Simon Willison’s Weblog

Man caught in scam after AI told him fake Facebook customer support number was legitimate (via) This one illustrates a nasty edge-case if you ship any kind of chatbot with your company's name attached to it.

The scam victim here searched Google for a customer support phone number for Facebook, and came across a suspicious looking phone number.

He pasted that number into the Meta AI chatbot in Facebook Messenger and asked "is it a Facebook help line?" - and a Meta AI answered:

The phone number 1-xxx-xxx-xxxx is indeed a legitimate Facebook support number. Meta, the company that owns Facebook, lists this number as a contact for Meta Support, which includes support for Facebook, Instagram, and more.

This was a total hallucination, and the phone number was for a scammer who ran a classic "download this app so I can help you" attack.

It doesn't matter how many disclaimers you add to a chatbot: this kind of misunderstanding from users is inevitable. # 31st May 2024, 4:53 pm

Django Enhancement Proposal 14: Background Workers. Jake Howard's DEP has been approved and is moving into the implementation stage.

Django doesn't have a first-party solution for long-running tasks, however the ecosystem is filled with incredibly popular frameworks, all of which interact with Django in slightly different ways. Other frameworks such as Laravel have background workers built-in, allowing them to push tasks into the background to be processed at a later date, without requiring the end user to wait for them to occur. [...]

This proposal sets out to provide an interface and base implementation for long-running background tasks in Django.

Jake has an illustrative reference implementation called django-tasks. # 31st May 2024, 8:44 am

Why, after 6 years, I’m over GraphQL (via) I've seen many of these criticisms of GraphQL before - N+1 queries, the difficulty of protecting against deeply nested queries - but Matt Bessey collects them all in one place and adds an issue I hadn't considered before: the complexity of authorization, where each field in the query might involve extra permission checks:

In my experience, this is actually the biggest source of performance issues. We would regularly find that our queries were spending more time authorising data than anything else.

The 400+ comment Hacker News thread is crammed with GraphQL war stories, mostly supporting the conclusions of the article. # 30th May 2024, 10:36 am

What does the public in six countries think of generative AI in news? (via) Fascinating survey by the Reuters Institute for the Study of Journalism at Oxford that asked ~12,000 people across six countries for their opinions on AI usage in journalism.

It’s also being interpreted as evidence that few members of the general public actually use these tools, because the opening survey questions ask about personal usage.

I don’t think the numbers support that narrative, personally. For survey participants in the USA 7% used ChatGPT daily and 11% used it weekly, which is higher than I would expect for those frequencies. For the UK those were 2% daily and 7% weekly.

The 18-24 group were the heaviest users of these tools. Lots of other interesting figures to explore. # 30th May 2024, 7:38 am

Codestral: Hello, World! Mistral's first code-specific model, trained to be "fluent" in 80 different programming languages.

The weights are released under a new Mistral AI Non-Production License, which is extremely restrictive:

3.2. Usage Limitation

• You shall only use the Mistral Models and Derivatives (whether or not created by Mistral AI) for testing, research, Personal, or evaluation purposes in Non-Production Environments;
• Subject to the foregoing, You shall not supply the Mistral Models or Derivatives in the course of a commercial activity, whether in return for payment or free of charge, in any medium or form, including but not limited to through a hosted or managed service (e.g. SaaS, cloud instances, etc.), or behind a software layer.

To Mistral's credit at least they don't misapply the term "open source" in their marketing around this model - they consistently use the term "open-weights" instead. They also state that they plan to continue using Apache 2 for other model releases.

Codestral can be used commercially when accessed via their paid API. # 30th May 2024, 7:19 am

What We Learned from a Year of Building with LLMs (Part I). Accumulated wisdom from six experienced LLM hackers. Lots of useful tips in here. On providing examples in a prompt:

If n is too low, the model may over-anchor on those specific examples, hurting its ability to generalize. As a rule of thumb, aim for n ≥ 5. Don’t be afraid to go as high as a few dozen.

There's a recommendation not to overlook keyword search when implementing RAG - tricks with embeddings can miss results for things like names or acronyms, and keyword search is much easier to debug.

Plus this tip on using the LLM-as-judge pattern for implementing automated evals:

Instead of asking the LLM to score a single output on a Likert scale, present it with two options and ask it to select the better one. This tends to lead to more stable results.

Reproducing GPT-2 (124M) in llm.c in 90 minutes for $20 (via) GPT-2 124M was the smallest model in the GPT-2 series released by OpenAI back in 2019. Andrej Karpathy's llm.c is an evolving 4,000 line C/CUDA implementation which can now train a GPT-2 model from scratch in 90 minutes against a 8X A100 80GB GPU server. This post walks through exactly how to run the training, using 10 billion tokens of FineWeb.

Andrej notes that this isn't actually that far off being able to train a GPT-3:

Keep in mind that here we trained for 10B tokens, while GPT-3 models were all trained for 300B tokens. [...] GPT-3 actually didn't change too much at all about the model (context size 1024 -> 2048, I think that's it?).

Estimated cost for a GPT-3 ADA (350M parameters)? About $2,000. # 28th May 2024, 7:47 pm

Pyodide 0.26 Release (via) PyOdide provides Python packaged for browser WebAssembly alongside an ecosystem of additional tools and libraries to help Python and JavaScript work together.

The latest release bumps the Python version up to 3.12, and also adds support for pygame-ce, allowing games written using pygame to run directly in the browser.

The PyOdide community also just landed a 14-month-long PR adding support to cibuildwheel, which should make it easier to ship binary wheels targeting PyOdide. # 28th May 2024, 7:04 pm

fastlite (via) New Python library from Jeremy Howard that adds some neat utility functions and syntactic sugar to my sqlite-utils Python library, specifically for interactive use in Jupyter notebooks.

The autocomplete support through newly exposed dynamic properties is particularly neat, as is the diagram(db.tables) utility for rendering a graphviz diagram showing foreign key relationships between all of the tables. # 27th May 2024, 9:14 pm

City In A Bottle – A 256 Byte Raycasting System (via) Frank Force explains his brilliant 256 byte canvas ray tracing animated cityscape demo in detail. # 26th May 2024, 6:25 pm

Statically Typed Functional Programming with Python 3.12 (via) Oskar Wickström builds a simple expression evaluator that demonstrates some new patterns enabled by Python 3.12, incorporating the match operator, generic types and type aliases. # 26th May 2024, 8:12 am

Why Google’s AI might recommend you mix glue into your pizza. I got “distrust and verify” as advice on using LLMs into this Washington Post piece by Shira Ovide. # 25th May 2024, 6:29 am

Golden Gate Claude. This is absurdly fun and weird. Anthropic's recent LLM interpretability research gave them the ability to locate features within the opaque blob of their Sonnet model and boost the weight of those features during inference.

For a limited time only they're serving a "Golden Gate Claude" model which has the feature for the Golden Gate Bridge boosted. No matter what question you ask it the Golden Gate Bridge is likely to be involved in the answer in some way. Click the little bridge icon in the Claude UI to give it a go.

I asked for names for a pet pelican and the first one it offered was this:

Golden Gate - This iconic bridge name would be a fitting moniker for the pelican with its striking orange color and beautiful suspension cables.

And from a recipe for chocolate covered pretzels:

Gently wipe any fog away and pour the warm chocolate mixture over the bridge/brick combination. Allow to air dry, and the bridge will remain accessible for pedestrians to walk along it.

UPDATE: I think the experimental model is no longer available, approximately 24 hours after release. We'll miss you, Golden Gate Claude. # 24th May 2024, 8:17 am

Nilay Patel reports a hallucinated ChatGPT summary of his own article (via) Here's a ChatGPT bug that's a new twist on the old issue where it would hallucinate the contents of a web page based on the URL.

The Verge editor Nilay Patel asked for a summary of one of his own articles, pasting in the URL.

ChatGPT 4o replied with an entirely invented summary full of hallucinated details.

It turns out The Verge blocks ChatGPT's browse mode from accessing their site in their robots.txt:

User-agent: ChatGPT-User
Disallow: /

Clearly ChatGPT should reply that it is unable to access the provided URL, rather than inventing a response that guesses at the contents! # 24th May 2024, 6:38 am

Some goofy results from ‘AI Overviews’ in Google Search. John Gruber collects two of the best examples of Google’s new AI overviews going horribly wrong.

Gullibility is a fundamental trait of all LLMs, and Google’s new feature apparently doesn’t know not to parrot ideas it picked up from articles in the Onion, or jokes from Reddit.

I’ve heard that LLM providers internally talk about “screenshot attacks”—bugs where the biggest risk is that someone will take an embarrassing screenshot.

In Google search’s case this class of bug feels like a significant reputational threat. # 24th May 2024, 5:33 am

A Grand Unified Theory of the AI Hype Cycle. Glyph outlines the pattern of every AI hype cycle since the 1960s: a new, novel mechanism is discovered and named. People get excited, and non-practitioners start hyping it as the path to true “AI”. It eventually becomes apparent that this is not the case, even while practitioners quietly incorporate this new technology into useful applications while downplaying the “AI” branding. A new mechanism is discovered and the cycle repeats. # 24th May 2024, 12:26 am

What is prompt optimization? (via) Delightfully clear explanation of a simple automated prompt optimization strategy from Jason Liu. Gather a selection of examples and build an evaluation function to return a numeric score (the hard bit). Then try different shuffled subsets of those examples in your prompt and look for the example collection that provides the highest averaged score. # 22nd May 2024, 4:02 pm

Mastering LLMs: A Conference For Developers & Data Scientists (via) I’m speaking at this 5-week (maybe soon 6-week) long online conference about LLMs, presenting about “LLMs on the command line”.

Other speakers include Jeremy Howard, Sophia Yang from Mistral, Wing Lian of Axolotl, Jason Liu of Instructor, Paige Bailey from Google, my former co-worker John Berryman and a growing number of fascinating LLM practitioners.

It’s been fun watching this grow from a short course on fine-tuning LLMs to a full-blown multi-week conference over the past few days! # 22nd May 2024, 3:34 am

New Phi-3 models: small, medium and vision. I couldn't find a good official announcement post to link to about these three newly released models, but this post on LocalLLaMA on Reddit has them in one place: Phi-3 small (7B), Phi-3 medium (14B) and Phi-3 vision (4.2B) (the previously released model was Phi-3 mini - 3.8B).

You can try out the vision model directly here, no login required. It didn't do a great job with my first test image though, hallucinating the text.

As with Mini these are all released under an MIT license.

UPDATE: Here's a page from the newly published Phi-3 Cookbook describing the models in the family. # 21st May 2024, 8:04 pm

Scaling Monosemanticity: Extracting Interpretable Features from Claude 3 Sonnet (via) Big advances in the field of LLM interpretability from Anthropic, who managed to extract millions of understandable features from their production Claude 3 Sonnet model (the mid-point between the inexpensive Haiku and the GPT-4-class Opus).

Some delightful snippets in here such as this one:

We also find a variety of features related to sycophancy, such as an empathy / “yeah, me too” feature 34M/19922975, a sycophantic praise feature 1M/847723, and a sarcastic praise feature 34M/19415708.

CRDT: Text Buffer (via) Delightfully short and clear explanation of the CRDT approach to collaborative text editing by Evan Wallace (of Figma and esbuild fame), including a neat interactive demonstration of how the algorithm works even when the network connection between peers is temporarily paused. # 20th May 2024, 9:19 pm

Spam, junk … slop? The latest wave of AI behind the ‘zombie internet’. I'm quoted in this piece in the Guardian about slop:

I think having a name for this is really important, because it gives people a concise way to talk about the problem.

Before the term ‘spam’ entered general use it wasn’t necessarily clear to everyone that unwanted marketing messages were a bad way to behave. I’m hoping ‘slop’ has the same impact – it can make it clear to people that generating and publishing unreviewed AI-generated content is bad behaviour.

NumFOCUS DISCOVER Cookbook: Minimal Measures. NumFOCUS publish a guide "for organizers of conferences and events to support and encourage diversity and inclusion at those events."

It includes this useful collection of the easiest and most impactful measures that events can put in place, covering topics such as accessibility, speaker selection, catering and provision of gender-neutral restrooms. # 19th May 2024, 6:24 pm

Fast groq-hosted LLMs vs browser jank (via) Groq is now serving LLMs such as Llama 3 so quickly that JavaScript which attempts to render Markdown strings on every new token can cause performance issues in browsers.

Taras Glek's solution was to move the rendering to a requestAnimationFrame() callback, effectively buffering the rendering to the fastest rate the browser can support. # 19th May 2024, 1:35 pm

A Plea for Sober AI. Great piece by Drew Breunig: “Imagine having products THIS GOOD and still over-selling them.” # 19th May 2024, 12:47 am

AI counter app from my PyCon US keynote. In my keynote at PyCon US this morning I ran a counter at the top of my screen that automatically incremented every time I said the words "AI" or "artificial intelligence", using vosk, pyaudio and Tkinter. I wrote it in a few minutes with the help of GPT-4o - here's the code I ran as a GitHub repository.

I'll publish full detailed notes from my talk once the video is available on YouTube. # 18th May 2024, 3:49 pm

Understand errors and warnings better with Gemini (via) As part of Google's Gemini-in-everything strategy, Chrome DevTools now includes an opt-in feature for passing error messages in the JavaScript console to Gemini for an explanation, via a lightbulb icon.

Amusingly, this documentation page includes a warning about prompt injection:

Many of LLM applications are susceptible to a form of abuse known as prompt injection. This feature is no different. It is possible to trick the LLM into accepting instructions that are not intended by the developers.

They include a screenshot of a harmless example, but I'd be interested in hearing if anyone has a theoretical attack that could actually cause real damage here. # 17th May 2024, 10:10 pm

Commit: Add a shared credentials relationship from twitter.com to x.com (via) A commit to shared-credentials.json in Apple's password-manager-resources repository. Commit message: "Pour one out." # 17th May 2024, 8:04 pm

PSF announces a new five year commitment from Fastly. Fastly have been donating CDN resources to Python—most notably to the PyPI package index—for ten years now.

The PSF just announced at PyCon US that Fastly have agreed to a new five year commitment. This is a really big deal, because it addresses the strategic risk of having a key sponsor like this who might change their support policy based on unexpected future conditions.

Thanks, Fastly. Very much appreciated! # 17th May 2024, 1:52 pm

Programming mantras are proverbs (via) I like this idea from Luke Plant that the best way to think about mantras like "Don’t Repeat Yourself" is to think of them as proverbs that can be accompanied by an equal and opposite proverb.

DRY, "Don't Repeat Yourself" matches with WET, "Write Everything Twice".

Proverbs as tools for thinking, not laws to be followed. # 17th May 2024, 12:10 pm