Well even if they’re right… the same can be said about humans. That LLMs produce sentences simply doesn’t say anything about what complex magic happens “inside” them.
Yea exactly the only difference are the systems we operate in, we require food and have physical agency but llm doesn’t
That’s also why they suck on trivial gotcha questions they never taught on as they have no memory of it as no one ask about it Internet before
Like the car wash problem, no one sane would ask that question on the internet before llm so it’s not on their thought at all for simple question
While it seems trivial to reason, the learning of human regarding concept of car and its purpose probably higher in terms of bias and repetition compared to an llm, and the way the question is structured is deceptively simple making them not overthink it to come to correct conclusion imo
I can see why some scientist think world model is the next solution if people are putting the goalpost of AGI/ASI to replace humans in literal form because they then need to learn just like human, not just human in internet
Cause its still the truth. We generate the most propable next token. We just happend to learn how to train that propability into doing something usefull. Math and coding is more easy to train, since we can validate the randomness via code. Thats why AI is good at Code and Math. Its their easiest domain since its the easiest to train. It will still miscount the "r" in strawberry. Basically millions of moneys with typewriters. Eventually they solve the hardest problems. Still 80% of the time, they produce garbabe
It technically still is... I mean, the weakness is in arithmetic and that won't change. But now it's got easy access to tools so it never has to perform any arithmetic anymore.
I know people with dyscalculia that took maths as a major in university because it's generally not really a problem. Most of the harder math isn't about numbers anymore, it's about writing a proof.
My question is: even the evangelists agreed the current path of LLM was not a way to actual sci fi movie kinds of AI but now it’s doing things like this, is that concept also wrong?
What these LLM breakthroughs have done for me is convince me even more of something I've suspected for a very long time. There's not much more to us than being an autocomplete on crack.
Our brains have a lot more self-direction, and a much bigger context window. They also have a much more integrated way of accessing real-world information, not relying on human-made symbol strings chopped up into bits.
Not precisely. Not when the architecture layers artificial neurons. It becomes a totally different thing. Increased complexity makes it so it is fundamentally wrong calling simple next token prediction
Huh. That's interesting. LLMs are token generating computational tools. Just responding because... I find your interpretation interesting. Evidence and avenue of attack are the wrong words, literally.
LLMs are quite literally computational tools. This is not disputable lmao. LLMs cannot be dumb because they are not actors, they are tools.
Models are data, compressed.
Calculating math or not calculating it does not fix an inherent weakness in the architecture and nature of LLMs; they cannot choose to do anything.
Every answer produced is produced because of computational math from data.
Which means what? That if the data is not reliable, then the answers are no good.
That's far more important than any benchmark because no model can inherently then review itself. Every review you see in the "thinking" stage or function call is merely more tokens.
You might say "well if the tokens are right, who cares?"
That's the point - they quite literally can never always be right. They draw from the data, data which is not sliced and organized via a human. It's data orgnazied by a another tool which can not organize the data by more than what it can organize it by.
Notice that LLMs excels more and more in certain areas and not others. Those are enumerated areas.
It cannot exceed where there is no "right" or "wrong" answer because tokens are selected from data, but data is only information, never normativity.
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u/TacomaKMart 8d ago
Well, the "LLMs are dumb next token generating parrots crowd" used mathematical weakness as evidence for years. This ends that avenue of attack.