Comment by YeGoblynQueenne
8 months ago
>> 1. To score positions in the training data. This is only training data, no search is performed when actually playing.
That's like saying you can have eggs without chickens, because when you make an omelette you don't add chickens. It's completely meaningless and a big fat lie to boot.
The truth is that the system created by DeepMind consists of two components: a search-based system used to annotate a dataset of moves and a neural-net based system that generates moves similar to the ones in the dataset. DeepMind arbitrarily draw the boundary of the system around the neural net component and pretend that because the search is external to the neural net, the neural net doesn't need the search.
And yet, without the search there is no dataset, and without the dataset there is no model. They didn't train their system by self-play and they certainly didn't hire an army of low-paid workers to annotate moves for them. They generated training moves with a search-based system and learned to reproduce them. They used chickens to make eggs.
Their approach depends entirely on there being a powerful chess search engine and they wouldn't be able to create their system without it as a main component. Their "without search" claim is just a marketing term.
It doesn't matter where the egg came from, just that it is an egg.
It could have luckily coalesced from gas (a Boltzmann egg), or perhaps even more radically, been laid by a duck.
you say
>They didn't train their system by self-play and they certainly didn't hire an army of low-paid workers to annotate moves for them.
So you are certainly aware that there are avenues to creating the data set. Given that, it is quite reasonable to say that search is unnecessary.
Neither of those has been shown to produce equivalent training data, no.
They should do one of those instead of using search before they claim it’s possible to not use search.
Or to borrow your analogy, you’ll need to show me a duck egg to prove you can make omelettes without chickens. Making an omelette from chicken eggs and claiming hypothetically some mystery other animal could have done it is nonsense.
>> So you are certainly aware that there are avenues to creating the data set. Given that, it is quite reasonable to say that search is unnecessary.
How is it unnecessary? They used none of those methods, so they had to use search. That is search being necessary, not the opposite.
Bold of you to assume that low-paid (and yet somehow grandmaster level chess playing) workers have never been exposed to search in any fashion.
The point -- which I don't think you got -- is that extremely generic ingredients like high-quality data (which is the point of Stockfish here) and very deep Transformer-type Neural Networks, are enough to nearly match the performance of ad-hoc, non-generalisable techniques like gametree search algorithms.
This has two possible applications: 1. There's far less need to invent techniques like MCTS in the first place. 2. A single AI might be able to play grandmaster level chess by accident.
The catch is you need high quality data in large amounts.
I did get the point and I'm commenting that the point is missing the point. There is nothing new in learning that a large neural net can approximate the output of a classical system. This has been done many times before. The real point is that DeepMind build a system that is half-search and pretend it's no-search. You cannot get the "high-quality data" without a classical system- not in chess.
I get your point. Acquiring the data is the hard part, and they cheated to get it. It's chicken and egg indeed.
Btw, just to be a bit more constructive (not by much) the proper term for what DeepMind did is "neuro-symbolic AI". But DeepMind shunned the term even for AlphaGO, a system comprised of a couple of neural nets and Monte-Carlo Tree Search.
The whole thing is just political: DeepMind use neural nets, GOFAI is dead and that's the way to AI. That's their story and they're sticking with it.
It's more like saying you can make omelette without killing chickens, even though chickens were clearly involved at some point. So I see your point, that this doesn't allow grandmaster level chess play with no search at any point, but I also think it's fair to say that this approach allows you to use search to build an agent which can play grandmaster-level chess without, itself, using search.
> That's like saying you can have eggs without chickens, because when you make an omelette you don't add chickens.
I just took it in the same way as saying that being a vegetarian is generally better for animal welfare, as you're not harming chickens as directly by eating an omelette, as you would by eating their wings.
> That's like saying you can have eggs without chickens, because when you make an omelette you don't add chickens. It's completely meaningless and a big fat lie to boot.
It's like saying ChatGPT isn't a human brain.
It was trained with human brains. But it isn't a human brain.
Would it be more fair if they said “only using search one time to process training data” or something like that?
Ok maybe it's fair to say it's Chess with Precompiled Search.