Live data from Hacker News

Compression is prediction

ngrok.com

61–70 of 322 posts

Re: Compression is prediction

#61
post #15

This perspective is a useful source of intuition against the “LLMs can’t have new ideas, they’re just next-token-predictors” style arguments. What if you shift your perspective to thinking of training as optimization over a vast parametrized family of compression algorithms? Well, it suddenly looks a lot more plausible that “new” “ideas” can emerge from that process!

> it suddenly looks a lot more plausible that “new” “ideas” can emerge from that process This is not intuitive to me. It seems like a "new idea" is something that (almost by definition) isn't in the training set. Can you elaborate a bit? Edit: but perhaps a good model could arise from training, which would be a good idea in the sense that parsimonious ideas are good scientific ideas.

An idea is a construction on existing concepts, a newer idea links more previously unlinked concepts.

Re: Compression is prediction

#62
post #48

This is the thesis behind the "Information Theory, Inference, and Learning Algorithms" course that was taught at Cambridge University. > Why unify information theory and machine learning? Because they are two sides of the same coin. In the 1960s, a single field, cybernetics, was populated by information theorists, computer scientists, and neuroscientists, all studying common problems. Information theory and machine l…

I had a long ranting comment I deleted. I just don't like this trend of people presenting work in a way that makes you think some combo of 1) they discovered from scratch themselves 2) it's new 3) they didn't try to cite or acknowledge where they learned it/point to good sources 4) they don't really care about trying to teach something deeply, they want shiny stuff that makes them seem deep. This post references spec…

And yet to this day, in AI threads, so many people act shocked and surprised if you dare follow the obvious implication and claim that understanding is a form of lossy compression.

Re: Compression is prediction

#63
post #51

Compression is not prediction, it is recall. Can we make predictions based on compression? Absolutely. Is memory encoded into physical neurons technically compression? I would argue also yes. However, going from compression to prediction is a large jump that is unsubstantiated by this article and based on the claim that probabilistic recall is also prediction. Two perfect counterpoints to this are markets and weather…

I know less about this than every other commenter here, but both weather patterns and market performance do seem predictable based on past behavior when modeled at the right level of abstraction. “Sunshine on Monday” does not imply “rain on Tuesday”, but “cold front moving in Monday night” does. (Likewise “stock up Monday” doesn’t imply “stock down Tuesday” but “CEO arrested for fraud on Monday” does.) I think this i…

Good points. I looked up the definition for prediction and I suppose I'm stretching what I view as prediction.

> A prediction is a statement about what you think will happen in the future, often based on experience or knowledge. It can also be referred to as a forecast or an informed guess

Based on my reading of this definition, compression may inform prediction but it is not itself prediction. The examples cited in the blog post are examples of probabilistic recall based on past events or instances. More context means a higher chance that the recall is more likely to be aligned.

But it's hard for me to accept the leap to compression == prediction because in my mind a prediction is an informed guess about something that hasn't yet come to pass. But thinking more about it, time is a human concept and so who's to say the temporal reference means anything at all here. Maybe probabilistic recall is the same as predictive forecasting if time is an invented concept and essentially means nothing?

Is everything fundamentally deterministic if you know everything in the universe or does free will exist?

IDK to be honest, I'm just more frequently surprised by new things that happen every day than I am at things that stay the same, even if mostly things stay the same. Maybe I just don't notice them and nothing actually ever happens.

Side note: the inevitable consequence of this line of reasoning will eventually become that LLMs given enough power are in fact intelligent and sentient, and I'm worried about how that affects humanity as a whole. Are we about to subjugate the most intelligent thing humanity has ever created, or is it about to subjugate us?

The rabbit hole gets deep quick when making the leap between a fancy recall mechanism and novel prediction, but I agree they're not that different in the end. I just believe it's important to be nuanced or else we'll miss when AGI actually happens (maybe it's already here).

Re: Compression is prediction

#64
i do agree with that point of view. I often referred to models as 'modern mp3s' storing a lossfull but lookalike version of information in order to counter that 'AI is totally new and not violating copyright by storing information in a magic fashion' argument.

Re: Compression is prediction

#66
post #14

Nope; there is a bit more nuance and the distinction is important. Compression is functionally equivalent to prediction when the data distribution is exactly representative of all future problems . The story changes drastically if you want generalization -- because the test distribution could be arbitrarily different, even if it had the same support ! Eg: you observe a rare edge case in your training data and (lossy)…

Compression is still prediction, the predictions just might not be good.

Re: Compression is prediction

#68
How about dictionary based compression as a counter example? Or the zig zag encoding scheme used in JPEG? I find it difficult to cast some of the things that effectively compress data as prediction.

Re: Compression is prediction

#70
post #51

Compression is not prediction, it is recall. Can we make predictions based on compression? Absolutely. Is memory encoded into physical neurons technically compression? I would argue also yes. However, going from compression to prediction is a large jump that is unsubstantiated by this article and based on the claim that probabilistic recall is also prediction. Two perfect counterpoints to this are markets and weather…

I know less about this than every other commenter here, but both weather patterns and market performance do seem predictable based on past behavior when modeled at the right level of abstraction. “Sunshine on Monday” does not imply “rain on Tuesday”, but “cold front moving in Monday night” does. (Likewise “stock up Monday” doesn’t imply “stock down Tuesday” but “CEO arrested for fraud on Monday” does.) I think this i…

> Likewise “stock up Monday” doesn’t imply “stock down Tuesday” but “CEO arrested for fraud on Monday” does

Stock market is even more pathological than weather here. Most statistical tools have baked-in assumptions about some degree of independence between factors under analysis. In weather, things are hard, because everything affects everything but in some random sense. With stock market, it's worse, because some things affect others in an adversarial way. A pattern discovered is not merely drowned in noise, but rather actively canceled out as other people discover and act on it. The way to describe this in formal terms is, I believe, that the stock market is "anti-inductive".

Fortunately, most things we deal with life are much friendlier to predictions than weather or stock prices.

> I think people are seeing

Better late than never, given that this has been empirically demonstrated two years ago by Anthropic. I actually don't understand why people don't make a bigger deal out of it - maybe it's because the AI hype/hate fight is sucking all attention from the room. But the point is: we not only have a thing that can learn concepts we recognize and build abstract world model, but also we have a degree of visibility and control of it we never had before. We can't see, much less suppress or stimulate individual concepts or concept groups in a human brain directly, but we can with LLMs.

Post reply on HN