And at least with Moore's law, we had some understanding of the physical realities as transistors would get smaller and smaller, and reasonably predict when we'd start to hit limitations. With LLMs, we just have no idea. And that could be go either way.
Not from me you haven't!
> "they've hit a wall, no more data, running out of data, plateau this, saturated that"
Everyone thought Moore's Law was infallible too, right until they hit that bend. What hubris to think these AI models are different!
But you've probably been hearing that for 3 years too (though not from me).
> Models keep on getting better, at more broad tasks, and more useful by the month.
If you say so, I'll take your word for it.
Since then, all improvements came at a tradeoff, and there was a definite flattening of progress.
Intel, at the time the unquestioned world leader in semiconductor fabrication was so unable to accurately predict the end of Dennard scaling that they rolled out the Pentium 4. "10Ghz by 2010!" was something they predicted publicly in earnest!
It, uhhh, didn't quite work out that way.
Idk, that sounds remarkably similar to these AI models to me.
I dunno. To me it doesn’t even look exponential any more. We are at most on the straight part of the incline.
SWE's may be seeing benefit. But in other areas? Doesnt seem to be the case. Consumers may use it as a more preferred interface for search - but this is a different discussion.