It only matters if you are claiming it to be general purpose.
If you admit that it's just a collection of narrow capabilities - whose strength is mostly confined to the 1000 or so RL environments it was post-trained in, then there is of course no expectation of it being general purpose.
The AI companies seem to heavily want you to believe it is some some near human level general intelligence, so therefore pointing out all the things it can't do is very relevant.
If something has general intelligence it should be able to read the rules of a game and follow them. Therefore an artificial general intelligence (AGI) should be able to do this.
So we have a situation where very powerful and influential people are saying we will have AGI in 6 months (if we don’t already), yet the facts on the ground are so clearly pointing in the opposite direction.
I would bet a lot of money that Astra can follow the rules of chess (perhaps if repeated within the context window). Also, this is a different argument than what I responded to.
I can write you a benchmark to prove it even with a heavy handed system prompt Astra will make an illegal move during the course of the games first few moves are generally ok since it's just throwing out learned moves.
Because we want to use this as a replacement for humans, and the average human can learn the rules of chess without needing to see the rules explained hundreds of thousands of times in millions of games.
So, yeah, it matters if a model has millions of examples of something in its training set and still cannot follow the rules.
We're not talking about learning the rules of chess here, but playing a competent game from just being shown the rules. Why is it so hard for people to keep track of the thread of discussion?
> We're not talking about learning the rules of chess here, but playing a competent game from just being shown the rules.
Okay, lets go with that: it's the "shown the rules" bit that we are arguing about.
The argument is that a human may play maybe a dozen games after learning the rules, after which they won't be inadvertently attempting illegal moves. What we are observing with SOTA models is that, even after seeing millions of chess rules, rulebooks, actual games, etc, they still attempt illegal moves.
This does not point to generalisable and adaptable intelligence, such as we see in the average human.
It depends on what you are selling it as.
It only matters if you are claiming it to be general purpose.
If you admit that it's just a collection of narrow capabilities - whose strength is mostly confined to the 1000 or so RL environments it was post-trained in, then there is of course no expectation of it being general purpose.
The AI companies seem to heavily want you to believe it is some some near human level general intelligence, so therefore pointing out all the things it can't do is very relevant.
If something has general intelligence it should be able to read the rules of a game and follow them. Therefore an artificial general intelligence (AGI) should be able to do this.
So we have a situation where very powerful and influential people are saying we will have AGI in 6 months (if we don’t already), yet the facts on the ground are so clearly pointing in the opposite direction.
I would bet a lot of money that Astra can follow the rules of chess (perhaps if repeated within the context window). Also, this is a different argument than what I responded to.
I can write you a benchmark to prove it even with a heavy handed system prompt Astra will make an illegal move during the course of the games first few moves are generally ok since it's just throwing out learned moves.
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I would definitely take you up on that.
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So we humans are not a general intelligence then?
And the stuff i'm using LLMs daily is just fake?
I see i see. I will see myself out of this weird discussion while I let an LLM continue doing a lot of interesting things.
> So we humans are not a general intelligence then?
No, because we can, in fact, generally read the rules of a game and then follow them. It's actually a hobby for many of us.
> And the stuff i'm using LLMs daily is just fake?
This misses the point completely.
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> Why should that matter?
Because we want to use this as a replacement for humans, and the average human can learn the rules of chess without needing to see the rules explained hundreds of thousands of times in millions of games.
So, yeah, it matters if a model has millions of examples of something in its training set and still cannot follow the rules.
We're not talking about learning the rules of chess here, but playing a competent game from just being shown the rules. Why is it so hard for people to keep track of the thread of discussion?
> We're not talking about learning the rules of chess here, but playing a competent game from just being shown the rules.
Okay, lets go with that: it's the "shown the rules" bit that we are arguing about.
The argument is that a human may play maybe a dozen games after learning the rules, after which they won't be inadvertently attempting illegal moves. What we are observing with SOTA models is that, even after seeing millions of chess rules, rulebooks, actual games, etc, they still attempt illegal moves.
This does not point to generalisable and adaptable intelligence, such as we see in the average human.
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But we are. The models can't even follow the rules: they try illegal moves all the time.