Michael Kaiser retweeted
Oh my GOD Kimi K3.1 is Broken
One shot fully working 3D Train with speed slider, assembly / exploded views, wireframe and stat tracking
Wtf is going on with these Chinese models, this feels design wise similar to a GPT model but just has that something extra like Anthropic models on top
Michael Kaiser retweeted
Claude Code 2.1.306 is now available.
2 CLI changes
Highlights:
• Fixed claude -p reporting 'Not logged in' in cloud sessions without env vars, restoring login status
• Fixed API errors being replaced by 'prompt is too long' in MCP-heavy sessions, showing original API errors
More details in thread ↓
Dario Amodei replied publicly to Nathan Calvin's critique of Anthropic. He agreed some examples "were mistakes by Anthropic," but rejected the thrust and defended its "race to the top" strategy, citing costly safety moves like backing California's SB53.
#Anthropic
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.
This is just the beginning.
Anthropic will continue pursuing biology heavily.
The teams at Anthropic are fairly segregated, with each working on different fronts. The life sciences team may not know what another team is working on, but they’re all pursuing separate research goals.
Every team is going to be asked how they can help Anthropic reach half a trillion dollars in revenue.
There’s some low-hanging fruit: GLP-1s, peptides, disease treatments, etc.
Expect to hear many more lab updates this year.
Michael Kaiser retweeted
ICYMI, meet Panels. These are mini-apps that live on your Home page. They're completely custom, so you can build whatever you want in about 2 minutes.
Connect Strava to build out your running plan, Chase for budget tracking, or Shopify to keep an eye on your purchases. They have whatever you need at a glance.
Michael Kaiser retweeted
こんにちは、Rody です。10 月 31 日に、渋谷の Google オフィスで、Antigravity Deep Dive というイベントをやります。午前に Google Antigravity の話をして、午後はみんなで何か作ってみたいです。日本のエンジニアがどんなものを作るのか、見るのを楽しみにしています。
cloudonair.withgoogle.com/ev…
やばすぎwww
OpenAIのResponses APIに、プロンプトキャッシュの最低保持期間を12時間にする選択肢が追加!毎回使う長い指示や資料が同じなら、数時間空いても読み取りの割引料金を活用しやすくなる。
🧠 対象はGPT-5.6以降。同じ先頭部分を再利用し、最低1,024入力トークンが必要
⏰ 標準の30分に加え、長い間隔で使う共通文脈には最低12時間を選べる
💰 12時間の書き込み総単価は通常入力の2.5倍。読み取りはモデル別の割引料金なので、得になるかは再利用回数次第
12時間は削除期限ではなく、キャッシュ読み取り料金の対象となる最低期間。毎回の高速化を保証するものでもありません。
朝の分厚い業務マニュアルを、午後も使い回す設計ができるのはデカい。ただし一度しか読まないのに長期キャッシュを選んだら、節約のつもりが豪華な保管料コースになるやんw
#OpenAI #AI開発
Michael Kaiser retweeted
网课、讲座存了一堆,真正从头看完的没几个?有个开源的 agent 技能,给它一个视频链接,它会整理出一份带时间索引的课堂笔记。
项目叫 bilibili-douyin-notes,可以装进 Claude Code、Codex 这类 agent,支持 B 站、抖音、YouTube 和小红书的链接。视频有字幕就用字幕,没有字幕就在本机用 faster-whisper 转写。README 写的是不调付费 API,也不需要显卡。
笔记的结构是:分小节的正文,后面附知识地图、概念卡片和自测题,最后是时间索引,点一下就跳回视频里对应的位置。它还能按时间点截图,黑屏和模糊的帧会被标出来,留不留由 agent 判断。效果可以先看仓库 examples 目录里那份李宏毅机器学习课的示例笔记。
在 Claude Code 里安装:
git clone github.com/lucky-Luor/bilibi… ~/.claude/skills/bilibili-douyin-notes
然后用 pip 装目录里的 requirements.txt,需要 Python 3.10 以上。Codex 等其他 agent 放在 ~/.agents/skills/ 下。
几个要先知道的限制:
没有字幕的视频最慢。作者写的是,CPU 转写一小时以上的视频,耗时大约是视频时长的 1 到 3 倍。
B 站扫码登录后能拿到 AI 字幕,这样多数视频就不用转写了。登录凭据会存在本地的 config.json 里,不要发给别人。
抖音和小红书要先把视频下载到本机再处理,平台一改版,这部分就可能暂时用不了,而且只能处理公开视频。
下载下来的视频和整理出的笔记,自己学习用就好,不要拿去转发或搬运。
项目 10 月 1 日建,MIT 协议。抖音签名用到的一个文件是 GPLv3,它不在仓库里,第一次用抖音功能时才会下载。目前 95 星(GitHub 数据,10 月 19 日早上),还很新,效果先以作者的说明和示例为准。
仓库:github.com/lucky-Luor/bilibi…
看到自 @GitHub_Daily:xitter.cf/GitHub_Daily/status/21…
在 B 站收藏了一堆教程,看完的没几个,看完了也记不住讲了啥,想复习还得拖着进度条一点点找。
bilibili-douyin-notes 是一个 AI Agent 技能,装进 Claude Code 这类工具后,丢一个视频链接过去,就能整理成一份课堂笔记。
B 站、抖音、YouTube、小红书 4 个平台的链接都认,有字幕直接用字幕,没字幕就在本地做语音识别,不调任何付费接口。
GitHub:github.com/lucky-Luor/bilibi…
笔记按小节整理,关键术语加粗,后面还附了知识地图、概念卡片和自测题,挺像认真的同学课后整理出来的那种。
文末带一份时间索引,点一下就跳回视频对应的位置,复习时找某个知识点方便不少。
还能按时间点截取重点画面,黑屏、模糊的帧会先被标出来,再由 AI 看一遍决定留不留。
仓库里放了一份李宏毅机器学习课的示例笔记,可以先看看效果。
Michael Kaiser retweeted
Qwen Code Web Shell can now be installed like an app, thanks to a community PR by jabrailkhalil!
Install it from your browser, and you get a standalone window and its own app icon. No more digging through browser tabs to find Qwen Code.
PR: github.com/QwenLM/qwen-code/…
Michael Kaiser retweeted
Anthropic’s comeback with Opus 5.5 should be studied...
Opus 5 was getting cooked for being verbose, over engineering simple tasks and needing constant babysitting people were literally canceling or switching away
Then Opus 5.5 dropped at $4/$20... cleaned up the writing and started beating Fable 5.1 on Terminal-Bench and CursorBench
Anthropic fixed the exact things people were complaining about and made it cheaper at the same time thats actually are
Michael Kaiser retweeted
Opus 5.5 came out almost a month ago and it still beats everything.
That is how far ahead Anthropic is.
最近のモデルの使い分け📝
【Opus 5.5】
・主砲。コーディングほとんどこれでやってる。
・Claudeの普通のChatもこいつでやる。
・判断が必要なAPIタスクもこいつにやらせることが多い。多少コスト嵩むが速くて賢いので投資と割り切ってる。
・最近のML Bear Timesの編集もこいつがやってる
・Opus安く使うためにキャッシュの勉強ちゃんとした
【Fable 5.1】
・Opus 5.5 がきてから全く使わなくなった
・早く Fable 5.5 出してくれ
【Haiku 5.5】
・Web Fetchツールが必要な簡単なAPIタスクをやらせてる
・AnthropicのWeb Fetchツールが謎に強いことに気づいてからHaiku4.5/5.5を使ってる
・GPT-6 Lunaの方が安いのでタスクごとに使い分けてる
【GPT-6 Astra】
・Codex経由で利用してOpus 5.5 のコードのレビューをさせる
・Opus 5.5 にレビューさせてもいいが、ChtaGPT Pro プランの利用制限が事実上無限に近いのでこいつにやらせてる
・ChtaGPT Workとかでもたまに使う、普通の Claude Chatとの使い分けはあまり深く考えてない。
【GPT-6.1 Sol】
・判断が必要なAPIタスクで Opus 5.5 に頼めないほど数があり、そこそこ難しいものをやらせてる。
・とにかく遅いので Fast Mode で使ってる。GPT-5.6 Solより遥かに遅いの謎い。
【GPT-6 Luna】
・判断が必要なAPIタスクで簡単なものをやらせてる
・安くていいよね、そんなに早くないのが玉に瑕。
【GPT-5.6 Sol】
・仕事のとあるタスクと相性いいのでそこをずっとやってもらってる
・なぜかGPT-6.1 Solに切り替えられなくて歯痒い
【Gemini 4 Argon】
・使ってない
・日本語綺麗なので文章書かせたいがOpus 5.5が賢すぎて代替できてない
・Opus 5.5の日本語が最近ダメダメなのでリライトに使ったりするといいかもと思いつつ使ってない
【Grok Bot】
・モデルじゃないけど書いとく
・TwitterやYoutubeチャンネルの監視をしてもらってる
・安定して動いてとてもいい
・利用量をガンガン食うのが玉に瑕 ($200プランで60-70%ぐらい消費しちゃう)
【dots】
・秘書として働いてもらってる
・操作承認系がポンコツなのでよく喧嘩してるがGrokBotと違って利用量が寛大なので仕方なく活用方法を探ってる
・Gmailの整理、カレンダー整理、各種通知とか
・ChtaGPT Pages (≒Notion) に今までObsidianでまとめてたものを書いてもらってる(日記、旅行記、映画鑑賞記録とか)
【その他の格安モデル】
・全く使ってない
・中華格安モデルもっと頑張ってくれ
Michael Kaiser retweeted
and you have no idea how excited i am for fable 5.5! let the models come! <3
Michael Kaiser retweeted
There is no better model than Opus 5.5 right now. It makes me super glad that anthropic got its magic back.
Michael Kaiser retweeted
DAILY AI BRIEF 🗞 — Oct 16
META 🔥:
- Meta released Muse Spark Open, an open-weight 816B-total, 42B-active MoE model with a 1M-token context window, on Hugging Face and optimized to run locally on Mac Studio.
NVIDIA 🔥:
- NVIDIA released Nemotron 3.5 Super VL, an open 120B-total, 12B-active multimodal model for long-running AI agents.
- NVIDIA also introduced Nemotron 3.5 Bolt 24GB, a model that fits into 24GB of memory.
OPENAI 🔥:
- OpenAI is rolling out GPT-Live-1.1 to Voice in ChatGPT, Codex and dots for all users, with new voices in six languages and API support coming soon.
- OpenAI launched the Rosalind Academic Plan, giving eligible US university labs sponsored access to GPT-Rosalind.
- Sites is now generally available for ChatGPT Enterprise with US and EU data residency.
- ChatGPT can now view your open Chrome tabs.
- Codex landed changes and more compute to sharply reduce "Selected model is at capacity" errors.
GOOGLE 🔥:
- Gemini 4 Argon is rolling out in Antigravity to paid Google AI Pro subscribers with a separate weekly Argon quota.
- Google launched Universal Cart, a cross-retailer shopping cart, in the US.
- Circle to Search can now check whether a text message is a scam.
MICROSOFT 🔥:
- Microsoft finished pre-training MAI-Base-2 and is already preparing the MAI-Base-3 training cycle.
- GitHub made agentic autofix for code scanning alerts generally available.
ANTHROPIC 🔥:
- Anthropic gave a team from METR employee-like access to assess its safety practices.
PERPLEXITY 🔥:
- Perplexity open-sourced SPACE, the Firecracker-based sandbox that runs every Perplexity Computer task, under Apache 2.0.
- Nemotron 3.5 Super VL is now in Perplexity for Pro and Max subscribers and in the Agent API.
CURSOR 🔥:
- Cursor added Muse Wonder at $4/$20 per million input/output tokens, scoring 46.1% on CursorBench.
BLACK FOREST LABS 🔥:
- Black Forest Labs released FLUX 3 Image Klein, a 5.6B open-weight image model with native 4K that runs on a single consumer GPU.
KREA 🔥:
- Krea launched Krea 3, an image-editing model for prompt-based 2K edits in under 8 seconds.
AMAZON 🔥:
- Amazon's Bee launched two new personal AI devices starting at $75.
* Used Grok to compose this brief, cherry-picking the news and doing some post-editing.
DAILY AI BRIEF 🗞 — Oct 15
SPACEXSI 🔥:
- SpaceXSI launched Grok Voice 3.0, a speech-to-speech model built for customer calls that it says responds in under a second with 40% lower latency.
- The Grok Bot marketplace is now open for developer submissions of connectors, plugins and MCP servers.
ANTHROPIC 🔥:
- Claude Code Desktop added a sessions hub for starting, tracking and following up on multiple sessions from one screen.
- Claude Managed Agents, the Messages API and the Claude SDK now support OpenTelemetry traces.
- Anthropic opened a Singapore office, its fifth in Asia-Pacific, and signed an AI safety MOU with Singapore's government.
PERPLEXITY 🔥:
- Perplexity Computer added Ultrafast versions of GPT-6 Astra and SOL 6.1 for Max subscribers.
MISTRAL 🔥:
- New Material, a design and AI product studio, is joining Mistral to help build its frontier solutions.
MICROSOFT 🔥:
- GitHub Copilot updated HydraFusion's model pool and added a new HydraFusion Max option, both still in research preview.
GOOGLE 🔥:
- Google Messages is adding an enhanced protection mode against phone scams.
- YouTube Music is rolling out labels for AI-generated songs.
OPENAI 🔥:
- Codex got another global usage-limit reset on Day 10.
NVIDIA 🔥:
- NVIDIA AI teased its own model launch coming next week.
* Used Grok to compose this brief, cherry-picking the news and doing some post-editing.




































