Brace Yourselves: Artificial General Intelligence Is Just Around The Corner
Been holding off on this particular warning for a while now. But the time has come to sound the warning on this because I don't think that Google is making idle "marketing" claims, here. General-purpose thinking (the kind of thinking we do when solving a puzzle or assembling the pieces of Ikea furniture, etc.) can be thought of as a kind of game, in the sense of game-theory.
An LLM is also a kind of tree, but of words. At each branch of that "word tree", you need to make choices about how to "move forward", as in a game of chess. And the LLM does this by what is really an extremely sophisticated and fine-tuned probability table. It doesn't
feel like a probability table but it really is just one, giant, probability table that has been highly compressed (like a Zip-file). The transformer model is really acting as a kind of "compression algorithm" and it is the compression that makes LLMs feel intelligent. The compression algorithm is mapping related "concepts" in a very high-dimensional space, in order to cram the training signals received during training into a seemingly impossibly-small space... as little as 4 gigabytes for some reasonably-performant LLMs.
The sequence of "all possible thoughts" can itself be thought of as a giant branching tree like this, but the problem with current LLMs is that they simply "roll the dice" at every branch. Those rolls are not really over the space of "the next word", they are over the space of all compressed "embeddings", one of which will be chosen, and decoded to a word (which will be the next word). The embeddings contain the probability information, but the key is to realize that there are vastly more embeddings than there are words, and the embeddings themselves are something more akin to
thought vectors. We have no idea what is in these "thought-vectors", so they are not quite the same thing, but they behave like that.
What Google is doing is they are applying the same kind of framework underlying AlphaZero to this branching thought-tree. AlphaZero was designed to learn a game without any human training. So, what they are probably doing is using a foundational language model (perhaps Bard) as the "rule-book", and they are training AlphaZero against some score metric to make "legal moves" within that rule-book, to maximize the score metrics. Basically, when AlphaZero says, "The chicken was slivy" the LLM fires a rule-violation because "slivy" doesn't make any sense in this context (or any context), and so AlphaZero has to choose a different "move" (a syntactically valid word). So, it tries some other word, e.g. "The chicken was running" and the LLM now allows it. But AlphaZero is not being
scored by the LLM, the LLM is just the syntactic referee, like an English teacher scoring your essay purely on the correctness of the grammar while ignoring the actual topic of discussion in the essay. Nevertheless, since an LLM does have both semantic and syntactic understanding of language, this is a very well-educated English teacher, so your essay needs to really make sense, even though you may make factually-false claims in the essay as long as the English teacher doesn't particularly know about that topic. This brings us to the scoring -- the actual scoring will be based on some kind of factual semantic knowledge, such as the many semantic AI tests that are already in use for scoring LLMs. The difference is that AlphaZero + LLM can do
massively better than LLM alone can. Instead of topping out at 50% on various logic puzzle tasks, AlphaZero + LLM is going to be able to do as well as an intelligent human would do if they are really concentrating, and probably much better than the human average. In short, when they launch it, this will be the message: AI is now smarter than humans.
And it's not over. There is more coming...