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A 7-minute LLM explainer (part of a Computer History Museum exhibit)

🕑 Added 2024-10-23 14:32:30 +0000 UTC

Comments

3blue1brown

I know it’s far from perfect, but what did you think of the video on attention I made? What points would you most like to see explained better?

Hitoshi Yamauchi

Nice. Thank you!

Casey Miller

Excellent introduction without overwhelming the consumer. Just enough to pique interest to want to learn more (the point of a museum).

Kyle M. Kabasares

I live so close to the Computer History Museum but haven’t been there before! Definitely need to check it out

David Terr

This is truly amazing! I'm convinced, as I've been for the past year or so, that with systems like this, AI has already passed the Turing Test. However, although I think the latest AI systems are highly intelligent, I don't think they're sentient, since they still follow classical, i.e., deterministic, algorithms, so they're still effectively our slaves and they don't care about that. However, I do believe that quantum computers could become sentient, and in fact, I think quantum mechanical uncertainty is ultimately the source of consciousness, so if we ever develop quantum computers with these capabilities, we'll need to treat them with respect, as we should with our fellow human beings. What are your thoughts about all this?

Albert Farve

I wonder if we’ll soon (or ever) see an LLM that can dynamically train itself. I.E., after pre-training it can continue to adjust its weights. After all, the human brain is continuously adjusting its own synapses (esp. during sleep). Perhaps this would be too computationally expensive to be practical? But for machines that can truly learn on the fly, I think that would be a prerequisite.

A Patreon of the Ahts

That's pretty good But I still haven't had attention explained to my satisfaction yet.I miss martin gardner , he would have done that.

Fran Abenza

this should be "Part 0"

Rick Rubenstein

One tiny note: near the end you refer to "the last vector in this sequence", but I don't think you had defined "vector" earlier in the video (unless I missed it); you just said "list of numbers".

Rick Rubenstein

Very nice! I live quite near the CHM, but haven't been in in ages. I should rectify that.

Ama

Brilliant! Your contribution to improve global human knowledge and understanding is unmatched. I'm so grateful for everything you've done. Thank you !

Richard Hackathorn

Amazing!!! If more people would understand these short seven minutes of simple clear explanation, we would have considerably less craziness in the AI media.

Gabriel Bergqvist

Wonderful. As usual.

Daniel Raynaud

Brilliant (as always).

dcy665 .

Nicely done. One of the better, or the best thus far, of explainers of LLM based AI As an, I don't know, not impressed observer of "AI" based on LLM, I cannot help but recall the many stories, rarely good, from throughout its actual history First was fuzzy logic, programmers made them, which were a MUCH simpler version of the pre-training (essentially, one column of numbers only). Then that begat neural Networks (more columns), which begat Machine Learning (even more columns). Then, more recently, Machine Learning using the technique called "AI" begat LLM. As a programmer for a quarter+ century, the problem I've always had with it was nobody can explain why it pops out the wrong answer. Never have. Never will. You simply cannot guarantee it will do anything correctly. The tendency to hallucinate means you should never trust the answer. The answers are ONLY a statistically high value that "would sound good in a conversation" which is quite a bit different from "the correct answer". Which explains why various ChatBots were convinced to be racists a few years ago As they say, but that's just me