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Human-Level AI Is Harder Than It Seemed in 1955 – John McCarthy (2006)
- dicroce 12y agoThe human brain has about 100 billion neurons. The human genome is 770MB (in .2bit format)... So, we know the genome doesn't have even close to enough information to describe all of the connections within the brain... This means that the brain must be an emergent phenomenon.. There must be some gross structure, or general mechanisms described in the genome and the rest is left to learning... Andrew Ng at Stanford built the largest neural network to date, with 11.2 billion parameters (which I'm going to take to mean 11.2 billion neurons, as I'm assuming the parameters are the neuron weights)... So we're still pretty far off of human numbers of neurons... In addition, humans have the be bathed in sensory input for years before they begin to show intelligence..
- sk5t 12y agoDid anyone ever suppose the genome could possibly describe the functioning of the brain? After all, learning to play an instrument doesn't change your genome, and who could even take a stab at estimating how many bits of storage it takes to "store" mastery?
- tmzt 12y agoI took it to mean that there isn't enough storage in the genome to encode the initial full linkage of neurons, not that learning would have to be written back to the genome in order to change the ongoing network.
- Iv 12y agoI'd wager it is 11.2 billion synapses. And probably at most half that as you need 2 parameters for a synapse: its destination and its weight.
- Teodolfo 12y ago11 billion parameters is a number of connections, not neurons. Connection weights, not neuron weights.
- superobserver 12y agoIt shouldn't actually be hard, especially when you look at how our brains lead to a recognizably human intelligence. Problem is, as has been pointed out by Jeff Hawkins, no one in AI research care(d/s) to look at biology to see what might be learned.... So much heat and funding without light. Edit: this was meant somewhat ironically to get the point across that we can't be expected to succeed with AI unless we know how HI actually works.
- simonh 12y agoThe problem with that is, we still dont really know how the brain works either. Yes we know roughly how neurons work, but how does that lead to the making of a decision? No clue. The best we can do is look at various activation patterns in the anterior cingulate cortex and wonder. It's like trying to figure out how a CPU works by measuring fluctuations in its temperature and power draw as it performs calculations.
- atrilla 12y agoAnd the closest to solving this we seem to be at present is fuelled by deep learning, which is basically a big neural network with an absurdly vast amount of neurons (i.e., parameters for learning, like the brain). We can observe how this brute-force technique works, but unfortunately no-one can explain why (it's a black box model). The same story has been on for decades. I would relate it to being a discriminative model, which is tailored to solving a specific task, in contract to generative models, which try to model and explain the world. Perhaps the brain is not meant to understand how the world works but how to do take advantage of it.
- ajtulloch 12y agoDeep learning models definitely don't need an "absurdly vast amount of neurons" - for example, GoogLeNet (arguably the state of the art image classification model) has only ~6M parameters.
- superobserver 12y agoWell, yes, which is the point. If we don't know how our brains do this intelligencing, then how can we expect any program or machine to do the same? This is a part of the failure of AI research. Can't put the cart before the horse. Well, you can, but it probably won't work.
- serf 12y agoJohn von Neumann was busy dying. Anyway he disapproved of the Newell-Simon work on chess, probably of AI in general. made me laugh. When McCarthy had just died I remember a video from a fellow that worked with him somewhere talking about how until the day of his death he had massive amounts of bandwidth piped into his house, and that the fellow wondered what he did with it all, sort of like a mad scientist. I still wonder sometimes when I think about him. I sort of like to think that he was busting out work towards the 'obstacle' points in this paper 'til the very end.
- tr352 12y agoWhat I miss in these notes, and what I think is the main question we should be asking ourselves, is the question of the black-box approach. That is, do we understand what intelligence amounts to? On the one hand, we want to be able to say yes but on the other hand, we haven't been able after all these years to formalize the concept of intelligence in a satisfactory or even meaningful way. So the answer seems to be no. Moreover, do we even know what intelligence is? Thus, should we instead be building black-box systems that behave seemingly intelligently without understanding why they behave intelligently? I.e. neural networks, deep learning? Is this a good investment? It seems so, at least in the short term. But what about the long term? I don't know the answer. Having said that, I've been working for some time on non-monotonic reasoning and related subjects, which are typical symbolic logic approaches to AI, and I believe that what I am doing, while intellectually very worthwhile, is a dead end in the context of AI. I'm sometimes surprised at how easily we get money to get to work on this stuff. So I agree with the point that lack of funding is not the problem.
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- coldtea 12y ago>I think the only concrete difference between "seemingly intelligent" and "intelligent" is wether an entity evolves over time and gets smarter. Even a naive chess engine being fed games can do that. That's not exactly intelligence.
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- harperlee 12y agoCould you please elaborate on why do you believe it is a dead end? I'm learning about symbolic logic and I would love to have some pointers on the limitation of the approach... From what I've read to date, it's just too expensive to have a proper rule set, but I haven't found a good discussion on the limitations of the approach!
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- technofiend 12y agoEmbed a mechanical turk worker?
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- p1esk 12y agoDid it pass the Turing Test?
- cLeEOGPw 12y agoWe will have article with same title, just years changed to 2045 and 2015 respectively. And probably one or two 30 year periods after that too. People underestimate the complexity of intelligence because of how common sense it seems to us.