[shanehoban]

This is a valid point, but we are still in the early stages of AI/LLMs, so one would expect the speed and efficiency to improve drastically (perhaps accuracy too) over the coming years.

At least AI & LLMs have large scale practical applications as opposed to crypto (IMO).

[AlchemistCamp]

AI is a lot older than blockchain. There were full-fledged neural networks in the 40s and the perceptron was implemented in hardware in the 50s.

[IshanMi]

It's also interesting to think that IBM released an 8-trillion parameter model back in the 1980s [0]. Granted it was an n-gram model so it's not exactly an apples-to-apples comparison with today's models, but still, quite crazy to think about.

[0]: https://aclanthology.org/J92-4003.pdf

[lukeschantz]

Interesting to see Robert Mercer the former CEO of Renaissance Technology is one of the authors on that paper. He is a former IBMer. If his name is unfamiliar he is a reclusive character who was a major funder of Breitbart, Cambridge Analytica and the Republican candidate in the 2016 presidential election.

[varjag]

I wouldn't call the early McCulloch & Pitts work quite "full-fledged". Also backpropagation, essential for multi level perceptrons was not a thing until 1980s.

[samus]

Backprop is just applied calculus. People simply didn't think about using it for neuronal networks yet.

[varjag]

It was thought of as early as in 1960s by Rosenblatt but he did not come up with a practical implementation at the time. Lotsa things look obvious in hindsight.