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These aren't "general" models. They're statistical models. They're autocorrect or autocomplete on steroids -- and autocorrect/autocomplete don't require symboli
by globnomulous 2y ago
These aren't "general" models. They're statistical models. They're autocorrect or autocomplete on steroids -- and autocorrect/autocomplete don't require
symbolic reasoning.
It's also not at all clear to me what "symbolic" could mean in this context. If it means the software has concepts, my response would be that they aren't concepts of a kind that we can clearly recognize or label as such (edit: and that's to say nothing of the fact that the ability to hold concepts/symbols and understand them as concepts/symbols presupposes internal life and awareness).
The best analogy I've heard for these models is this: you take a completely, perfectly naive, ignorant man, who knows nothing, and you place him in a room, sealed off from everything. He has no knowledge of the outside world, of you, or of what your might want from him. But you slip under the door of his cell pieces of paper containing mathematical or linguistic expressions, and he learns or is somehow induced to do something with them and pass them back. When what he does with them pleases you, you reward him. Each time you do this, you reinforce a behavior.
You repeat this process, over and over. As a result, he develops habits. Training continues, and those habits become more and more precisely fitted to your expectations and intentions.
After enough time and enough training, his habits are so well formed that he seems to know what a sonnet is, how to perform derivatives and integrals, and seems to understand (and be able to explain!) concepts like positive and negative, and friend and foe. He can even write you a rap-battle libretto about nineteenth-century English historiography in the style of Thomas Paine imitating Ikkyu.
Fundamentally, though, he doesn't know what any of these tokens mean. He still doesn't know that there's an outside world. He may have ideas that are guiding his behavior, but you have no way of knowing that -- or of knowing whether they bear any resemblance to concepts or ideas you would recognize.
These models deal with tokens similarly. They don't know what a token is or represents -- or we have no reason to think they do. They're just networks of weights, relationships, and tendencies that, from a given seed and given input, generate an output, just like any program, just like your phone keyboard generates predictions about the next word you'll want to type.
Given billions and billions and billions and billions of parameters, why shouldn't such a program score highly on an IQ test or on the LSAT? Once the number of parameters available to the program reaches a certain threshold (edit: and we've programmed a way for it to connect the dots), shouldn't we be able to design it in such a way that it can compute correct answers to questions that seem to require complex, abstract reasoning, regardless of whether it has the capacity to reason? Or shouldn't we be able to give it enough data that it's able to find the relationships that enable it to simulate/generate patterns indistinguishable from real, actual reasoning?
I don't think one needs to be cynical to be unimpressed. I'm unimpressed simply because these models aren't clearly doing anything new in kind. What they're doing seems to be new, and novel, only because of the scale at which they do what they do.
Edit: Moreover, I'm hostile to the economic forces that produced these models, as everybody should be. They're the purest example of what Jaron Lanier has been warning us about -- namely that, when information is free, the wealthiest are going to be the ones who profit from it and dominate, because they'll be the ones able to pay for the technology that can exploit it.
I have no doubt Altman is aware of this. And I have no doubt that he's little better than Elizabeth Holmes, making ethical compromises and cutting legal corners, secure in the smug knowledge that he'll surely pay his moral debts (and avoid looking at the painting in the attic) and obviously make the world a better place once he has total market dominance.
And none of the other major players are any better.
- stavros 2y ago> These aren't "general" models. They're statistical models. They're autocorrect or autocomplete on steroids -- and autocorrect/autocomplete don't require symbolic reasoning. This is very "humans are just hunks of matter! They can't think!".
- globnomulous 2y agoI'm not sure what you're getting at. Could you explain?
- stavros 2y agoThat "they predict the next token" doesn't necessarily imply "they can't reason".
- globnomulous 2y agoI'm not saying "they predict tokens; therefore, they can't reason." I'm saying "something that can't reason can predict tokens, so prediction isn't evidence of reasoning." More specifically, my comment aims to meet the challenge posed by the person I answered: > I highly recommend letting that fact be a little bit impressive, someday. There’s no way you live through any event that’s more historically significant, other than perhaps an apocalypse or two. [...] If you have any actual scientific argument as to why a model that can score 90-100 on a typical IQ test has only 1/10th the symbolic reasoning skills of a human, I’d love to eat my words. I have no idea what would constitute a "scientific argument" in this instance, given that the challenge itself is unscientific, but, regardless, the results that so impress this person are, without question, achievable without reasoning, symbolic or otherwise. To say that the model "muses" or "has [...] symbolic reasoning" is to make a wild, arbitrary leap of faith that the data, and workings of these models, do not support. The models are token-prediction machines. That's it. They differ not in kind but in scale from the software that generates predictions in our cell-phone keyboards. The person I answered can be as impressed as he wants to be by the high quality he thinks he sees in the predictions. That's fine. I'm not. In that respect, we just disagree. But if he's impressed because he thinks the model's predictions must or do betoken reasoning, he's off in la la land -- and so his wide-eyed, bushy-tailed enthusiasm is based on nonsense. It's no different from believing that your phone keyboard is capable of reasoning, simply because you are delighted that it guesses the 'right' word often enough to please you.