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Regression to the Mean: on LLMs and the quiet death of the new

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Re: Regression to the Mean: on LLMs and the quiet death of the new

#71

Post by krona »

orbital-decay wrote: post #60
krona wrote: post #28

The output of a GPT is an interpolation (an estimation of new data points inside the range of known data) rather than extrapolation (estimations outside that range). 99% of the time we don't need a true intellectual breakthrough to get the job done, and often 'new ideas' are simply riffs on or blends of old ones, like fashion or music genres. The worry to me, however, is that if society comes to rely on this form of…

>The output of a GPT is an interpolation (an estimation of new data points inside the range of known data) rather than extrapolation (estimations outside that range). That's a common meme but it's the opposite of true. Everything big models, not just transformers, mathematically do is extrapolation in the feature space, almost never interpolation. They're perfectly able of combining the ideas, although of course this…

> That's a common meme but it's the opposite of true.

But you're restating what I just wrote - We're training a status quo machine and the probability of anything outside that distribution rapidly drops to zero.

Re: Regression to the Mean: on LLMs and the quiet death of the new

#72

Post by NichoPaolucci »

adverbly wrote: post #10

Good potential for discussion here. I full agree with the underlying premise: This technology CANNOT be allowed to just give us more of the same, but lazily. It HAS TO be an empowering tool. It has to unlock NEW discoveries. For the purpose of discussion though, this also undersells AIs: 1. They CAN be great tools for novelty + discovery! You just need to ask and explore and put in work. Its not "easy", but it does h…

I agree with this sentiment.

Many folks have touted the "calculator" similarities as an argument, saying it's more of an efficiency gain / productivity enhancer. To me, LLMs are far more involved than this. Now, unknowingly (or knowingly), people are offloading the problem solving portion of small tasks.

- Creative Writing (Claude, make this email sound more professional)

- Coding (Handle this small logic bug for me)

- Note Taking (Generate a summary of this meeting recording)

- Strategy (Set up a roadmap for X project) and many other areas

- Design (Give me a powerpoint for a stakeholder meeting)

- Personal Life (Find a restaurant I can take my wife to for our anniversary)

Many people underestimate how many "simple" tasks required creative problem solving abilities, and we're actively handing more and more of that over to the thinking machine.

Perhaps it's human nature to give this up, and maybe it's in our best interests - but this is the first time I've ever seen people stop thinking for themselves en masse. Interesting times ahead, IMO.

Re: Regression to the Mean: on LLMs and the quiet death of the new

#73

Post by ux266478 »

phillipcarter wrote: post #45
zwischenzug wrote: post #14

This touches on something I've (and many others) have felt throughout my life, not just since the advent of LLMs. To take a simple example: I grew up with computer games in the '80s where there were no 'physics engines' or frameworks for building games. As a result, each game was an expression of the author's personality somehow. Fast forward to the noughties, games bored me as they mostly looked and felt the same, o…

> Or am I just getting old? Perhaps? But I think this is more a case of just not seeking things out. Music is as vibrant and diverse as ever, but not if you're only looking at the top charts run by the music industry. Same deal with games, there's more experimentation and interesting concepts in gaming than ever before, but not from the AAA studios. Now I can't speak for how you vacation, but I've had wonderfully dif…

> Same deal with games, there's more experimentation and interesting concepts in gaming than ever before, but not from the AAA studios.

I just wanted to add on to this, I wouldn't really classify modern games as "lower quality" than those of the 80s. I'm really not a fan of AAA games, I think the last one I played was Elden Ring, but I would never suggest that they're actively low quality. Uncompelling? Absolutely. But I also have spent a lot of time playing games from the 80s. Silver and golden age CRPGs, random simulators, DOS games that catch my eye. "Quality" isn't the first thing that jumps to my mind. Often they're ugly, terribly balanced, buggy, rife with all sorts of issues in any category you can think of. Games have come a very, very long way. 2400 AD (1988) and Champions of Krynn (1990) are relatively speaking highly polished masterpieces. They're still kusoge, honestly. I have very little experience with the consoles of that era, because pretty much nothing I see even remotely catches my eye.

Re: Regression to the Mean: on LLMs and the quiet death of the new

#74

Post by kolinko »

aerodexis wrote: post #69
orbital-decay wrote: post #60

Earlier quoted context omitted.

>The output of a GPT is an interpolation (an estimation of new data points inside the range of known data) rather than extrapolation (estimations outside that range). That's a common meme but it's the opposite of true. Everything big models, not just transformers, mathematically do is extrapolation in the feature space, almost never interpolation. They're perfectly able of combining the ideas, although of course this…

so you're saying the difference b/w extrapolation and interpolation is subjective unless the difference is defined tautologically?

There isn’t a big difference between interpolation and extrapolation when the space has an immense amount of dimensions, and when you are free to modify the space at will.

Re: Regression to the Mean: on LLMs and the quiet death of the new

#76

Post by kolinko »

lmeyerov wrote: post #33

I've been calling this Software Collapse It's the same problem that AI faces of Model Collapse: AIs that train on the internet ultimately just end up training on one another, stop moving forward, and end up as identical polished versions of one another I now think of it as a Dr. Jekyll/ Mr. Hyde situation for software projects: - Dr. Jekyll: For makers, the only limit is your imagination, architectural guidance, and…

That is not true - a model trained in the internet can both build verifiers to remove false/poor quality data from the next training, and build synthetic datasets that will supplement its training.

Similar to a human that wants to learn something and invents exercises to practice.

1-2 years ago it was a theory, but new models are trained, successfully, on synthetic datasets.

Re: Regression to the Mean: on LLMs and the quiet death of the new

#77

Post by HarHarVeryFunny »

beyonddream wrote: post #40

The recent breakthrough of llm’s solving major open problem’s in math is a direct contradiction to the article. But, there is some truth to the article and perhaps it is more true in chat based interactions. The agentic, hands-off mode might tell a different story.

> The recent breakthrough of llm’s solving major open problem’s in math is a direct contradiction to the article.

I disagree. LLMs are essentially trained on all the math we know, as well as - via RL training - how we apply it to solve given types of problems.

It should be obvious that not every known mathematical technique, or sequence of techniques, have yet been tried by humans to solve every unproven conjecture, so necessarily there is some amount of low hanging fruit where an automaton tasked with throwing the kitchen sink at a problem will be successful. This is not the same as creativity.

If you are familiar with the mathematical notion of a closure, then what LLMs are capable of is generating the generative closure of what they were trained on. They can generate output that is novel in the sense of a sequence of chess moves, or mathematical moves, that was not - as a sequence - in the training set, but yet it WAS in the training set as part of the implicit closure of what an LLM would be capable of generating.

Re: Regression to the Mean: on LLMs and the quiet death of the new

#78

Post by kolinko »

krona wrote: post #57
kolinko wrote: post #54

This is a recurring sentiment but flawed, I think. First of all, neural nets do nit return averages per se. They construct space between the points and extrapolate outside of the points. So even if a point was not in their training data, they will be ok, in many situations, to acknowledge it. Or in other words - LLMs don’t average. They construct world models. A novel thing that fits their world model will be accepte…

> They construct space between the points and extrapolate outside of the points. They don't. They interpolate between the points on a manifold.

Manifold vs space - yes, I meant manifold, english is not my first language and I missed this word.

The argument stands.

Re: Regression to the Mean: on LLMs and the quiet death of the new

#79

Post by zwischenzug »

phillipcarter wrote: post #45
zwischenzug wrote: post #14

This touches on something I've (and many others) have felt throughout my life, not just since the advent of LLMs. To take a simple example: I grew up with computer games in the '80s where there were no 'physics engines' or frameworks for building games. As a result, each game was an expression of the author's personality somehow. Fast forward to the noughties, games bored me as they mostly looked and felt the same, o…

> Or am I just getting old? Perhaps? But I think this is more a case of just not seeking things out. Music is as vibrant and diverse as ever, but not if you're only looking at the top charts run by the music industry. Same deal with games, there's more experimentation and interesting concepts in gaming than ever before, but not from the AAA studios. Now I can't speak for how you vacation, but I've had wonderfully dif…

On cities, I guess my point is that I didn't have to seek out new experiences. Simply going there guaranteed new experiences. I spent a lot of time in Vienna growing up and everything was different. I literally couldn't have a familiar experience even if I'd wanted to. In fact, I remember having to spend lots of money and travelling a long way to find a specialised shop to get a familiar food item (baked beans) to relieve the homesickness.

I don't think people under a certain age can really appreciate how different it was.

Re: Regression to the Mean: on LLMs and the quiet death of the new

#80

Post by orbital-decay »

aerodexis wrote: post #69
orbital-decay wrote: post #60

Earlier quoted context omitted.

>The output of a GPT is an interpolation (an estimation of new data points inside the range of known data) rather than extrapolation (estimations outside that range). That's a common meme but it's the opposite of true. Everything big models, not just transformers, mathematically do is extrapolation in the feature space, almost never interpolation. They're perfectly able of combining the ideas, although of course this…

so you're saying the difference b/w extrapolation and interpolation is subjective unless the difference is defined tautologically?

I'm saying extrapolation as a mathematical concept is orthogonal to the non-rigorous definition of creativity.
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