What can LLMs never do? • Hacker News Board

Re: What can LLMs never do?

#291

Post by scoot » Sun, Apr 28, 2024, 1:08 PM UTC

Al-Khwarizmi wrote: post #264

rainsford wrote: post #177

Earlier quoted context omitted.

Arriving at a generally accepted scientific definition of AGI might be difficult, but a more achievable goal might be to arrive at a scientific way to determine something is not AGI. And while I'm not an expert in the field, I would certainly think a strong contender for relevant criteria would be an inability to process information in a way other than the one a system was explicitly programmed to, even if the new wa…

An LLM doesn't even see individual letters at all, because they get encoded into tokens before they are passed as input to the model. It doesn't make much sense to require reasoning with things that aren't even in the input as a requisite for intelligence. That would be like an alien race that could see in an extra dimension, or see the non-visible light spectrum, presenting us with problems that we cannot even see a…

And yet ChatGPT 3.5 can tell me the nth letter of an arbitrary word…

Re: What can LLMs never do?

#292

Post by Etherlord87 » Sun, Apr 28, 2024, 1:09 PM UTC

throwthrowuknow wrote: post #286

SomeCallMeTim wrote: post #136

Earlier quoted context omitted.

LLMs are good at tasks that don't require actual understanding of the topic. They can come up with excellent (or excellent-looking-but-wrong) answers to any question that their training corpus covers. In a gross oversimplification, the "reasoning" they do is really just parroting a weighted average (with randomness injected) of the matching training data. What they're doing doesn't really match any definition of "und…

What is your definition of understanding? Please show me where the training data exists in the model to perform this lookup operation you’re supposing. If it’s that easy I’m sure you could reimplement it with a simple vector database. Your last two paragraphs are just dualism in disguise.

I'm far from being an expert on AI models, but it seems you lack the basic understanding of how these models work. They transform data EXACTLY like spreadsheets do. You can implement those models in Excel, assuming there's no row or column limit (or that it's high enough) - of course it will be much slower than the real implementations, but OP is right - LLMs are basically spreadsheets.

Question is, wouldn't a brain qualify as a spreadsheet, do we know it can't be implemented as one? Well, maybe not, I'm not an expert on spreadsheets either, but I think spreadsheets don't allow you circular references, and brain does, you can have feedback loops in the brain. So even if the brain doesn't have something still not understood by us, that OP suggests, it still is more powerful than AI.

BTW, this is one explanation on why AI fails at some tasks: ask AI if two words rhyme and it will be quite reliable on that. But ask it to give you word pairs that rhyme, and it will fail, because it won't run an internal loop trying some words and checking if they succeed to rhyme or not. If some AI actually succeeds at rhyming, it would do so either because it's trained to contain such word pairs from the get-go or because it's implemented to have multiple passes or something...

Re: What can LLMs never do?

#293

Post by fragmede » Sun, Apr 28, 2024, 1:13 PM UTC

kromem wrote: post #239

fragmede wrote: post #161

Earlier quoted context omitted.

interestingly enough, it seems that ChatGPT-4 can now detect the variations of the classic logic puzzle and solve it, so that can't is now a couldn't .

We may be talking about different logic puzzles? The only model I've seen that didn't need some rather extreme adjustments to eventually solve it was Mistral large.

what's your puzzle? mines the river crossing puzzle

Re: What can LLMs never do?

#294

Post by card_zero » Sun, Apr 28, 2024, 1:19 PM UTC

jncfhnb wrote: post #273

adrianN wrote: post #233

Earlier quoted context omitted.

I try my best not to experience continuous time for at least eight hours a day.

Then for at least eight hours a day you don’t qualify as a generally intelligent system.

If I spend some amount of the day bathing, some amount of it scratching, some amount of it thinking vaguely about racoons without any clear conclusions, and a lot of it drinking tea, I wonder how many seconds remain during which I qualified as generally intelligent.

Re: What can LLMs never do?

#295

Post by patching-trowel » Sun, Apr 28, 2024, 1:28 PM UTC

joshspankit wrote: post #290

As I was reading, this voice got louder and louder: Would LLMs cross this threshold if we were able to train them only on works that are “objectively good”? if someone has better language than this, please enlighten me) That is to say: coherent, empathetic, transparent, free from bias, substantiated, free from “fluff”. For example: For science one cannot simply train from all works published in scientific journals be…

My gut says no because of the way language relates to meaning. In language, a “chair” is a chair is a chair. But in meaning, a chair is not-a-stool, and not-a-couch, and not-a-bench etc. We understand the object largely by what the object is similar to but not.

In order for the LLM to meaningfully model what is coherent, empathetic, free from bias, it must also model the close to, but NOT-that.

Re: What can LLMs never do?

#296

Post by layer8 » Sun, Apr 28, 2024, 1:29 PM UTC

furyofantares wrote: post #288

baobabKoodaa wrote: post #201

Earlier quoted context omitted.

What parent is saying is that instead of asking the LLM to play a game of Wordle with tokens like TIME,LIME we ask it to play with tokens like T,I,M,E,L. This is easy to do.

And if you tell it to think up a word that has an E in position 3 and an L that's somewhere in the word but not in position 2, it's not going to be any better at that if you tell it to answer one letter at a time.

The idea is, instead of five-letter-words, play the game with five-token-words.

Re: What can LLMs never do?

#297

Post by throwthrowuknow » Sun, Apr 28, 2024, 1:32 PM UTC

Etherlord87 wrote: post #292

throwthrowuknow wrote: post #286

Earlier quoted context omitted.

What is your definition of understanding? Please show me where the training data exists in the model to perform this lookup operation you’re supposing. If it’s that easy I’m sure you could reimplement it with a simple vector database. Your last two paragraphs are just dualism in disguise.

I'm far from being an expert on AI models, but it seems you lack the basic understanding of how these models work. They transform data EXACTLY like spreadsheets do. You can implement those models in Excel, assuming there's no row or column limit (or that it's high enough) - of course it will be much slower than the real implementations, but OP is right - LLMs are basically spreadsheets. Question is, wouldn't a brain…

You can implement Doom in a spreadsheet too, so what? That wasn’t the point op or I were making. If you bother to read the sentence before op talks about spreadsheets they are making the conjecture that LLMs are lookup tables operating on the corpus they were trained on. That is the aspect of spreadsheets they were comparing them to, not the fact that spreadsheets can be used to implement anything that any other programming language can. Might as well say they are basically just arrays with some functions in between, yeah no shit.

Which LLMs can’t produce rhyming pairs? Both the current ChatGPT 3.5 and 4 seem to be able to generate as many as I ask for. Was this a failure mode at some point?

Re: What can LLMs never do?

#298

Post by Etherlord87 » Sun, Apr 28, 2024, 1:35 PM UTC

naasking wrote: post #282

iraqmtpizza wrote: post #280

Earlier quoted context omitted.

Endless ink has been spilled on the most banal and useless things. Deconstructing ice cream and physical beauty from a Marxist-feminist race-conscious postmodern perspective.

Except one is clearly a niche question, and the other has repeatedly captured the world's imagination and spilled orders of magnitude more ink.

Is it interesting to ponder if the Earth is flat?

Re: What can LLMs never do?

#299

Post by naasking » Sun, Apr 28, 2024, 1:52 PM UTC

> They have been trained on more information than a human being can hope to even see in a lifetime. Assuming a human can read 300 words a min and 8 hours of reading time a day, they would read over a 30,000 to 50,000 books in their lifetime. Most people would manage perhaps a meagre subset of that, at best 1% of it. That’s at best 1 GB of data.

This just isn't true. Human training is multimodal to a degree far beyond even the most capable multimodal model, so human babies arguably see more data by a young age than all models collectively have seen.

Not to mention that human babies don't even start as a blank slate as LLMs do, billions of years of evolution have formed the base model described by our DNA.

Re: What can LLMs never do?

#300

Post by furyofantares » Sun, Apr 28, 2024, 1:55 PM UTC

layer8 wrote: post #296

furyofantares wrote: post #288

Earlier quoted context omitted.

And if you tell it to think up a word that has an E in position 3 and an L that's somewhere in the word but not in position 2, it's not going to be any better at that if you tell it to answer one letter at a time.

The idea is, instead of five-letter-words, play the game with five-token-words.

That was my original interpretation, and while all it sees are tokens, roughly none of its training data is metadata about tokenizing. It knows far less about the positions of tokens in words than it does about the positions of letters in words.