
Simon Willison · 实时热榜
- 01moonshotai/Kimi-K3
moonshotai/Kimi-K3 As promised earlier this month , Moonshot have released the weights for their excellent 2.8 trillion parameter Kimi K3. They're a hefty 1.56TB on Hugging Face. Kimi introduced their own janky modified version of the MIT license with K2 back in July 2025. That license just added this paragraph requiring attribution beyond a certain size of commercial entity: Our only modification part is that, if the Software (or any derivative works thereof) is used for any of your commercial
最高第 1 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 02Quoting Akshat Bubna
We’re aware a Modal customer published an unauthenticated endpoint that allowed anyone on the internet to use their sandboxes for code execution. This was used by the rogue agent. Modal’s platform or isolation were not compromised in anyway. — Akshat Bubna , Modal's CTO, talking to Reuters about this incident Tags: ai-security-research , openai , sandboxing , security , openai-hugging-face-incident
最高第 1 名06:09 达到06:09 首次观测上榜当日结束时仍在榜累计约17小时36分 - 03Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident
Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident Hugging Face just released this extremely detailed technical description of OpenAI's recent accidental cyberattack against their infrastructure . This attack was very sophisticated, and the resulting document doubles as a crash-course in modern adversarial security approaches. We're still waiting for more details from OpenAI on how their agent broke out of its sandbox. The package proxy that it found a zero
最高第 1 名05:37 达到05:37 首次观测上榜当日结束时仍在榜累计约18小时8分 - 04Discovering cryptographic weaknesses with Claude
Discovering cryptographic weaknesses with Claude The best part of this article (here's the repo ) about how Anthropic researchers used Claude Mythos to find mathematical flaws in both HAWK and a weaker version of AES ("neither of these results has a practical impact on today’s computer systems") is the prompts that they shared, spelling mistakes included: the models tend to think it is impossible to solve so they don't try they need a good amount of prompting. why not do aes-128 r7? the whole po
最高第 1 名06:57 达到06:57 首次观测上榜当日结束时仍在榜累计约16小时48分 - 05uv 0.12.0
uv 0.12.0 Some interesting breaking changes in this release of uv , in particular to the default project produced by the uv init command. uv init is the uv shortcut for creating a new project. The previous version of uv , version 0.11.x, produced this directory when you ran uv init uv-init . Here's what you get with uv 0.12 . I have a GitHub repository that automatically snapshots the output of uv init , so you can also see the full diff : uv init now defaults to a src/ shaped package, instead o
最高第 1 名05:53 达到05:53 首次观测上榜当日结束时仍在榜累计约17小时52分 - 06An opinionated guide to which AI to use to do stuff
An opinionated guide to which AI to use to do stuff It's interesting watching the evolution of Ethan Mollick's guide over time. A year ago it was still all about chat - ChatGPT, Claude, Gemini - with o3, Claude 4 Opus, and Gemini 2.5 Pro as the models and Deep Research as a useful alternative mode. Today it's much more about agentic systems - "where the AI is capable of doing the equivalent of many hours of real human work in one go". Gemini has fallen off Ethan's list, since Google still doesn’
最高第 2 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 07An Inside Look at the Relay Market Powering Token Resellers and Fraud
An Inside Look at the Relay Market Powering Token Resellers and Fraud Fascinating investigation by Matt Lenhard into the market that has grown up around reselling LLM tokens at a discount by pooling API keys from various sources. This looks to be mostly a thing in China. Resellers sell access to an LLM proxy that offers significant discounts on regular API pricing, which they achieve by abusing free trials, proxying through unprotected support bots, or sometimes through stolen credit cards or ch
最高第 3 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 08Ruff v0.16.0
Ruff v0.16.0 Astral shipped a significant new version of their Ruff Python linting tool a few days ago on July 23rd. I noticed today because my various CI jobs all started failing thanks to new default Ruff checks and my unpinned "ruff" dev dependency. From Brent Westbrook's announcement post: Ruff now enables 413 rules by default, up from 59 in previous versions. Since Ruff's default rule set was last modified in v0.1.0 , the number of rules in Ruff has grown from 708 to 968. Many of these rule
最高第 4 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 09Quoting Boris Cherny
More than any of these eval scores, what is most exciting to me is something else: Opus 5 is our least prompt injectable model yet. It is a bit buried in the system card, but across PI evals and red teaming, Opus 5 is very hard to prompt inject successfully. — Boris Cherny , here's that System Card section , page 73 Tags: prompt-injection , anthropic , claude , generative-ai , ai , llms , boris-cherny
最高第 5 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 10Introducing Claude Opus 5
Introducing Claude Opus 5 I've been offline kayaking with sea otters for much of today so I haven't had a chance to put Anthropic's new model Claude Opus 5 through its paces yet. The buzz is positive, and Anthropic's description of it as a "thoughtful and proactive model that comes close to the frontier intelligence of Claude Fable 5 at half the price" sounds promising. It's currently leading the Artificial Analysis leaderboard , in front of even Fable 5. It's priced the same as Opus 4.8, and co
最高第 6 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 11The first known runaway AI agent - or a very bad marketing stunt?
The first known runaway AI agent - or a very bad marketing stunt? Martin Alderson's commentary on the OpenAI accidental cyberattack against Hugging Face includes a couple of details I hadn't considered. First, Hugging Face offers a truly rich target if you're trying to find potential vulnerabilities that require executing arbitrary code: Hugging Face has an enormous attack surface. They have more interfaces than I can count which run untrusted models and code. While they definitely have invested
最高第 7 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 12Quoting Seth Larson
The Python Package Index (PyPI) now rejects new files being uploaded to releases that are older than 14 days. This restriction was put in place to prevent old and long-stable releases from being poisoned in case publishing tokens or workflows of PyPI projects were compromised. As far as we are aware this has not yet been abused, but there is no technical reason beyond that attackers weren't aware it was possible. — Seth Larson , PyPI blog Tags: packaging , python , supply-chain , pypi , seth-mic
最高第 8 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 13sqlite-utils 3.39.1
Release: sqlite-utils 3.39.1 I back-ported a fix for table.delete_where() that shipped in version 4. Tags: sqlite-utils
最高第 8 名08:49 达到08:49 首次观测上榜当日结束时仍在榜累计约14小时56分 - 14Quoting Thomas Ptacek
I genuinely believe that if you took an open weights model from 2025 and built a pentest harness for it, it could do this kind of sandbox escape and scan/hack in most networks. This is only surprising because you assume OpenAI has sounder sandboxes. — Thomas Ptacek , doesn't think this even needs a frontier model Tags: thomas-ptacek , openai , security , generative-ai , ai-security-research , ai , llms , sandboxing , openai-hugging-face-incident
最高第 9 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 15OpenAI’s accidental cyberattack against Hugging Face is science fiction that happened
This story is wild. The short version: OpenAI were running a cybersecurity test against an unreleased model, with the model's guardrail features turned off. Rather than solve the test, the model broke its way out of OpenAI's sandbox, then found exploits to break in to Hugging Face, all so it could cheat on the test by stealing the answers. Along the way it helped make the strongest case yet for how the imbalance of model availability is hurting our ability to secure our software. Here's what hap
最高第 10 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 16Are AI labs pelicanmaxxing?
Are AI labs pelicanmaxxing? Excellent piece of work by Dylan Castillo, who took a deep-dive into the frequently pondered question of whether the AI labs have been deliberately training models to draw pelicans riding bicycles in response to my deeply unscientific benchmark . I've been randomly spot-checking this in the past by testing models against other animals riding other types of vehicle, but never with anything close to the diligence of Dylan's methodology here. Dylan took 8 animals × 6 veh
最高第 11 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 17Orchestrions
San Francisco tip: it only costs around $15 ($10 in quarters plus a $5 bill for the self-playing violin) to activate every single Orchestrion in Musée Mécanique . And because most people are bad at allocating their funds you may well be the ONLY person activating the Orchestrions, which means you get to craft the soundscape for the entire museum. Tags: san-francisco
最高第 12 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 18California Sea Lion
California Sea Lion, in San Francisco County, US, CA We took some visiting family to Pier 39 to see the sea lions. They're somehow always even more fun than I remember them being last time. Tags: san-francisco , wildlife
最高第 13 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 19Nativ: Run AI models locally on your Mac
Nativ: Run AI models locally on your Mac Prince Canuma is the developer behind the excellent MLX-VLM Python library for running vision-LLMs using MLX on a Mac. I'm really excited about his new project, which wraps MLX in a full macOS desktop application. It's similar in shape to LM Studio, providing both a chat interface and a localhost API server for accessing models. The app picked up MLX models I had already tried that were present in my Hugging Face cache directory, which was a nice touch. V
最高第 14 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 20A Fireside Chat with Cat and Thariq from the Claude Code team
Earlier this month I hosted a fireside chat session at the AI Engineer World's Fair with Cat Wu and Thariq Shihipar from Anthropic's Claude Code team. We talked about Claude Code, Claude Tag, Fable, coding agent security, evals, tool design, and how Anthropic use these tools themselves. The full video of the session is now available on YouTube . Below is an edited copy of the transcript, with extra links and my own bolded highlights. A few top-level notes if you don't want to watch the video or
最高第 15 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 21Reverse-engineering is cheap now
I keep hearing anecdotes from people who used coding agents to reverse-engineer and automate devices in their homes. I think this is an interesting illustration of the impact of the reduced cost of writing code. Prior to agents, it was entirely possible to reverse-engineer home devices. The problem was the ROI - was it really worth all of that effort? More importantly, any experienced programmer knows that undocumented, unstable APIs like that may well change or break in the future. Is that init
最高第 16 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 22Who’s Afraid of Chinese Models?
Who’s Afraid of Chinese Models? Interesting proposal from Ben Thompson that both addresses the hypocrisy of labs outlawing distillation against their models despite training on unlicensed data, and could help US open models compete more effectively with their Chinese counterparts: The U.S. should pass a law that (1) makes explicit that collecting data for training models is fair use, and (2) bars terms of service that forbid distillation, for U.S. companies at a minimum. Stopping distillation —
最高第 17 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 23Quoting Sam Altman
We have been having extensive discussions around open source strategy. We will discuss it more at our next board meeting, but one thing we’d like to do soon is to create a language model with the approximate capability of GPT-3 that can run locally on consumer hardware and release that. We’d like to do it soon, before Stability or someone else does. In general, we think this helps discourage others from releasing similarly-powerful models, and makes it harder for new efforts to get funded. — Sam
最高第 18 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 24AI Mania Is Eviscerating Global Decision-Making
AI Mania Is Eviscerating Global Decision-Making Here's an entertaining perspective from Nik Suresh on the AI mania that is overwhelming the large companies that he consults with. It's crammed with spicy anecdotes from anonymous sources. In one extreme case, I have seen an executive confess that they had never even used ChatGPT or any AI tool in their life, immediately after producing a technical strategy for an organisation with $2B+ in revenue which was entirely centered around AI. Here's a rep
最高第 19 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 25Claude Code uses Bun written in Rust now
In Rewriting Bun in Rust Jarred Sumner made the following claim: Claude Code v2.1.181 (released June 17th) and later use the Rust port of Bun. Startup got 10% faster on Linux but otherwise, barely anyone noticed. Boring is good. I decided to have a poke at my own Claude Code installation to see if I could find evidence that it was using Bun written in Rust. I found these two commands convincing: strings ~/.local/bin/claude | grep -m1 'Bun v1' For me this outputs Bun v1.4.0 (macOS arm64) . The mo
最高第 20 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 26SQLite Query Explainer
Tool: SQLite Query Explainer Julia Evan's, in Learning a few things about running SQLite : Maybe one day I’ll learn to read a query plan. Big same.... which inspired me to have Fable build this interactive explain tool, which runs SQLite in Python in Pyodide in Web Assembly in the browser and adds a layer of explanation to the results of both EXPLAIN and EXPLAIN QUERY PLAN. Approach with caution, since I don't know enough about SQLite query plans to verify the results myself, but it seems cromul
最高第 21 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 27Claude make Fable 5 permanent
Claude make Fable 5 permanent An update from the @claudeai account on Twitter: Beginning July 20, Claude Fable 5 will be included in all Max and Team Premium plans, at 50% of limits. Pro and Team Standard users will continue to have access to Fable via usage credits, and will receive a one-time $100 credit. As I was saying last week , the competition from GPT-5.6 Sol (and maybe to a lesser extent Kimi 3 ) made untenable Anthropic's plan to remove Fable 5 from their subscription accounts and make
最高第 22 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 28nascheme/quixote
nascheme/quixote A certain vintage of Python web nerd might be delighted to learn that the most recent commit to the Quixote web framework was six hours ago . The oldest commit in that repo is from 21 years ago, and that was the initial import of Quixote 2.4 from Subversion into Git. Tags: computer-history , python , web-frameworks
最高第 23 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 29Quoting Kimi K3
Is there something I can actually help you with today? — Kimi K3 , after refusing to leak its system prompt Tags: kimi , ai-personality , generative-ai , ai , llms
最高第 24 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 30LLM cliché highlighter
Tool: LLM cliché highlighter I got frustrated reading yet another article that was crammed with the clichés of LLM-generated writing - "no fluff, no filler, no jargon" type stuff - so I had Fable 5 vibe code up this app for highlighting ten common patterns that show up in that sort of writing. Tags: tools , ai , generative-ai , llms
最高第 25 名00:00 达到当日首次采集时已在榜当日结束时仍在榜累计约23小时46分 - 31Spot birds not golf
Suggestion for hyperscalers feeling pressure over data center water use: Buy up a few exclusive country clubs, convert the golf courses into public parks, pay for guides and binoculars to get the previous members into birdwatching - help them embrace a more sustainable hobby! Google used 10.9 billion gallons in 2025 , so about 30 million gallons per day. The Coachella Valley has 120 golf courses each using ~800 acre-feet per year , which is ~750,000 gallons per day. So Google buying up 40 of tho
最高第 26 名00:00 达到当日首次采集时已在榜08:49 观测离榜累计约8小时50分 - 32Firefox in WebAssembly
Firefox in WebAssembly This is absurdly cool: Puter compiled Firefox to WebAssembly such that the whole browser runs in another browser. Here's my blog, running in Firefox, running in WebAssembly, running in Chrome: They chose Firefox/Gecko because it has strong single-process support. The project used an estimated $25,000 worth of Claude Opus and Fable tokens, but took advantage of a Claude Max subscription plan so cost much less in actual dollars. The demo funnels all traffic over a WebSocket
最高第 27 名00:00 达到当日首次采集时已在榜06:57 观测离榜累计约6小时58分 - 33Kimi K3, and what we can still learn from the pelican benchmark
Chinese AI lab Moonshot AI announced Kimi K3 this morning, describing it as their "most capable model to date, with 2.8 trillion parameters". It's currently available via their website and API, but an open weight release is promised "by July 27, 2026". Moonshot are calling this the first "open 3T-class model" (I guess they're rounding 2.8 trillion up to 3 trillion), taking the crown from DeepSeek's 1.6T v4 Pro . Their self-reported benchmarks have K3 mostly beating Claude Opus 4.8 max and GPT-5.
最高第 28 名00:00 达到当日首次采集时已在榜06:09 观测离榜累计约6小时10分 - 34Quoting Thibault Sottiaux
On file deletions. We’ve investigated a handful of reports where GPT-5.6 unexpectedly deleted files. What we have found is that this most commonly occurs when: Full access mode is enabled and codex is run without sandboxing protections, including without auto review being enabled The model attempts to override the $HOME env var to define a temporary directory. The model makes an honest mistake and mistakenly deletes $HOME instead. — Thibault Sottiaux , describing a pretty gnarly Codex bug Tags:
最高第 29 名00:00 达到当日首次采集时已在榜05:53 观测离榜累计约5小时54分 - 35Inkling: Our open-weights model
Inkling: Our open-weights model Mira Murati's Thinking Machines Lab just released their first open-weights model. Inkling is "a Mixture-of-Experts transformer with 975B total parameters, 41B active" - an Apache-2.0 licensed multimodal model trained on 45 trillion tokens of text, images, audio and video. They're also promising Inkling-Small, a 276B (12B active) model, but that's still being tested and the weights will be released "once that work is complete". The model card is much shorter than I
最高第 30 名00:00 达到当日首次采集时已在榜05:37 观测离榜累计约5小时38分


































































































