what is the grand parsimonious theory of intelligence going to look like so the 10,000 foot view of intelligence that I think the successive scaling points to is that all intelligence is is search over Turing machines and I think anything that happens can be described by Turing Machines of various lengths and all that we're doing when we're doing learning or when we're doing scaling is that we're searching over more and longer turning machines and we're applying them in specific case I think otherwise there's kind of you know there's no General Master algorithm and there's no special
intelligence fluid it's just a tremendous number of special cases that we learn and then code into our brains yeah I mean when I think about I don't know when I think about the way in which my smart friends are smart it kind of just feels like a more um like a general horsepower kind of thing right they've just got more juice and that seems more compatible with this masteral algorithm perspective whereas if with this touring machine perspective I don't know it doesn't really feel like they've got this long tale of touring machines that they've learned
uh how does this picture account for variation in human intelligence when we talk about more or less intelligence it's just that they have more compute in order to do search over more Turing machines for longer um I don't think there's like anything else other than that so you know from any learned brain you could extract small solutions to specific problems but because all the large Brain is doing with the compute is finding it um and that that's why you never kind of you know we going to find any IQ gland there's nowhere in the brain
where if you hit it you eliminate fluid intelligence I just think that you know it'll turn out that you know this doesn't exist because what your brain is doing is a lot of learning individual specialized problems and then once those individual problems are learned then they get recombined for fluid and and that's just you know like intelligence typically with a large neural network model you can always pull out kind of a small model which does a specific task equally well because that's all the large model is right it's just a gigantic Ensemble of small models
tailored to the ever escalating number of tiny problems that You' have been feeding them so if intelligence is just search over touring machines and of course intelligence is tremendously valuable and useful doesn't it make it all the more surprising that intelligence took this long to evolve in humans not not really uh I I would actually just say that it helps explain why human level intelligence isn't such a great idea and so rare to evolve because any small turning machine could always be encoded more directly by your genes right with sufficient Evolution you have these organisms
where like their entire neural network is just hardcoded by the genes so if you could do that obviously that's way better than some sort of colossally expensive Ive unreliable glitchy search process like what humans Implement right which takes whole days in some cases to learn whereas you know you it could be hardwired in right from birth so I think for many creatures like it just doesn't pay to be intelligent because that's not actually adaptive um there are better ways to solve the problem than a general purpose intelligence so in any kind of Niche where it's
like static or where intelligence will be super expensive or where you don't have much time because you're a short-lived organism is going to be really hard to evolve a general purpose learning mechanism when you could instead evolve one that's just tailor made to the specific problem that you encounter
