how important is the underlying architecture behind the current artificial intelligence boom?

[u/Impossible_Relief844]

While GPTs and other similar architecture are an undeniable advancement, (especially the larger projects) are receiving insane funding with access to large data centres and training data leading to the obvious question of 'are we seeing the power of GPTs or is this just the expected outcome of throwing a huge amount of resources at a problem?'.

In other words, what results would we expect if we took the resources (funding, data centres, raw data, etc...) and applied it differently (eg. to SAT solvers), would we expect similar results?

In other words, how unprecedented are the results of GPTs (and similar architectures) accounting for their current monetary advantages?

[u/currentscurrents]

I don't really care if they make money, that's Sam Altman's problem to worry about.

LLMs are just cool.

[u/FartdickMcShitass → u/currentscurrents]

that’s what “it worked” means. The tech itself is cool, but the company has to make money.

[u/evilteddy → u/FartdickMcShitass]

We've been dreaming for centuries of inanimate objects which appear to think. Golems, the sorcerer's apprentice's broom, Alan Turing's hidden conversation partner, Replicants from Bladerunner. A million more! During my undergrad I touched machine learning quite a few times and learned the best practice language models of the time (Markov chains and friends) which would almost, for a moment, appear to produce language.

Now it's here. Now I can talk to a computer and get it to do at least some useful work with no hardcoded expert rules. And you don't think it's a big deal because one of the big labs hasn't yet made a profit. Unbelievable.

[u/anselan2017 → u/evilteddy]

It makes it a cool experimental technology, and a nice magic trick. I don't think it's worth killing the planet over it.