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this post was submitted on 15 May 2024
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Big brain tech dude got yet another clueless take over at HackerNews etc? Here's the place to vent. Orange site, VC foolishness, all welcome.
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That’s like saying a person reading a book before a quiz is doing it open book because they have the memory of reading that book.
I'm not even going to engage in this thread cause it's a tar pit, but I do think I have the appropriate analogy.
When taking certain exams in my CS programme you were allowed to have notes but with two restrictions:
The idea was that you needed to actually put a lot of work into making it, since the entire material was obviously the size of a fucking book and not an A4 page, and you couldn't just print/copy it from somewhere. So you really needed to distill the information and make a thought map or an index for yourself.
Compare that to an ML model that is allowed to train on data however long it wants, as long as the result is a fixed-dimension matrix with parameters that helps it answer questions with high reliability.
It's not the same as an open book, but it's definitely not closed book either. And the LLMs have billions of parameters in the matrix, literal gigabytes of data on their notes. The entire text of War and Peace is ~3MB for comparison. An LLM is a library of trained notes.
My question to you is how is it different than a human in this regard? I would go to class, study the material, hope to retain it, so I could then apply that knowledge on the test.
The ai is trained on the data, "hopes" to retain it, so it can apply it on the test. It's not storing the book, so what's the actual difference?
And if you have an answer to that, my follow up would be "what's the effective difference?" If we stick an ai and a human in a closed room and give them a test, why does it matter the intricacies of how they are storing and recalling the data?
I mean, if we took all net worth of Sam Altman and split it between these two guys who at least benefited humanity with their work we'd get at least a step closer to justice in the universe.
Getting a Turing award: $1M
Dropping out of Stanford to work on something unironically called "Loopt": Priceless