Simon Willison’s Weblog

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Thursday, 30th May 2024

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 600+ comment Hacker News thread is crammed with GraphQL war stories, mostly supporting the conclusions of the article. # 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. # 7:38 am

The realization hit me [when the GPT-3 paper came out] that an important property of the field flipped. In ~2011, progress in AI felt constrained primarily by algorithms. We needed better ideas, better modeling, better approaches to make further progress. If you offered me a 10X bigger computer, I’m not sure what I would have even used it for. GPT-3 paper showed that there was this thing that would just become better on a large variety of practical tasks, if you only trained a bigger one. Better algorithms become a bonus, not a necessity for progress in AGI. Possibly not forever and going forward, but at least locally and for the time being, in a very practical sense. Today, if you gave me a 10X bigger computer I would know exactly what to do with it, and then I’d ask for more.

Andrej Karpathy # 7:27 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. # 7:19 am