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How LLMs work

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Re: How LLMs work

#31

Post by achrono »

jfim wrote: post #17
malwrar wrote: post #10

Back when ChatGPT came out, I was so shocked by how _good_ it was for an “AI” product that I simply had to know how it worked. Over the next month I ended up drawing out a block diagram on a whiteboard I have in my office, with the math involved next to each step in the blackboard. I’d puzzle about each step along the way, and the triumph of completing the drawing was also that of this sense of deep understanding. I…

Indeed. It's pretty interesting to realize after implementing GPT-2 that the frontier models are scaled up versions of that, with various tweaks to improve performance, model-wise. The secret sauce though is all the datasets, RL training, knowledge of what works from doing all kinds of ablation experiments, and a massive compute moat.

How do we know that today's frontier models are merely scaled up versions of that? Genuine question, since the labs have narrowed what they share over the years to now almost nothing, in terms of how the model was trained and how it works under the hood.

Re: How LLMs work

#32

Post by AgentMatt »

mattnewton wrote: post #28
zemo wrote: post #21

Earlier quoted context omitted.

normal people talk and write with some notion of meter, the cadence of communicating where pauses are inserted at places that naturally suit the speaker (and listener) to pause for thought. LLM's don't really do that, they just write a bunch of sentences. > Researchers have found that some neurons inside the FFN are strongly associated with specific concepts or facts. One neuron might activate strongly on Eiffel-Towe…

I don’t disagree with your conclusion that this is likely ai rewritten, but I do find it strange that you say “normal people don’t write like this” when it is mimicking how people write, and using patterns I have seen people write. I think models are at the point where style is not really reliable as an indicator anymore.

I'm sure there's plenty of writing in the above style to be found on the Internet, and hence having been trained on by the LLM. I'm also not a fan of this style, and in particular I'd say it's rarely or never found in scientific / technical writing meant to convey understanding rather than sell or hype. So here it's IMO more of a style mismatch.

Re: How LLMs work

#33

Post by wuschel »

malwrar wrote: post #10

Back when ChatGPT came out, I was so shocked by how _good_ it was for an “AI” product that I simply had to know how it worked. Over the next month I ended up drawing out a block diagram on a whiteboard I have in my office, with the math involved next to each step in the blackboard. I’d puzzle about each step along the way, and the triumph of completing the drawing was also that of this sense of deep understanding. I…

Could you perhaps cite the core papers for LLMs beyond „Attention is all you need“?

Re: How LLMs work

#34

Post by ai_slop_hater »

achrono wrote: post #31
jfim wrote: post #17

Earlier quoted context omitted.

Indeed. It's pretty interesting to realize after implementing GPT-2 that the frontier models are scaled up versions of that, with various tweaks to improve performance, model-wise. The secret sauce though is all the datasets, RL training, knowledge of what works from doing all kinds of ablation experiments, and a massive compute moat.

How do we know that today's frontier models are merely scaled up versions of that? Genuine question, since the labs have narrowed what they share over the years to now almost nothing, in terms of how the model was trained and how it works under the hood.

No they are clearly not just scaled up versions of gpt 2; there are different LLM architectures like mixture of experts etc that appeared relatively recently. I am not an expert though, far from it.

Re: How LLMs work

#35

Post by jumploops »

trollbridge wrote: post #26
jumploops wrote: post #22

Earlier quoted context omitted.

Those are all just optimizations. We still don’t really know why they work, we just know how to build them.

We don't really know why language works with humans, either. If you raise a baby from birth, you kind of observe how it is learning language, but the process is also rather mysterious. My eldest son's first word was to actually imitate a cow mooing, and then after that to imitate a motor noise of a tractor or truck. And then after that a meow. (His first complete sentence was "King Graham fell"...) My next child took…

Completely agree!

It’s interesting to me how similar attempting to understand LLMs is to neuroscience.

“When we turn this bit off, this other thing happens… if we change these weights the Eiffel Tower is now in Rome”

We’re basically just probing around and trying to reverse engineer an emergent system.

To your point, this system may be quite different from model to model (human to human) although some similarities likely occur.

The comment I was responding to tried to belittle the OP’s understanding of transformers, by mentioning that running an LLM at scale is much harder than the simple white board diagram.

My point was simply that we don’t know why they work, and all the extra optimizations isn’t the “thing” that makes it emergent.

Simply scaling the “GPT” is good enough to see it, so the OP’s awe should stand.

(On a side note, what other architectures can we scale to find similar emergent behavior?)

Re: How LLMs work

#36

Post by ai_slop_hater »

trollbridge wrote: post #26
jumploops wrote: post #22

Earlier quoted context omitted.

Those are all just optimizations. We still don’t really know why they work, we just know how to build them.

We don't really know why language works with humans, either. If you raise a baby from birth, you kind of observe how it is learning language, but the process is also rather mysterious. My eldest son's first word was to actually imitate a cow mooing, and then after that to imitate a motor noise of a tractor or truck. And then after that a meow. (His first complete sentence was "King Graham fell"...) My next child took…

Human brain capabilities are truly amazing, imagine if people didn’t treat their children as if they are stupid and didn’t constantly lie to them, because kids are stupid right, they wouldn’t understand. What heights could be reached.

Re: How LLMs work

#37

Post by fragmede »

10GBps wrote: post #6

I learned TCP/IP by watching and reading raw packets over packet radio at 1200 baud. I've noticed the same thing is possible if you watch the output of a slow LLM. Eventually you start to see the machinery. input tokens = output tokens, it's math. I can't exactly predict the tokens generated but I can see how they are formed. It's a lot like chess. You can't see every possible move but the mechanism is understandable…

https://distill.pub/2019/activation-atlas/

I can only imagine what sort of visualizations are going on today inside of the AI labs.

Re: How LLMs work

#38

Post by ctolsen »

10GBps wrote: post #15
malwrar wrote: post #10

Back when ChatGPT came out, I was so shocked by how _good_ it was for an “AI” product that I simply had to know how it worked. Over the next month I ended up drawing out a block diagram on a whiteboard I have in my office, with the math involved next to each step in the blackboard. I’d puzzle about each step along the way, and the triumph of completing the drawing was also that of this sense of deep understanding. I…

Yep. It's nearly identical to the neural nets we were using in the 90s. Back then even a supercomputer wasn't big enough or fast enough to do what we do today. I have to wonder though. Is this all a human brain is? A similar thing to an LLM just scaled exponentially larger. I mean a brain is not just neurons with simple connections to each other. The neurons, axons, dendrites, , etc in a brain are all holding and pro…

No, it’s definitely not what a human brain is. That makes very little sense. The ways we interact with language (and thus conceptual memory) is completely and fundamentally different.

Re: How LLMs work

#39

Post by otabdeveloper4 »

ai_slop_hater wrote: post #34
achrono wrote: post #31

Earlier quoted context omitted.

How do we know that today's frontier models are merely scaled up versions of that? Genuine question, since the labs have narrowed what they share over the years to now almost nothing, in terms of how the model was trained and how it works under the hood.

No they are clearly not just scaled up versions of gpt 2; there are different LLM architectures like mixture of experts etc that appeared relatively recently. I am not an expert though, far from it.

MoE and such are basically performance enhancements, they don't make the model smarter.

Re: How LLMs work

#40

Post by otabdeveloper4 »

10GBps wrote: post #15
malwrar wrote: post #10

Back when ChatGPT came out, I was so shocked by how _good_ it was for an “AI” product that I simply had to know how it worked. Over the next month I ended up drawing out a block diagram on a whiteboard I have in my office, with the math involved next to each step in the blackboard. I’d puzzle about each step along the way, and the triumph of completing the drawing was also that of this sense of deep understanding. I…

Yep. It's nearly identical to the neural nets we were using in the 90s. Back then even a supercomputer wasn't big enough or fast enough to do what we do today. I have to wonder though. Is this all a human brain is? A similar thing to an LLM just scaled exponentially larger. I mean a brain is not just neurons with simple connections to each other. The neurons, axons, dendrites, , etc in a brain are all holding and pro…

> I mean a brain is not just neurons with simple connections to each other.

No, it's not. There are many animals that have extremely complex and even learned behaviour that have literally zero neurons.

Clearly "neurons" is an oversimplification just-so story, not a scientific theory.

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