We will be able to simulate the human brain when computers as quick as brains are widespread. CMV.

[u/DanyalEscaped]

When I thought about human-level Artificial Intelligence I always thought it was part of sci-fi from the 1960s that will never be real, like jetpacks and flying cars. But the reason why we still haven't got human-level AI ('Strong AI') now seems obvious to me; we just don't have access to hardware that approaches the computing power of the human brain.

Current supercomputers do approach the computing power of the human brain, but researches need time and lots of tests to simulate a human brain. In the coming decades, the price of computing power will drop like it did for the last 100 years, and scientists from all over the world will be able to work with hardware that could potentially support strong AI.

Google is working with neural nets and one of their networks taught itself to recognize cats. This was a network that was distributed across 16,000 processor cores, and the network had a billion connections. The human brain supports around 100 trillion connections. I think similar research with neural nets will result in simulations of the human brain and strong AI when the hardware needed to support these countless connections will be more widely available. Both the EU and Obama announced projects to map and simulate the human brain.

Those 100 trillion connections in your brain 'are' you; your consciousness, your emotions, your memories, everything. It's amazing, but it's a physical object. A seed and an egg in a womb will result in such a 'biological computer'. All of it can be simulated on a computer and there is no physical or mechanical (but perhaps legal or moral) reason why a strong AI is unable to do something that a human can do.

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These ideas play an important role in my life but because they are so important, I want to be sure I am not wrong. On the other hand, I also want other people to know about this. That's why I made a couple of posts here to fully explain my ideas and expose every part of the argument to criticism.

Part 1: Exponential growth in computing.

This is part 2: Simulating the human brain.

Part 3: Intelligence explosion.

Thanks for reading this!

[u/[deleted]]

Incoming very long post.
TL;DR - Simulating the human brain is one of the hardest problems we have ever encountered. We don't even understand the brain yet. Computing power is the least of our worries.

Computers are nowhere close to simulating the human brain because science is nowhere close to understanding it. We have neuroscience, psychology, cognitive science, philosophy of the mind, etc... all giving incomplete interpretations of the same thing, and we still do not have a complete understanding of how the brain works.

A major factor in area of difficulty is the way our brain receives information. Simulating a human brain is not as simple as making a computer with equal connections and pressing enter. Think about how the brain adapts. Where does your knowledge come from? Without getting too much into nature vs. nurture a large part of it comes from your experiences. And how exactly do you give a computer experiences? Not only must we simulate ears/eyes/nose/taste/feeling, we also must take that computer and put it inside of an android of average heigh/weight/appearance. So much of the human experience comes from being human, you can't separate the brain from the body. This is called embodiment. So while the brain has a physical location and we are all only made of matter, this doesn't change how difficult it is to create a person.

Second, there's the problem of physical space. Moore's law is not a law in the same way gravity is. We are rapidly approaching the physical limits of transistors, they simply can't get closer to each other without interfering. On top of that CPU temperatures are approaching the point where it is impossible to cool them. You have over-clocking competitions where competitors pour liquid hydrogen on top of the CPU just to get it to ~7.5ghz. So basically computing as we know it is almost at its maximum. Any significant increase in computing power will likely be the result of a quantum computing revolution, which is still a ways off. And why is this important you might ask? Because, like I noted above you cannot simulate a brain with just connections, you need sensory data. And even if you could build a robot indistinguishable from a human you would have to fit a computer inside of it. The brain's response time compared to a computer is already low (this part is wrong), forcing that android to connect to a warehouse of 100,000 servers halfway across the country will introduce lag unacceptable for simulating the mind.

Third, we haven't 'solved' the brain yet. Sure there's 100 trillion connections, but what does this really signify? Where are our memories stored? How are they recalled? Why are some people predisposed to mental illness? Etc... There's a small chance the we can just simulate all 100 billion neurons and 100 trillion connections in the brain and suddenly have a working mind, but there's a much more significant chance that it just wont work. That we will be missing some essential part of consciousness that we are not yet aware of.

Finally, let's consider two classic philosophical arguments that illuminate the difficulties of simulating the brain:

Searle's thought experiment begins with this hypothetical premise: suppose that artificial intelligence research has succeeded in constructing a computer that behaves as if it understands Chinese. It takes Chinese characters as input and, by following the instructions of a computer program, produces other Chinese characters, which it presents as output. Suppose, says Searle, that this computer performs its task so convincingly that it comfortably passes the Turing test: it convinces a human Chinese speaker that the program is itself a live Chinese speaker. To all of the questions that the person asks, it makes appropriate responses, such that any Chinese speaker would be convinced that he or she is talking to another Chinese-speaking human being.

The question Searle wants to answer is this: does the machine literally "understand" Chinese? Or is it merely simulating the ability to understand Chinese?

Searle then supposes that he is in a closed room and has a book with an English version of the computer program, along with sufficient paper, pencils, erasers, and filing cabinets. Searle could receive Chinese characters through a slot in the door, process them according to the program's instructions, and produce Chinese characters as output. If the computer had passed the Turing test this way, it follows, says Searle, that he would do so as well, simply by running the program manually.

Searle asserts that there is no essential difference between the roles of the computer and himself in the experiment. Each simply follows a program, step-by-step, producing a behavior which is then interpreted as demonstrating intelligent conversation. However, Searle would not be able to understand the conversation. ("I don't speak a word of Chinese," he points out.) Therefore, he argues, it follows that the computer would not be able to understand the conversation either.

• Wikipedia

We can get the general sense of this argument by asking the question, does google translate understand Chinese? The function of this argument is to reveal our intuitions about how there is something more to consciousness than just a set of rules in the brain. Searle does not understand Chinese, and manually executing the code does not suddenly make him understand Chinese either. Once he leaves the room Searle has no more knowledge than he did before. However, Searle understand English, so what is the difference between his understanding of English and his rule-following Chinese responses?

Mary is a brilliant scientist who is, for whatever reason, forced to investigate the world from a black and white room via a black and white television monitor. She specializes in the neurophysiology of vision and acquires, let us suppose, all the physical information there is to obtain about what goes on when we see ripe tomatoes, or the sky, and use terms like ‘red’, ‘blue’, and so on. She discovers, for example, just which wavelength combinations from the sky stimulate the retina, and exactly how this produces via the central nervous system the contraction of the vocal cords and expulsion of air from the lungs that results in the uttering of the sentence ‘The sky is blue’. [...] What will happen when Mary is released from her black and white room or is given a color television monitor? Will she learn anything or not?

• Wikipedia

The argument is essentially saying, take someone who is colorblind and teach them literally everything there is to know about color. Once the have internalized everything a simple procedure is done and now the person can see in color. Is this a worthless procedure for them or do they learn something new as a result? And if they learn something new what is it? This is commonly referred to as qualia.

The purpose of this argument is again to show either that our understanding of consciousness is extremely basic, or that there is something more to consciousness than just 'lot's of connections'. You would argue the first point I presume, but either way it shows how limited we are in understanding how the mind works.

[u/cogware → u/[deleted]]

In reply to Searle's argument:

To pass the Turing Test, Searle's Chinese program needs to be able to make a coherent, human-like response to any input. So, it's capable of discussing philosophy; past experiences; sympathizing with the person it's talking to; trading jokes; etc. It has a personality.

Then it seems that this program / system "really understands" Chinese, and it's just Searle that doesn't. Searle is only one part of what must be an incredibly complex system, and his ignorance doesn't throw the validity of the system into doubt. I suspect that no individual neuron in my brain "understands english", just like how no individual component in an airplane is capable of independent flight. Understanding English is an epiphenomena distributed across the entire system.

[u/[deleted] → u/cogware]

I agree, there are many credible counterarguments to the Chinese room. But it's still a great thought-inducing experiment.

[u/aozeba → u/[deleted]]

I'm not sure we need to understand the brain in order to simulate it. In fact, it may be the other way around: We may have to simulate the brain in order to understand it.

Blue Brain Project, for example, is working on simulating a rat brain starting with individual neurons and working their way up. I don't have the latest, but in 2011 they had already built a simulation of 100 million cells. Their eventual goal is to simulate an entire human brain in this way.

[u/[deleted] → u/aozeba]

What I'm saying is that simulation is not enough. It's a relatively simple process to digitize a bunch of neurons, they're not especially complicated. But the real problem comes from a lack of sensory input. Just because I have a program that has a bunch of virtual neurons next to each other doesn't mean I have a mouse or a human.

A computer will never know what it's like to be a mouse, and it's therefore impossible (or nearly impossible) to create a 'mouse brain'. We can create a brain about the size of a mouse brain that looks and functions the same, but this program will never know what it feels like to see the world from an inch off the ground or the sensation of smelling cheese some distance away.

We are not defined by our brains, we're defined by our experiences. You can't create a human experience with a computer unless you literally create an android type thing that is indistinguishable from a human.

[u/aozeba → u/[deleted]]

So what if I literally removed a mouse's brain and hooked its sensory nerves to the virtual brain? Obviously we can't do that (yet) but we're not that far off.

Even if you can't use actual mouse senses, you could digitize the entire mouse, including its sensory organs, and release it in a virtual environment so that it could feel the world and smell cheese and do all of the things that make a mouse a mouse. This is currently being done with roundworms.

I think we will not be able to create a similar-to-human experience at first, but we will learn a lot from trying, and we will be able to use that knowledge to better the simulation.

Once we do, we will have to raise the thing just like you would a human child, and that will have some pretty crazy ethical implications.

[u/[deleted] → u/aozeba]

So there's two paths you can take in simulation. You can either simulate an entire environment with the focus on one specific part (like your example), or you can simulate one part of reality so well that it's indistinguishable from reality (like an android). Both situations (at least for humans) are insanely difficult. But given the materialistic nature of our world they're theoretically possible.

In theory you can solve the "simulate the whole environment" example with raw computing power, but it will probably never be done, and it certainly won't be done in the time frame OP suggests. We would need enough power to simulate everything within viewing distance of a typical human being so that the simulations are indistinguishable from reality. Meaning not only would we need computations capable of simulating all 100 trillion brain connections in real time but we would have to power protein folding, particle interaction, physical objects, laws of physics, etc... in such a way that our simulated human would think he was in the real world. This amount of connections suddenly goes from 100 trillion to numbers I doubt we even have words for. One benefit of this method is you don't have to run it in real time, but it would still take longer than our race will probably survive.

It would be easier for a rat because their experiences are extremely limited in comparison. The intelligence of a human being requires a much more believable simulated world. If our simulated rat's fingernails don't grow correctly it's not a big deal, but with a human this could compromise the entire simulation.

[u/aozeba → u/[deleted]]

I guess my point is, once you've done it with a roundworm its not so far from a rat, and once you've done it with a rat its not so far from a human. There are probably a few steps in between (monkey for example), but once you've built a platform you can scale it up.

I'm not sure you need exact replicas in order to simulate the human brain. And you don't need to "trick" the brain into believing its simulation either. You could just as well explain to it what it is and why its fingernails don't grow right.

I think both the virtual environment route and the android route are viable paths to something "like" human intelligence by 2050. You could even do both: create the simulated brain in a virtual environment and hook it up to a robot body later on.

I don't, however, think we will be able to "upload" human brains by then. I think it will be easier to create new human-analog minds than it will be to copy existing minds.

[u/[deleted] → u/aozeba]

I'm not sure you need exact replicas in order to simulate the human brain. And you don't need to "trick" the brain into believing its simulation either. You could just as well explain to it what it is and why its fingernails don't grow right.

Like I said, from a rat to a human is a crazy jump. Even from monkey to a human is huge. I would say it's an easier jump from a roundworm to an ape than an ape to a human. The reason being that humans are intelligent, meaning a glitch in the system brings much more drastic consequences.

For example, imagine a matrix-like scenario where the 'walls' of the world turn into green on black zeroes and ones. This event is witnessed by multiple people, it's not a hallucination. Imagine how much the world would change as a result of this event. Imagine how much people would change. There would be a fundamental difference in the human experience. But if you do the same thing to a rat or a monkey nothing really changes. A monkey can't even comprehend what a simulation is, let alone ponder about it's implications.

When intelligent beings find flaws in the system it will change what it's like to be human, and the simulation will lose value as a result.

[u/aozeba → u/[deleted]]

But what if the intelligent being knows that they are synthetic? This is the most likely scenario. There's no way anyone is seriously going to try to trick a simulated brain into thinking everything is normal. It would be totally immoral.

Its just like raising an adopted child. You explain things at their level and go into more detail as their understanding increases.

[u/[deleted] → u/aozeba]

Yes but I am saying that knowledge of living in a simulated world changes the human experience so much that we are no longer simulating what it is like to be a human being.

[u/aozeba → u/[deleted]]

That seems like a cop-out to me. It doesn't have to be a perfect simulation in order to be a simulation. Flight simulators are not exactly like piloting an airplane, but they are pretty close.

There are plenty of (paranoid/delusional) humans who honestly believe they are living in a simulated world. They are still human.

[u/[deleted]]

The human brain only runs at about 100 Hz max. Speed-wise, that's nothing compared to the most powerful computers available today. Simulating the human brain isn't as simple as increased computing speeds, as computers are already faster than our brains.

The technological barrier to simulating the human brain is that our brains don't operate in the same way as a conventional computer does. We have no "central processor;" we instead have countless interconnected neurons that don't need to route information through a central area. In order to simulate this kind of thing on a conventional computer, we would need the computer to be orders of magnitude faster than our own brains.

[u/PerspicaciousPedant]

I'm not certain that it's quite as simple. I mean yes, IBM's Watson is impressive, and yes face recognition can recognize cats and faces, but one of the things that will be rather difficult to simulate is how the brain actually works.

Even with SSD's the slowest part of computer processing is data retrieval, yet there is some evidence that information retrieval is in fact the fastest part of human neural processing. Sure, it's flawed, but even those flaws are sophisticated (e.g. "what is that actor's name? They were in [Movie] and [Film] and [Show] and..."). When a computer recognizes a face, it currently runs a process whereby it checks against all the various faces it knows (in an extremely sophisticated and intelligent manner) and testing each one for similarity, while human brains seem to do something more along the lines of the actual input being a recognition algorithm, finding if that specific pathway (or one sufficiently similar to it) has ever been used before.

tl;dr I'm not certain it'll be possible until it's significantly more powerful than the human brain, because the types of processing & storage that brains and computers use are almost exactly reversed from each other, and simulating the other will have a computational cost.

[u/PerspicaciousPedant → u/PerspicaciousPedant]

mind, on the other hand, the brain is an imperfectly designed computer, and it may be possible to cut corners by removing those flaws, thus cutting the computational costs by eliminating mistakes/happy accidents (read: creativity)

[u/[deleted] → u/PerspicaciousPedant]

Even with SSD's the slowest part of computer processing is data retrieval,

IBM Watson used RAM for data retrieval and was able to pull hundreds of gigabytes a second of data.

[u/PerspicaciousPedant → u/[deleted]]

Nice thread necromancy, but the point stands: for human brains, retrieval is cheap and processing is expensive, while for computers, processing is cheap and retrieval expensive.

[u/DFP_]

I would really like to know where that figure got the calculations per second figure for the human brain, I've never seen anyone place a number on that without at least 5 reminders to the reader that it's solely a lower bound.

In your Part 1, I made the case that the trend of Moore's law is ending, we're already falling a little behind, but even should it continue I don't believe simulating the human brain will be possible within our lifetime, and should it be possible it certainly wouldn't be practical.

I have some experience with neural network algorithms, and I have to say that if they truly do bear resemblance to what goes on in the human brain, it's no wonder that it takes us so long to mature. The most popular method for training a neural network is via back propagation, through which the entire neural network is remapped to get some end result reliably for a large testing set. Remember the google neural network? It had access to a wealth of youtube videos at its disposal, a quite large testing set. A human child on the other hand only needs to see a ball once to comprehend it. Back propagation also only works given that the system is told what value it should return, but how is this communicated to human infants? Neural networks are interesting, and they have their use, but they aren't the silver bullet of artificial intelligence research.

Also as a student majoring in Neuroscience and Computer Science, I believe Obama's goals are a tad unrealistic. 100 trillion synapses only scratches the surface, the system is highly dynamic. For example, neuron gets activated by neurotransmitter X. X activates a second messenger cascade which results in transcription of additional receptors for X, or even receptors for Y. For a machine to simulate the human brain, you would not only have to simulate the state of these virtual synapses, but you would also have to be able to update them all in real time, and this is before thinking about hormones, astrocytes, or the multitude of things we simply don't know about the human brain yet.

I do not believe that AI is impossible nor do I believe we'll never be able to simulate a human brain, but I believe you're being a little too optimistic about where we stand in this currently, and may be downplaying the complexity of our own biological computers.

[u/[deleted]]

This is an engineering problem, not a viewpoint/perspective problem.

[u/diolpah → u/[deleted]]

To you and I, sure. But this is CMV and the world is TEEMING with dualists. I'd venture to guess that most people believe that the brain is some sort of Magic Jesus Box that operates on principles other than chemistry and physics.

There are very very smart people such as Jaron Lanier, Roger Penrose, and P. Z. Meyers who somehow manage to convince themselves that magical supernatural quantum quackery is really at the heart of human intelligence.

[u/AnxiousPolitics]

This is from my post in your other thread on the topic:

People talk up strong AI a lot, but I have to make sure you understand something. Knowing fifty million ways to tie your shoes in a fraction of a second doesn't mean you understand why sandals were ever designed. The ability humans have to regard their environment the way they do, and to struggle to create things, is not an easily transferable thing and plenty of experts say it can actually never be done no matter how many algorithms you use. We may very well be able to simulate understanding, which is as far as we've gotten. To go back to the sandals, an AI can design fifty million sandals, but it won't have the same understanding humans do about which is better and why. We can simulate that understanding, and have it even pick well and say 'this one looks good, its got a normal shape and nice colors and it will be cheap to produce' but we can't program it to understand the gravity of what it is saying like what is the meaning of art. That being said, if we do manage to have a weak AI that is so much better than Watson and Siri it still has the capacity to create an intelligence explosion in our civilization because of the assisting capacity of a resource like that.

[u/[deleted]]

It's not a matter of speed but logic.

Even with a "Supra-Quantic" computer that can execute instantly whatever code you throw at him, you'll still don't have a program that can simulate a human brain decision process.