I got this sense as well, particularly from the section about assertions. Most of the use cases they describe (e.g checking function arguments and return values) are much better handled by an expressive type system than ad-hoc checks.
> and it’s ultimately done to show that OpenAI is making an effort to mitigate the risks that regulators claim it creates.
I’d go one step further — the subtext is that only Open AI is willing to do this, and that LLMs are just too dangerous to open source/not another with regulation that only big companies have the resources to adhere to.
I think IAM would be a lot easier to interact with from a dev perspective if the error messages were more clear. I suspect that they are sometimes intentionally vague (or misleading) as a kind of security-through-obscurity. For example, S3 returns “file does not exist” errors when the real problem is that the caller doesn’t have permission to access the bucket/prefix.
> Gleam's labelled arguments are AFAIK a unique feature. This lets you have named function argument appear differently to the caller than they do internally. The caller may way to refer by verb ("multiply_by") and the function may want to refer to it as a noun ("multiplier").
I find that kind of surprising; the lack of “customer service voice” is one of the main reasons I prefer the Mistral models over Open AI’s, even if the latter are somewhat better at complex/specific tasks.
The fact that, at the time of writing, all of the comments on this post are about the Oxford comma rather than the actual thesis of the article goes a long way to proving its point.