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GPT-4 cannot alter its weights once it has been trained so this is just factually wrong.
LLMs are really cool and very useful, don't get me wrong. But people get excited by what they seem to do and lose sight of what they actually can do. They are not intelligent. They create text based on inputs. That is not what intelligence is, unless you have an extremely dismal view of intelligence that humans are text creation machines with no thoughts, no feelings, no desires, no ability to plan... basically, no internal world at all.
An LLM is an algorithm, not an intelligence.
Adam Something uploaded a video starting with the definition of intelligence itself, and then explains how something that “acts” intelligent doesn’t mean it “is” intelligent.
I think even "intelligence" here is a stretch. In a very narrow sense, it is intelligent: it creates text, simulates conversations, answers questions. But that is not what intelligence is (and it is all LLMs can do).
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The author is an imbecile if they haven't been able to break GPT. It took me less than one day of tooling around with it before I got it to say something which outed it as having no understanding of what we were discussing.
The bit you quoted is referring to training.
Recent papers say otherwise.
The conclusion the author of that article comes to (LLMs can understand animal language) is.. problematic at the very least. I don't know how they expect that to happen.
In what sense does your link say otherwise? Is a world model the same thing as intelligence?
In the end of the bit I quoted you say: "basically no world at all." But also, can you define what intelligence is? Are you sure it isn't whatever LLMs are doing under the hood, deep in hidden layers? I guess having a world model is more akin to understanding than intelligence, but I don't think we have a great definition of either.
Edit to add: More... papers...
From the Encyclopedia Britannica:
In no sense do LLMs do any of these except, perhaps, "understand and handle abstract concepts." But since they themselves have no understanding of the concepts, and merely generate text that can simulate understanding, I would call that a stretch.
Yes. LLMs are not magic, they are math, and we understand how they work. Deep under the hood, they are manipulating mathematical vectors that in no way are connected representationally to words. In the end, the result of that math is reapplied to a linguistic model and the result is speech. It is an algorithm, not an intelligence.
I'm not really interested in papers that either don't understand LLMs or play word games with intelligence (shockingly, solipsism is an easy point of view to believe if you just ignore all evidence). For every one of these, you can find a dozen that correctly describe ChatGPT and its limitations. Again, including ChatGPT itself. Why not believe those instead of cherry-pick articles that gratify your ego?
I mean, my first paper was from Max Tegmark. My second paper was from Microsoft. You are discounting a well known expert in the field and one of the leading companies working on AI as not understanding LLMs.
I note that's the definition for "human intelligence." But either way, sure, LLMs alone can't learn from experience (after training and between multiple separate contexts), and they can't manipulate their environment. BabyAGI, AgentGPT, and similar things can certainly manipulate their environment using LLMs and learn from experience. LLMs by themselves can totally adapt to new situations. The paper from Microsoft discusses that. However, for sure, they don't learn the way people do, and we aren't currently able to modify their weights after they've been trained (well without a lot of hardware). They can certainly do in-context learning.
We understand how they work? From the Wikipedia page on LLMs:
It goes on to mention a couple things people are trying to do, but only with small LLMs so far.
Here's a quote from Anthropic, another leader in AI:
They're working on trying to understand LLMs, but aren't there yet. So, if you understand how they do what they do, then please let us know! It'd be really helpful to make sure we can better align them.
Is this not what word/sentence vectors are? Mathematical vectors that represent concepts that can then be linked to words/sentences?
Anyway, I think time will tell here. Let's see where we are in a couple years. :)
are you not an algorithm?
perfected over thousands of years?