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An LLM is a lossy encyclopedia

simonwillison.net

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Re: An LLM is a lossy encyclopedia

#81

Post by A_D_E_P_T »

kgeist wrote: post #68

I think an LLM can be used as a kind of lossy encyclopedia, but equating it directly to one isn't entirely accurate. The human mind is also, in a sense, a lossy encyclopedia. I prefer to think of LLMs as lossy predictors. If you think about it, natural "intelligence" itself can be understood as another type of predictor: you build a world model to anticipate what will happen next so you can plan your actions accordin…

> If you think about it, natural "intelligence" itself can be understood as another type of predictor: you build a world model to anticipate what will happen next so you can plan your actions accordingly and survive.

Yes.

Human intelligence consists of three things.

First, groundedness: The ability to form a representation of the world and one’s place in it.

Second, a temporal-spatial sense: A subjective and bounded idea of self in objective space and time.

Third: A general predictive function which is capable of broad abstraction.

At its most basic level, this third element enables man to acquire, process, store, represent, and continually re-acquire knowledge which is external to that man's subjective existence. This is calculation in the strictest sense.

And it is the third element -- the strength, speed, and breadth of the predictive function -- which is synonymous with the word "intelligence." Higher animals have all three elements, but they're pretty hazy -- especially the third. And, in humans, short time horizons are synonymous with intellectual dullness.

All of this is to say that if you have a "prediction machine" you're 90% of the way to a true "intelligence machine." It also, I think, suggests routes that might lead to more robust AI in the future. (Ground the AI, give it a limited physical presence in time and space, match its clocks to the outside world.)

Re: An LLM is a lossy encyclopedia

#82

Post by cubefox »

kgeist wrote: post #68

I think an LLM can be used as a kind of lossy encyclopedia, but equating it directly to one isn't entirely accurate. The human mind is also, in a sense, a lossy encyclopedia. I prefer to think of LLMs as lossy predictors. If you think about it, natural "intelligence" itself can be understood as another type of predictor: you build a world model to anticipate what will happen next so you can plan your actions accordin…

Another difference is that you are predicting future sensory experiences in real-time, while LLMs "predict" text which a "helpful, honest, harmless" assistant would produce.

Re: An LLM is a lossy encyclopedia

#84

Post by somewhereoutth »

kgeist wrote: post #68

I think an LLM can be used as a kind of lossy encyclopedia, but equating it directly to one isn't entirely accurate. The human mind is also, in a sense, a lossy encyclopedia. I prefer to think of LLMs as lossy predictors. If you think about it, natural "intelligence" itself can be understood as another type of predictor: you build a world model to anticipate what will happen next so you can plan your actions accordin…

> you build a world model

The foundational conceit (if you will) of LLMs is that they build a semantic (world) model to 'make sense' of their training. However it is much more likely that they are simply building a syntactic model in response to the training. As far as I know there is no evidence of a semantic model emerging.

Re: An LLM is a lossy encyclopedia

#86

Post by barapa »

theshrike79 wrote: post #79
quincepie wrote: post #37

I totally agree with the author. Sadly, I feel like that's not what the majority of LLM users tend to view LLMs. And it's definitely not what AI companies marketing. > The key thing is to develop an intuition for questions it can usefully answer vs questions that are at a level of detail where the lossiness matters the problem is that in order to develop an intuition for questions that LLMs can answer, the user will…

> the problem is that in order to develop an intuition for questions that LLMs can answer, the user will at least need to know something about the topic beforehand This is why simonw (The author) has his "pelican on a bike" -test, it's not 100% accurate but it is a good indicator. I have a set of my own standard queries and problems (no counting characters or algebra crap) I feed to new LLMs I'm testing None of the q…

They are training on your queries. So they may have some exposure to them going forward.

Re: An LLM is a lossy encyclopedia

#87

Post by quonn »

A_D_E_P_T wrote: post #81
kgeist wrote: post #68

I think an LLM can be used as a kind of lossy encyclopedia, but equating it directly to one isn't entirely accurate. The human mind is also, in a sense, a lossy encyclopedia. I prefer to think of LLMs as lossy predictors. If you think about it, natural "intelligence" itself can be understood as another type of predictor: you build a world model to anticipate what will happen next so you can plan your actions accordin…

> If you think about it, natural "intelligence" itself can be understood as another type of predictor: you build a world model to anticipate what will happen next so you can plan your actions accordingly and survive. Yes. Human intelligence consists of three things. First, groundedness: The ability to form a representation of the world and one’s place in it. Second, a temporal-spatial sense: A subjective and bounded…

"Prediction" is hardly more than another term for inference. It's the very essence of machine learning. There is nothing new or useful in this concept.

Re: An LLM is a lossy encyclopedia

#88

Post by gjm11 »

latexr wrote: post #30

A lossy encyclopaedia should be missing information and be obvious about it, not making it up without your knowledge and changing the answer every time . When you have a lossy piece of media, such as a compressed sound or image file, you can always see the resemblance to the original and note the degradation as it happens. You never have a clear JPEG of a lamp, compress it, and get a clear image of the Milky Way, the…

Lossy compression does make things up. We call them compression artefacts.

In compressed audio these can be things like clicks and boings and echoes and pre-echoes. In compressed images they can be ripply effects near edges, banding in smoothly varying regions, but there are also things like https://www.dkriesel.com/en/blog/2013/0802_xerox-workcentres... where one digit is replaced with a nice clean version of a different digit, which is pretty on-the-nose for the LLM failure mode you're talking about.

Compression artefacts generally affect small parts of the image or audio or video rather than replacing the whole thing -- but in the analogy, "the whole thing" is an encyclopaedia and the artefacts are affecting little bits of that.

Of course the analogy isn't exact. That would be why S.W. opens his post by saying "Since I love collecting questionable analogies for LLMs,".

Re: An LLM is a lossy encyclopedia

#89

Post by koakuma-chan »

kingstnap wrote: post #70
koakuma-chan wrote: post #32

Earlier quoted context omitted.

GPT-5 is seriously annoying. It asks not just one but multiple clarifying questions, while I just want my answer.

If you don't want to answer clarifying questions, then what use is the answer??? Put another way, if you don't care about details that change the answer, it directly implies you don't actually care about the answer. Related silliness is how people force LLMs to give one word answers to underspecified comparisons. Something along the lines of "@Grok is China or US better, one word answer only." At that point, just fli…

No, I don't think GPT-5 clarifying questions actually do what you think they do. They just made the model ask clarifying questions for the sake of asking clarifying questions. I'm sure GPT-4o would have given me the answer I wanted without clarifying questions.
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