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David Deutsch On Artificial Intelligence

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Re: David Deutsch On Artificial Intelligence

#51
post #31

Earlier quoted context omitted.

Right, I remembered him after I posted. I don't know what to think of that. He obviously knows quantum theory. He can open any undergraduate textbook on neurophysiology and read all about how neurons work. So is he merely crazy, filling some emotional void religion might had filled in the old days, or something else? I don't know.

Do you really believe we know all there is to know about how neurons work? I don't. I think there are lots of surprises lurking.

I am not sure we positively know every single detail there is to know about neurons, but we know an excruciating amount of details. At the level of a single neuron, it's physiology and connections to neighbouring neurons, we know everything we need to know that it has absolutely nothing to do with QM. There are no mysterious phenomena here, nothing outside biochemistry and physiology.

Re: David Deutsch On Artificial Intelligence

#52
Has anyone ever tried using the first law of thermodynamics to prove that AGI is impossible. It's somewhat dependent on what one considers "intelligent" of course. But let me give a stab at it.

Say AGI is a computer machine and/or algorithm that's capable of "creatively" building a smarter version of itself. Then (here's the proof) say we did build a machine that was capable of building a smarter version of itself, then that machine would technically be a perpetual motion machine, and therefore a violation of the first fundamental law of thermodynamics: "In all cases in which work is produced by the agency of heat, a quantity of heat is consumed which is proportional to the work done; and conversely, by the expenditure of an equal quantity of work an equal quantity of heat is produced." (Rudolf Clausius, 1850)

Or assuming that AGI is just "in the software", the heat produced by the computation would continually increase, as an ever more complicated algorithm/computation is formulated, and therefore violate the first law of thermodynamics -- again. Assuming a more "intelligent" computation consumes more heat/energy.

Re: David Deutsch On Artificial Intelligence

#53
> Unfortunately, what we know about epistemology is contained largely in the work of the philosopher Karl Popper and is almost universally underrated and misunderstood (even — or perhaps especially — by philosophers). For example, it is still taken for granted by almost every authority that knowledge consists of justified, true beliefs

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The Gettier problem has been well known in Philosophy since the 60s. Probably the most famous example would be barn-façades, first showing up in the mid 70s. It's taught in undergraduate courses. It's the second bullet point on the Standford Encyclopedia of Philosophy's Epistemology article.

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> How could I have ‘extrapolated’ that there would be such a sharp departure from an unbroken pattern of experiences, and that a never-yet-observed process (the 17,000-year interval) would follow?

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One rather assumes your experience with numbers has included 20 following 19 before and you extrapolated the rules from that and similar experiences with assigning numbers to things. You were, after all, previously told that it's how years worked - and doubtless you've lived through at least one year changing.

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> Even in the hard sciences, these guesses have no foundations and don’t need justification. Why? Because genuine knowledge, though by definition it does contain truth, almost always contains error as well. So it is not ‘true’ in the sense studied in mathematics and logic. Thinking consists of criticising and correcting partially true guesses with the intention of locating and eliminating the errors and misconceptions in them, not generating or justifying extrapolations from sense data.

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Be that as it may, some guesses are better than others. Generally the guesses that are based on more data. You lock someone in a room for 19 years, don't talk to them beyond the basic social interaction required for them to develop language, and then ask them to guess what an atom bomb is, they're not going to get very far. Even guessing what an atom is, or a bomb they'd be hopelessly out of the context of their experience.

Guesses, in so far as they're meaningful, have foundations. Those foundations limit what you can guess about and have any practical chance of refining towards truth with more evidence. You can't start off knowing nothing and then go to nuclear weapons in one step. You have to make smaller guesses, based on what you know.

And much though the author you might criticise Bayesian probability, this is bound up in the idea that probability is based on dividing the search space between the explanations we can come up with for a thing and then weighting it with evidence.

Re: David Deutsch On Artificial Intelligence

#54
post #44
post #42

> Despite this long record of failure, AGI must be possible. And that is because of a deep property of the laws of physics, namely the universality of computation. This actually doesn't follow. It is logically possible that general intelligence is the result of a non-physical process (or at least a process outside any conception of known physics). It could be, as philosophers have put it, a homunculus that interfaces…

If these were true, It would mean that atoms in our brain violate physics as we know it. This source of intelligence would be detectable, because it is significant enough for neurons to detect it. The hidden premise of the quote is that that we have observed brains enough to be confident that they are running on physics.

The current theories of physics do not even begin to offer an explanation for "subjective experience"/consciousness, which definitely has everything to do with the brain.

Re: David Deutsch On Artificial Intelligence

#55
post #11

Earlier quoted context omitted.

Is there a difference between reasoning and predicting? It seems you don't think so and the author does.

I think there is a difference, but my view is that it is impossible to reason without sufficiently accurate prediction, and that the concepts we use for reasoning are largely formed based on how predictive they are. Consider playing a game where two players throw dice, and the one with the larger number wins. There is no predictability between turns, so there is no point in reasoning far into the future, unlike in ch…

Bad example. I can predict the dice game's problem space. E.g. for a single normal die (1-6), I can predict that I'll never observe a 7 [P(7) = 0%]. I can also predict the probability distribution. E.g. for two dice thrown together, the probability of throwing a sum of 7 is 1/6, whereas the probability of throwing snake eyes is only 1/36. Yes, the game's output is random. But what you're talking about is control, not prediction. If random meant "impossible to make predictions about", then statistics wouldn't exist.

Regarding winning, there's no way to improve one's chances (besides cheating?). But merely knowing that the game is predicated solely on chance can be useful for other applications. E.g. realizing that the lottery is a scam.

Personally, I'm in that camp that says reasoning is a instrumental value towards prediction.

Re: David Deutsch On Artificial Intelligence

#58
post #12
post #9

> So, why is it still conventional wisdom that we get our theories by induction? I thought the other conventional wisdom is that we get our theories by building mental models. I throw a ball, and I can either remember how it flew in the past and use that to predict, I can also build a mental model from first principles to find out what will happen. Maybe run a short 5 second idealized simulation in my head and I can…

I thought the other conventional wisdom is that we get our theories by building mental models. I throw a ball, and I can either remember how it flew in the past and use that to predict, I can also built a mental model from first principles to find out what will happen. Maybe run a short 5 second idealized simulation in my head and I can predict what might happen. Well then I might realize that there was wind that my…

"Our brains are not, as far as I know, running any kind of recognizable simulation like we would with a computer."

One way to implement the 'remembering' of the ball position is to run a forward model of the trajectory in your head.

Your brain has specialized hardware for running forward models (short-term simulations) of physical systems. You need these to control your body precisely in the face of delays in the feedback from your limbs.

A nice story - it's a just-so story, but a nice one - is that we repurpose this simulation hardware to simulate systems we observe outside our bodies. Expert ball-catchers have a very good simulation, beginners have a bad one. If you're already an expert, you can get even better by running your simulation off-line: this may be why experts can practice by visualizing their golf swing or swim stroke but newbies can not improve much that way.

There is some physical evidence that the off-line model stuff is real, as when you imagine yourself walking, or watch someone else walking, some of the same parts of your motor cortex are active as when you are actually walking.

My very favourite part of this explanation trail is as follows: animals got very good at modelling the behaviour of other animals, in order to predict what they will do next: Eventually, they/we started re-using the same systems to understand and explain our own behaviour into the future. This is (at least part of) what we call consciousness.

Now, you may or may not buy this, but it's rather elegant as a hypothesis.

Re: David Deutsch On Artificial Intelligence

#59
post #16

I can just say that Deutsch is another victim of what being good at theoretical physics tends to do to one's mind. The amount of intellectual hubris and arrogance we can develop is staggering. Sheldon Cooper is not really a parody, it's what many theoretical physicists actually think (but are to socially adapted to say out loud), as in: "Penny - I'm a physicist. I have a working knowledge of the entire universe and e…

Could not agree more. He states a lot of statements as if they are proven facts, where they are really speculation and opinion, which is the opposite of an objective scientific argument. And he seems to fundamentally miss-understand machine learning

Re: David Deutsch On Artificial Intelligence

#60
So evolutions "works" in the sense that anything that doesn't work doesn't stick around to show its face. There isn't any intention behind it, yet us people, who clearly have intention (and I'm not even going to stand for an argument about whether or not free will exists. You take that shit outside with the rest of the garbage) are a product of it.

But we're kind of long past the point where just any old random slurry of chemicals is going to get means-tested in the great arena of life. Life is not finding the right set of chemicals to combine, life is a specific set of chemicals and the right orientations of different copies of those chemicals.

So I think we're at a point were binary code, the instructions to run on the processor, is akin to chemicals in the physical world. We try to treat them like DNA, but you can't just toss a bunch of chemicals in a bucket at random and expect life to come out. 100 billion times out of 100 billion times, random chemicals in a bucket makes you nothing close to life. Ultimately, chemicals are at the core, but they aren't sufficient. The right chemicals are needed, and they interact in such a way that infinite variation is the result.

And DNA is a code--a deterministic, exceedingly discrete code. Yet somehow (hand waiving), from such arises the non-deterministic, comparatively-infinite variability of human behavior. So in that sense, I don't think he's necessarily correct that AGI is a "different type of program than we've ever programmed."

But all that is just to create a system that is intelligent, it's not intelligent itself. It's a road, not a destination. Living things, on the other hand, have goals and try to achieve them. Not just have goals, but generate goals. Create it's own notions of what to do and how to do them and why the doing of it is important.

You touch fire, your hand recoils, because in you is a system for detecting potential damage and the understanding that damage is not something you want on your docket. Computer touches fire, computer recoils, because in it is a system for detecting potential damage and YOUR understanding that damage is not good. The computer didn't conclude on its own that damage was bad. It never had the sense that it existed. And this isn't even an "intelligent" response, this one is merely instinct.

So I think the big, missing question in AGI is, "what could a computer want?" We could program a computer to have certain goals, but that is not the same thing as a computer sitting around and saying, "hey, you know what? Let's go to the beach this weekend." We foist our own goals on the computer and instruct it on how to understand those goals, and are disappointed when it fails to get the point of the goals at all and sits there blinking at us. How can you ever hope to have an intelligent computer if it isn't intelligent on its own terms?

IDK, I am rambling. Would you be intelligent or have any hope of becoming intelligent if you didn't create your own designs on your future, couldn't perceive anything to test your actions against your desires for the future, and had no means of your own to ever come about correcting these issues? It just seems like the only way AGI will happen is through something incredibly simple that allows a computer to put its own parts together, see the result, and arbitrarily evaluate it.

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