this post was submitted on 21 Oct 2024
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The sheer size of it and it's training data makes it hard to really say what it's doing. Like for an object that it wouldn't have come across in it's training data, a) how could they tell it was truly a new thing that had never been discussed anywhere on the internet where the training could have consumed it, and b) that any description provided for it didn't map it to another object that would behave similarly when stacking.
Stacking things isn't a novel problem. The internet will have many examples of people talking about stacking (including this one here, eventually). The put the flat part down for the nail could have been a direct quote, even. Putting a plank of wood at the bottom would be pretty common, and even the eggs and book thing has probably been discussed before.
I mean, I can't dismiss that it isn't doing something more complex, but examples like that don't convince me that it is. It is capable of very impressive things, and even if it needs to regurgitate every answer it gives, few problems we want to solve day to day are truly novel, so regurgitating previous discussions plus a massive set of associations means that it can map a pretty large problem space to a large solution space with high accuracy.
I'm having trouble thinking of ways to even determine if it can really problem solve that won't accidentally map to some similar discussion among nerds that like to go into incredible detail and are willing to speculate in any direction just for the sake of enjoying a thought experiment.
Like even known or suspected unsolvable problems have been discussed to greater levels of detail than I've likely considered them, so even asking it to do its best trying to solve the traveling salesman problem in polynomial time would likely impress me because computer science students and alums much smarter than I am have discussed it at length.
Sure, there is a chance the exact question had been asked before, and answered, but we are talking remote possibilities here.
If it has to say 'this item is like that other item and thus I can use what I've learned about stacking that other item to stack this item' then I would absolutely argue that it is reasoning and not just "predicting text" (or, again, predicting text might be the equivalent of reasoning).
Sure, stacking things is not a novel problem, which is why we have the word "stack" because it describes something we do. But stacking that list of things is (almost certainly) a novel problem. It's just you use what you've learned and apply that knowledge to this new problem. A non-novel problem is if I say "2+2 = 4" and then turn around and ask you "what does 2 + 2 equal?" (Assuming you have no data set) If I then ask you "what's 2 + 3?" that is a novel problem, even if it's been answered before.
How are you convinced that humans are reasoning creatures? This honestly sounds like you could be describing 99.99% of human thought, meaning we almost never reason (if not actually never). Are we even reasonable?
I don't mean it needs to be the exact question, just something with equivalence. If someone talked about stacking boards and other things, the board could go on the bottom and then maybe someone else talked about stacking balls and books that way, so it used that because "eggs" were associated with "round". Follow up with the nail thing from another conversation.
It's definitely a form of intelligence, but I don't think it's anywhere close to 99.9% of human thought. I think it's missing entire dimensions of thought.
I'm not saying it's 99.9% of human intelligence, I'm saying you're describing 99.9% of human thought.
This is what humans do, we hear about something thing and then we learn how to apply it to another. You even mention here "stacking balls" and then making the connection that eggs are also round and would need to be stacked in the same way to prevent rolling. This is reasoning, using what you've learned and applying it to a novel problem.
What you are describing as novel problems are really just doing the same thing at a completely different level. Like I play soccer, but no matter how much I trained, there is no way I would ever reach Messi's skill, because he was just born with special skill in that area, but still just human like the rest of us.
And remember I'm mostly just pointing to the "text predictor" claim. I'm not convinced it's not, and I think that appeared true for early models, but not so easy to apply to current models.
Yeah, it is hard to say if the "glorified text predictor" is completely accurate, since the sheer size of the model allows for some pretty deep connections.
And, thinking about it since making that post, it's hard to say for sure that even Einstein or Newton were doing anything differently or were just the first/most famous to put those particular things together.
It's a weird world and cool to think about. Thanks for the civil and interesting discussion.
Yeah, it was a good talk. Funny watching the sentiment of the voters throughout, too.
IMO, one of the best QoL updates for Lemmy is to make the votes invisible.
I suggest the personal firmware update of stopping caring about downvotes. Then they just become interesting data points.
I dont personally care about downvotes, but those data points sure do shake my faith in humanity sometimes.
If I get downvotes without any reply, I generally assume I've angered some trogdolytes, similar to getting replies full of vitriol.
Which has helped with my own urges to rage reply.
Yeah for me it's less that I rage about getting downvoted, its just when I see a massive number of downvotes for posts that are simply pointing to the facts, or being logical and rational...and they get a massive number of downvotes because it contradicts the circlejerk or what people want to be true.
Yeah, though on the bright side, it's not nearly as bad here as Reddit was. Based on votes and replies, it seemed like a non-trivial amount of people on there didn't have much skill in the reading comprehension or persuasion department.