[ben_w]

> LLMs are not accurate, they aren't subject matter experts that'll be maybe within 5% error margin.

The Gell Mann amnesia effect suggests people will have a very hard time noticing the difference. Even if the models never improve, they're more accurate than a lot of newspaper reporting.

> People will gradually learn and discover anf the cost of keeping a model updated and running won't drastically reduce so we'll most likely see dust settling down.

So, you're betting on no significant cost reduction of compute hardware? Seems implausible to me.

[nativeit]

> …they’re more accurate than a lot of newspaper reporting.

Is that when they’re cribbing straight out of the newspaper pages, or is this just a cynical snipe at the poor state of media that, not for nothing, tech companies have had a fair hand in kneecapping?

[ben_w]

The criticism of the performance of newspapers goes back well before Lovelace and Babbage:

"""I will add, that the man who never looks into a newspaper is better informed than he who reads them; inasmuch as he who knows nothing is nearer to truth than he whose mind is filled with falsehoods & errors. He who reads nothing will still learn the great facts, and the details are all false."""

- Thomas Jefferson (not Mark Twain), 1807, https://www.snopes.com/fact-check/mark-twain-read-newspaper-...

[thesz]

> So, you're betting on no significant cost reduction of compute hardware? Seems implausible to me.

This is not about compute, but about data.

https://arxiv.org/abs/2404.04125

"...our study reveals an exponential need for training data which implies that the key to "zero-shot" generalization capabilities under large-scale training paradigms remains to be found."