Simon Willison’s Weblog

Friday, 7th April 2023

The progress in AI has allowed things like taking down hate speech more efficiently—and this is due entirely to large language models. Because we have large language models [...] we can do a better job than we ever could in detecting hate speech in most languages in the world. That was impossible before.

Yann LeCun # 7:32 pm

We need to tell people ChatGPT will lie to them, not debate linguistics

ChatGPT lies to people. This is a serious bug that has so far resisted all attempts at a fix. We need to prioritize helping people understand this, not debating the most precise terminology to use to describe it.

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Database “sharding” came from UO? (via) Raph Koster coined the term “shard” back in 1996 in a design document proposing a way of scaling Ultima Online: “[...] we realized we would need to run multiple whole copies of Ultima Online for users to connect to, we needed to come up with a fiction for it. [...] the evil wizard Mondain had attempted to gain control over Sosaria by trapping its essence in a crystal. When the Stranger at the end of Ultima I defeated Mondain and shattered the crystal, the crystal shards each held a refracted copy of Sosaria.” # 1:56 pm

For example, if you prompt GPT-3 with “Mary had a,” it usually completes the sentence with “little lamb.” That’s because there are probably thousands of examples of “Mary had a little lamb” in GPT-3’s training data set, making it a sensible completion. But if you add more context in the prompt, such as “In the hospital, Mary had a,” the result will change and return words like “baby” or “series of tests.”

Benj Edwards # 3:36 am

Why ChatGPT and Bing Chat are so good at making things up. I helped review this deep dive by Benj Edwards for Ars Technica into the hallucination/confabulation problem with ChatGPT and other LLMs, which is attracting increasing attention thanks to stories like the recent defamation complaints against ChatGPT. This article explains why this is happening and talks to various experts about potential solutions. # 3:33 am

Several libraries let you declare objects with type-hinted members and automatically derive validation rules and serialization/deserialization from the type hints – Pydantic is the most popular, but alternatives like msgspec are out there too. There’s also a whole new generation of web frameworks like FastAPI and Starlite which use type hints at runtime to do not just input validation and serialization/deserialization but also things like dependency injection.

Personally, I’ve seen more significant gains in productivity from those runtime usages of Python’s type hints than from any static ahead-of-time type checking, which mostly is only useful to me as documentation.

James Bennett # 2:19 am

The different uses of Python type hints (via) Luke Plant describes five different categories for how Python optional types are being used today: IDE assistants, type checking, runtime behavior changes via introspection (e.g. Pydantic), code documentation, compiler instructions (ala mypyc)—and a bonus sixth, dependency injection. # 2:17 am

Projectories have power. Power for those who are trying to invent new futures. Power for those who are trying to mobilize action to prevent certain futures. And power for those who are trying to position themselves as brokers, thought leaders, controllers of future narratives in this moment of destabilization. But the downside to these projectories is that they can also veer way off the railroad tracks into the absurd. And when the political, social, and economic stakes are high, they can produce a frenzy that has externalities that go well beyond the technology itself. That is precisely what we’re seeing right now.

danah boyd # 2:04 am