[MatejKafka]

I don't think it's about trying to handwave away the achievement. The problem is that many AI proponents, and especially companies producing the LLM tools constantly overstate the wins while downplaying the issues, and that leads to a (not always rational) counter-reaction from the other side.

[D-Machine]

It is especially glaring in this case because, when queried, it is clear that far too many of the most zealous proponents don't even understand the simplest basics of how these models actually work (e.g. tokenization, positional or other encoding schemes, linear algebra, pre-training, basic input/output shaping/dimensions, recursive application, training data sources, etc).

There are simple limitations that follow from these basic facts (or which follow with e.g. extreme but not 100% certainty), such that many experts openly state that e.g. LLMs have serious limitations, but, still, despite all this, you get some very extreme claims about capabilities, from supporters, that are extremely hard to reconcile with these basic and indisputable facts.

That, and the massive investment and financial incentives means that the counter-reaction is really quite rational (but still potentially unwarranted, in some/many practical cases).

[NegativeK]

The same crap happened with cryptocurrency: it was either aggressively pro or aggressively against, and everyone who could be heard was yelling as loud as they could so they didn't have to hear disagreement.

There is no loud, moderate voice. It makes me very tired of the blasting rhetoric that invades _every_ space.

[MatejKafka]

https://simonwillison.net/ is a pretty loud and moderate voice in the community. Also active on Lobste.rs: https://lobste.rs/~simonw

But agree that there's an irrational level of tribalism on both sides.