEO Aaron Levie, argued that mass disruption would be highly unlikely. And several subsequent guests, from Amazon Web Servi

匹配字段正文

ith background agents followed. By January of this year, just two months after the v2 launch, around 60% of PRs at Ramp were authored by Inspect, which increased to 75% by May. At Anthropic, Claude Code won rapid adoption after an internal release, as covered in the deepdive How Claude Code is built. Then Inspect hit a neat milestone in July, crossing the one million total sessions mark: 2. Why build your own background coding agent? There are a few reasons why Ramp decided to turn down tried-an

匹配字段正文

stood out this week — one on AI‑safety norms, one on a genuinely novel clinical application. Zhipu published research that a Chinese cybersecurity specialist framed as an answer to Anthropic’s Project Glasswing, described as marking a shift in how Chinese labs approach AI‑safety disclosure. (SCMP); A Chinese brain‑reading AI model reportedly can help predict depression risk up to four years in advance — one of the more concrete medical applications to come out of a Chinese lab this year. (SCMP)

匹配字段正文

Dan Shipper on doubling headcount while automating everything, building an agent out of 30,000 copyedits, and the “dirty secret” of writing with AI Casey Newton My fiancé works at Anthropic, whose models Every reviews and builds on, and which comes up below. Earlier in our miniseries on productivity in the AI era, Replit's Amjad Masad described a "self-driving company" where most engineers don't look at the code anymore. For our penultimate episode, I wanted to visit someone running a version of

匹配字段正文

ble reasoning effort, but reviews were mixed: strong gains in cybersecurity and coding, “underwhelming” elsewhere. DeepSeek Harness, MIT-licensed and explicitly positioned against Anthropic’s Claude Code, is the bigger tell: DeepSeek is chasing the agentic-coding wars, not just benchmark leaderboards, and it’s willing to charge higher prices to fund it. (Bloomberg/Reuters/Nikkei Asia/The Information) Meta has unwinded its $2 billion Manus deal, and Tencent stepped in to become the AI agent start

匹配字段正文

rite one up when it will not count toward academic tenure. AI models are different. Even an uninteresting negative result can be useful, provided it is labeled. Earlier this year, Anthropic put a version of this to the test. The company pulled 129 decision points from real Claude Code sessions between January and March 2026, showed models the work up to a human detour, and asked what should happen next. Claude Mythos Preview beat the human choice 64% of the time, while Opus 4.5 managed 51%. The

匹配字段正文