5 ms·

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 to

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 3y ago
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.
- deleted 3y ago
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- IshanMi 3y ago
  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 https://aclanthology.org/J92-4003.pdf
  - lukeschantz 3y ago
    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 3y ago
  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 3y ago
    Backprop is just applied calculus. People simply didn't think about using it for neuronal networks yet.
    - varjag 3y ago
      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.