Am I the only one who's skeptical about the feasibility of AI? As I see it there are two ways to think about AI: first there's the kind of AI that arises from software emulating parts of the human brain based on our current understanding of its inner functioning and produces human-like intelligence, so even if the mechanisms are different from those actually employed by the brain the output is similar in response and depth of reasoning; then there's the AI that stems from creating an artificial brain by reverse-engineering the human brain, but we are an awfully long way from doing that, mostly because we can't expect to unravel in a few decades what evolution has spent millennia perfecting.
It looks to me, a layman, that the only approach that holds any water is the first one. But then again, it mostly looks like people are implementing software based on a flawed understanding of cognitive functions and basically hoping that something magic happens. How can a scattershot approach like this ever produce anything even remotely resembling human intelligence?
Evolution did just fine, and it's far more scattershot than our current efforts at AI.
You're also crucially missing the possibility that someone comes up with an intelligent algorithm that doesn't mirror the human brain in much detail, but still manages to outperform it. Think of flight: inventing flapping machines didn't turn out to be very useful, but we figured out a workaround that was far more efficient. The most interesting (terrifying?) AI research is along these lines.
You're being a bit parochial, specificially anthropocentric. Why a human brain? If you consider it's possible that other intelligences exist in the universe, they probably won't have human brains... Or, consider other animals on earth: given several million years and the right conditions, do you consider it possible that intelligence (at our level) could evolve again - and I don't just mean apes, dolphins and elephants. Especially fascinating in this connection are parrots, crows and other corvids, which are obviously quite intelligent, but have a completely different neuroanatomy of the higher centers from mammals.
Are really we so special? Apart from being first (that we know of)? The history of science is a history of anthropocentrism iconoclasm!
Of course, copying what we know works seems like a reasonable starting point.
Secondly, who said it has to be done within a few decades? If it is done within centuries or millennia, it is still done. "Infeasible" would mean it can't be done, ever.
Personally, I tend towards 50 years off... as it has been for a long time (and probably will continue to be) <- this is a joke. I'm saying it's a looong way off.
"mostly because we can't expect to unravel in a few decades what evolution has spent millennia perfecting" - that's not the kind of thinking that got us driving cars, flying planes, coding computers and altering genes. Evolution doesn't have a brain.
I'm extremely skeptical of this, even though I spend a good deal of my time trying to automate machine 2 machine communication (which gets me thinking about this a lot). I also think that there's a good amount of hubris in these scientists believing that the brain is something that can be emulated by computing power of any kind...are we sure it's an apt analogy (brain as computer)?
Why not? I keep seeing these discussions pointing out the futility of thinking about the brain as a computer, but still don't see powerful arguments to back that postulate up, other than the 'brain too hard, computer too easy, so brain no computer'.
Brain as a computer, in my opinion should be the default state for this discussions. Why? Consider the old and tired brain-made-of-matter argument. There's no reason to think there's something magical or supernatural inside the brain, so treat it as an organized collection of atoms doing cool stuff. The default state cannot be magic, it has to be something that can be disproved or ruled out.
Some parts of it seem to work, as fas as we know, in a (suspiciously) algorithmic way, or in other words, a highly abstract step-by-step chain of actions can be identify for a given part of the brain.
Why not start with the crazy assumption that the whole brain acts as a computer (the theoretical concept), and then identify which parts of it fail the analogy? The key part here is the word 'fail': it should not mean 'too complex for any computer we have built' nor 'we don't know any algorithm that does that', it should mean that there are parts that inherently cannot be modelled, under any circumstances, like the definition of algorithm.
If some part is discovered not to hold the analogy, you should just then question if the analogy is question is apt or not.
It's totally fair for one to start with that assumption, and stick with it until proven otherwise. But it's just as fair for me to be skeptical of the analogy. Before the concept of computers existed, people (very smart people) thought the complex organisms worked just like mechanical machines (http://en.wikipedia.org/wiki/Mechanical_philosophy), and I'm sure there were - and are - many similarities and likenesses to be drawn. However that analogy wasn't correct as we now know. So we're on to the current thinking. Fair enough.
I also think it's a jump to go from "if brain isn't a computer - then magical". There's a lot of room in between. And there are plenty of reasons to think that what goes on inside the brain cannot be mimicked by a computer or algorithms as we currently know them. We don't even know what consciousness is! We should at least admit as much...
I really liked the point of mechanical philosophy you made. This is science in action, when one paradigm can no longer be a valid model, a revised one with none of its weaknesses but with more virtues arises, in this case, the computing machine philosophy.
>And there are plenty of reasons to think that what goes on inside the brain cannot be mimicked by a computer or algorithms as we currently know them. We don't even know what consciousness is! We should at least admit as much...
I agree, it's a huge jump! And that's precisely my point. The brain as a computer paradigm has nothing to do with the idea that an i5 core can't recognize cats, is the theoretical aspect of a computing machine that is used when trying to argue in favour of the BaaC paradigm.
Conciousness is precisely what doesn't fit in the BaaC paradigm. So the research should start from there.
I'm curious if the definition conciousness will have to be changed in the near future. Exciting times!
Where is the hubris in attempting to do something without knowing whether it's possible? What is it about AI that seems to make people defensive? Is it the idea that human intelligence might not be as special as we think it is?
Religious people, even if not strict, have this reaction always. I don't see this clashing with religion, but 'they' do. Then again, i'm not religious although I was raised with the bible at home and in school and know it by heart.
I guess that if you're religious, then yeah, almost by definition, you would be skeptical of assertions like these. Although to the parent comments point, I'm not defensive at all about looking into AI. I find it fascinating and exciting and though I'm not trained in it, I read as much as I can about it and don't want to stop any research or questions into it at all.
But hubris - yes it is hubris. Because there is no scientific basis for the assertion that we will cross that chasm into 'true' AI, and thus it's based just as much on faith as any religious belief. And it's hubris because they claim a scientific basis where there is none.
When there is a scientific basis or proof that we've reached (or will reach) this 'singularity', you won't see me complaining. I'm not anti-science. I just don't think it's ever going to happen.
On a semi-related note, doesn't anyone find it kind of odd that Ray Kurzweil's calculations for when the singularity will occur happen to be just about the time his natural life will end (statistically speaking)? These projections are all driven by ego and faith, very little by science...
I said exactly that about Kurzweil his predictions here on HN a while ago; others have the same issue; fear of death moves their predictions near the end of their own life. That's not weird though; if you don't get to see it yourself, what's the point? Sure it's nice for the future generations but that's not really how most people think.
About religion and science; it is about definition where there difference is; IF you accept some definition X as being strong AI then when we reach that we have a scientific reality. The chasm and 'true' AI and what these are in scientific terms are vague, however in science we accept definitions of how nature works and if those definitions are things you hold true there is no reason why it won't be reached as there is not 'special' in the fabric of our brains which we couldn't copy given advanced enough ehm, take your pick; biology, nanotech, electronics, 3d printing etc. If you however cannot agree on definitions and have that (to me alien) quality of accepting mystery above all, then sure it's all believe or not. Not a good conversation maker as we are done after 2s, but he.
Well, if you look at them from very far and keep your ears closed they kind of resemble birds. And they do resemble birds more than other stuff in the air. I think that analogy probably will hold up; the eventual strong AI will resemble a brain a complexity and will have a lot of things in common, but it will not be the same.
Well, no. You're right. I don't know whether that invalidates my point though. It may not be necessary to model the human brain to achieve machine intelligence. It may also be that any sufficient machine intelligence would wind up modelling the human brain to a limited but necessary degree, in a similar way that birds and airplanes share wings with similar lift effects, but different mechanics. Until there's something real to point at, I think it's semantics.
I agree with your assessment on those two avenues. One thing that throws people off is that the AI/Machine Learning community is constantly selling their models as "human like" when the models are really only inspired by the human brain by extremely loose analogies.
There is another approach, what I would call the Airplane approach, since it is to the brain what airplanes are to birds. That is, to base machine intelligence on a new kind of mathematical logic that hasn't been invented yet.
Actually, there are some areas where evolution still has an advantage. A biologist was explaining to me how artificial enzymes (man made proteins) can at best speed up a chemical reaction by 10^3 - 10^6, while natural enzymes typically speed them up by 10^9 - 10^12. Might have got those number wrong, but his point was that natural enzymes beat artificial ones by a wide margin.
Is it feasible? Yes, absolutely. Are we anywhere near to 'human-level' AI? No, not by a long shot. How long will it take? Will we ever make it? Very hard to know.
Well... That definition keeps changing. For passed definitions we passed human-level a few times. And for some tasks we did or will pass it soon. So what is your definition of 'human-level' intelligence? Don't copy wikipedia; make one up in strict language (don't say consciousness please). For what a lot people make/made up we passed.
I'm not going by a definition. Getting an airtight definition is pretty hard. I'm talking in a fuzzy "You'll know it when you see it" sense. Sure, we get human or even superhuman performance at various constrained tasks, and that's great. But what about say, iron man's Jarvis? Still in the realm of science fiction.
We get superhuman performance on most tasks we use computers for now; people forget that easily. Not too long ago, before electronic calculators, we used people as calculators; it was a good job for which you needed a brain; they would consider computers now superhuman. A Watson hooked up to Asimo presented a few 100 years back (I don't think you actually would have to go back that far; my grandparents would not see it as less than human, probably more) would be considered god himself.
And we are on HN, mostly smart people here who vastly over estimate 'normal people'. It's nice that we (me included) assume a human can be taught to be able to do anything other humans can (with some margins), but for now this is not true either. And if we want this empirical evidence thing going on; if a (kind of) Turing test would be done with a large part of the population who have not been told they are, for instance, we let a human with earplugs walking around a village in Arkansas and walk up to an average person and play the human interaction for Watson (or something like it), it would usually succeed. It would in my village for 100% sure; I could actually make a knowledge based script for talking to a lot of people and they would not see the difference. So I understand what you mean, but I don't think in a chinese room kind of way (and that experiment, as many have shown, doesn't matter) we are not that far off. When we reach your level of input/output you will 'see it' but still, because you don't have a definition, will deny it. I would wager that we are there are already in the 'fuzzy' sense of at least 40% (I think it's a lot more) of the population. My grandparents, bless them, definitely think they are talking to a human when they call they book a railway ticket (which has been a steadily improving AI for a little under 20 years now); for their 'fuzzy' it's been solved and strong AI exists.
I think that one thing that people are missing when they think AI is not a threat is there does not have to be a singular AI for every problem.
Chess computers are better than humans, but I wouldn't trust them to manage the electricity grid. What if there was an equivalent quality of computer specialized for every significant area of society - electricity grid, packet routing, high speed trading, etc etc.
I'm no expert in this area so I welcome corrections to my rough numbers below.
Approximate number of human neurons: 1.0e11
Approximate number synapses in a human: 1.0e14
These are big numbers, but not impossibly big numbers. There are different kinds of
neurons, and signals on synapses are not simply binary. However, even with these
complications, the hardware needed to reach these scales isn't hard to imagine.
Transistors in XBox One: 1.0e09
Brains are biological computers so they suffer from very slow switching speeds at the neural
level. Neurons run in parallel, but they are not fast:
Approximate neural switching speed: 1.0e03/sec
Even if all of the synapeses could sustain this rate in parallel (they can't) and even if all of the brain was 100% occupied with solving a single task (it isn't) this would mean that we absolutely can't compute faster than:
Speed * synapses (brain ops per second): 1.0e17/sec
For comparison, the fastest bitcoin hardware I see is advertised to operate at the
following speed:
Minerscube 15 (hashes per second): 1.5e12/sec
And a regular GPU is capable of simple instructions that run at the following speed:
AMD Radeon HD 6990 32-bit instructions: 2.6e12/sec
From this we can see that hardware is catching up with the raw computing ability of
the human brain. Now consider the problem of programming a brain. It isn't necessary to
program every synapse. The brain learns, and essentially programs itself. To see
why this is true consider the programming that we are born with:
Bits of information in human genome: 1.0e10
This is far less than the number of synapses that we have. Therefore, the brain must
program itself, somehow.
Now, to address the argument about evolution taking millions of years. First, we can
evolve programs much faster than nature can evolve humans. There have been, perhaps,
100 million generations of humans. Even if it takes six seconds of computing time to
run an evolutionary computation for a single generation it will take no more than
20 years to run over 100 million generations.
Brute force evolution isn't the only way to build strong AI. A program can exhibit
behavior that we don't anticipate. I've written simple programs that beat me easily
at games such as Othello or Freecell.
Finally, once machines get smart enough to design other machines there may be a
rapid acceleration of progress in this area as we employ them in designing subsequent generations.
I feel that strong AI may pose a significant risk to humans; consequently, we should
proceed with caution. Here is a thought experiment. If a chimpanzee could be taught to drive, would you trust it to pick your kids up from school? What sort of value judgements would it make in the case of an impending emergency? Would you let an elephant baby sit for you? Even if was much "smarter" than a normal elephant?
Strong AI will not be like us. It will learn and develop without a human body, and it will not interact with the world and society as we do and may end up being very foreign to us. Will it be sociopathic? Or will it be like whales, intelligent, but mysterious, perhaps spending all its time singing AI songs to other AIs.
It looks to me, a layman, that the only approach that holds any water is the first one. But then again, it mostly looks like people are implementing software based on a flawed understanding of cognitive functions and basically hoping that something magic happens. How can a scattershot approach like this ever produce anything even remotely resembling human intelligence?