Simon Willison · 实时热榜

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 —

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

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

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

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

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

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

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

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

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

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

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.

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:

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

Tool: Mermaid to ASCII art (mermaid-ascii) After building the Mermaid to ASCII tool based on Grok Build's Rust code I learned that there's an older, more fully-featured Go library called AlexanderGrooff/mermaid-ascii that implements a similar pattern, so I had Claude Fable 5 compile that one to WebAssembly as well so I could compare the two. This one includes support for colors! Tags: go , tools , webassembly , mermaid

I realize that some people really dislike AI, but this is an area where I'm willing to absolutely put my foot down as the top-level maintainer. Linux is not one of those anti-AI projects, and if somebody has issues with that, they can do the open-source thing and fork it. Or just walk away. AI is a tool, just like other tools we use. And it's clearly a useful one. It may not have been that "clearly" even just a year ago, but it's no longer in question today. There are other questions around AI (

Tool: Mermaid to Unicode box art (grok-mermaid) While exploring the codebase for the newly open-sourced Grok CLI coding agent I came across xai-grok-markdown/src/mermaid.rs , a "self-contained terminal renderer for Mermaid diagrams" written in Rust. I figured it would be fun to try that out in a browser via WebAssembly. Here's the prompt I ran in Claude Code for web (Fable 5), and this is what the resulting tool looks like: Tags: tools , rust , webassembly , mermaid , grok , xai