Ask HN: What's with floating point operations and AI regulations?

  • The rationale: it's a manageable number to "easily" differentiate regulated parties.

    How they got to this number, I've got no idea, but having reviewed training, it's easy to demonstrate whether or not your model should be regulated. It lets companies "self regulate" and as an engineer, if you build a model exceeding these parameters, you should be complying with the rules.

    How do you know: take your hardware specs and multiply them by how long it takes you to train your model on that hardware. It's straightforward and only enforceable in hindsight.

  • This article has some information. https://jack-clark.net/2024/03/28/what-does-1025-versus-1026...

  • its bad regulation where the regulators have to be seen doing something.

    I could almost imagine it being explained as a speed limit for AI.