[ben_w]

So your job is to, in your own words, be "replicating 6 million years of evolution"?

You know how big your own team is, and that your team is itself an abstraction from the outside world. You know you get the shortcuts of being able to look at what nature does and engineer it rather than simply copy without understanding. You know your own evolutionary algorithms, assuming you're using them at all, run as fast as you can evaluate the fitness function, and that that is much faster than the same cycle with human, or even mammalian, generational gaps.

> CLIP is proof of what AI can and can't do

CLIP says nothing about what AI can't do, but it definitely says what AI can do. It's a minimum, not a maximum.

[abduhl]

Not to be rude but you're arguing with somebody that works in what I would assume is a highly mathematical space and asserting your opinion on how quickly that highly mathematical space can advance while your own profile admits that you were unable to understand "advanced calculus or group theory" and your own github indicates that you are stuck on "the hard stuff — abelian groups, curls, wedge products, Hessians and Laplacians" because you "don't understand the notation." Your opinion on the speed of advancement just doesn't seem informed?

Maybe this is an old post and your understanding has dramatically improved to the point where you're able to offer useful insight on ML/AI/self-driving?

https://benwheatley.github.io/blog/2024/03/11-12.00.16.html

[ben_w]

1. Note time stamp: https://github.com/BenWheatley/char-rnn

2. Most ML is basic calculus and basic linear algebra — to the extent that people who don't follow it, use that fact itself as a shallow argument.

3. I'm not asserting how fast it can advance, I'm asserting that the comparison with "6 million years of evolution" is a as much a shallow hand-wave as saying it's trivial, as evidenced by what we've done so far.