Human brains are energy inefficient? Well, thats a first ;)
"In 1990, the legendary Caltech engineer Carver Mead correctly predicted that our present-day computers would use ten million times more energy for a single instruction than the brain uses for a synaptic activation."
"Last March, AlphaGo, a program created by Google DeepMind, was able to beat a world-champion human player of Go, but only after it had trained on a database of thirty million moves, running on approximately a million watts. (Its opponent’s brain, by contrast, would have been about fifty thousand times more energy-thrifty, consuming twenty watts.)"
[1] http://www.newyorker.com/tech/elements/a-computer-to-rival-t...
The main difference is computer technology is designed to be very general purpose. The brain is more like an ASIC that's hardwired to run one specific algorithm. GPUs are also computing 16 or more bits of precision, when real neurons are very low precision. There are some other differences, like how real brains are incredibly sparse and most of the synapses at any given time are dormant and not using much energy. They are also very sparsely connected to each other. While our current NNs are very dense and need to spend energy to compute every single connection each cycle.
> "Last March, AlphaGo, a program created by Google DeepMind, was able to beat a world-champion human player of Go, but only after it had trained on a database of thirty million moves, running on approximately a million watts. (Its opponent’s brain, by contrast, would have been about fifty thousand times more energy-thrifty, consuming twenty watts.)"
Let's say alphaGo trained for a year, that would be 1 MWyr energy consumed. And lets assume that Lee Se-dol's brain consumed 20W over 34 years of his live doing nothing but working on Go, that would be 640 Wyr, still a factor 1000-ish smaller.
I mean, in principle, if you had two numbers, "human energy consumption from learning Go" and "AlphaGo energy consumption from learning Go", you could compare them. But in practice there's no way to come up with such numbers, so what's the point of comparing apples and orangutans?
You can expect a similar thing with Go at some point.
I'm sure any dollar store calculator spends way less energy performing long division than the average human.
And for another, Calculation != AI, far from actually.
12/43523523452. Go.
Two, AI is applied statistics. What do you think AI is?
>I'm sure any dollar store calculator spends way less energy performing long division than the average human
Thats the comment.
A calculator is a one role device, with exactly specified rules.
Similarly, with training you can too. You don't need to be special, other than being practiced,which is a fair requirement for a human being.
Here is a human being who could out perform it: https://en.wikipedia.org/wiki/Shakuntala_Devi
>In 1977, at Southern Methodist University, she gave the 23rd root of a 201-digit number in 50 seconds.[1][4] Her answer—546,372,891—was confirmed by calculations done at the US Bureau of Standards by the UNIVAC 1101 computer, for which a special program had to be written to perform such a large calculation.[10]
She could easily out-perform calculators because she never needed time to key in the commands (she needs to hear the problem to solve it).
If we exclude that restriction, and the commands magically float into the calculator, and that the problem is small enough to match the calculators limits, then yes, if those arbitrary conditions are met the calculator can out-perform her brain.
Which is precisely the type of “cows are round spheres” thinking that’s being decried in the article.
People can and regularly do out-perform calculators in speed, energy and complexity of computation.
Do note that calculators weren’t allowed as exam tools in a lot of countries till a decade or so ago. Students learnt mental math techniques which were known since ancient times (think Greece).
For a human brain the answer isn’t even calculation, it becomes pattern recognition. The square root of 25 is 5, which takes about the same neural load as it takes to recognize a letter.
The calculation you provided is harder, but thats a function of lack of training/practice, not complexity.
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AI is not in the realm of what a calculator can pull off, is what I meant to say by the compute part.
edit: I tried your computation on a store calculator, its beyond its ability to calculate,(0.0000000027)
But you're right to say calculators are single purpose devices and that's magically inserting the question.
So I downloaded sklearn, which contains a set of labelled hand-written digits.
It takes about 0.17-0.2 seconds for my laptop to learn to read numbers, from scratch, and thereafter it can read digits at a rate of about 8,200 per second.
For reference, "a blink of an eye" is 0.1-0.4 seconds depending on who you ask.
Dollar store calculator? I'd never have said that myself because I know calculators are rubbish. But in the context of "AI: Will it ever beat humans?" hell yes, it will and in many cases it already does.
https://youtu.be/-9T3P--ubQc?t=6m10s
Granted, these are people at the top of their game, so may not qualify as "normal" per your argument, but this is to illustrate that the limits of numerical calculation in "normal" people may be the algorithms we are taught rather than the computational capacity of our brains.
I'm of the opinion that that's an assumption being made. An article I read at one point supposed that our brains could have, as a way of example, a linking to quantum mechanics that we are not aware of due to not having yet discovered it that causes self-awareness. The point was not so much the mechanism, but that we can't yet rule out such a mechanism existing that our brain could have but our silicon currently doesn't — because we have no real idea what consciousness is, and we've not constructed an AI that proves that no such mechanism exists. If consciousness is intelligence, this could matter more (but this could also be another assumption).
(Unfortunately, I cannot find the article.)
(The article also went on to note that we can copy computer programs, but not brains, and wondered if perhaps there is some relation to the previous problem. It was also advocating that we need a testable hypothesis around consciousness; to either prove or disprove the question "is it possible to clone a brain?" would be an extraordinary discovery either way. I found it interesting.)
> Imagine an AI brain that is optimized for the purpose of mathematics, or computer programming, science, or engineering. Or at doing AI research... Imagine how much better it could be at these tasks than humans. It could quickly solve problems that would take the greatest human minds generations. It could manage levels of complexity that would drive humans crazy.
I'm just wishing for an automatic soap dispenser that can reliably sense my hand.
Quantum-based self-awareness is a cop-out IMO, an open way to claim that it comes from God. Well, if that's true and it's beyond our reach, then we'll never build a self-aware AI ourselves. But assuming something is impossible doesn't help moving forward...
Not so much an assumption as a reasonable guess. Is it logically possible that there's something magical about human brains? Yes.
But there are countless examples of things we thought were magical historically, and, as far as I know, exactly zero that we've ended up concluding actually were magical, and a large number that we're pretty confident aren't at this point.
The smart money here is on "no, the human brain isn't magical."
If we've made a science out of it, no matter how advanced it is, it's not magic — e.g. if telekinesis was possible, it would have a scientific explanation and be a natural power — which bares some similarly to the way things are called "artificial intelligence" when they're impossible, only to be reduced to "trivial" when someone makes a machine do them: Chess, Go, having a large vocabulary or knowing many languages, being good at arithmetic or being able to do calculus at all, writing music or news stories, trading on the stock market — all things that used to be synonymous with genius, yet all done by machines we don't call intelligent.
That's not an article but a whole book:
I just want to point out that some recent research indicates that this might not actually be true. Single neurons may be more complex than we thought since researchers managed to extract significant and complex functionality from single neurons (!). Not to mention glia seem to be important for cognition, and not just glue as we thought... So perhaps not as wasteful and kludgy as we might think :)
You can think of intelligence as a couple of dimensions rather than just one dimension as the author is arguing. However I don't agree with his/her logic.
You can think of the brain as a massively parallel computer. Intelligence can be gauged by total cores, memory and CPU per core, power usage and network bandwidth between cores. Sure different configurations will give different strengths but something optimized atomically for performance will be faster than a mushy brain.
Now imagine a billion of this little pods placed all over the planet. With amazing bandwidth between the computers akin to our internet.
Worst case: they think humans are the enemy and out think us to extinction.
Best case: studying intelligence helps us figure out how Brians work. This helps us figure out how DNA nano manufacturing works. We figure out brain to brain and brain to AI networking. Now all humans are collectively a super computer being able to share knowledge and abilities. May be this is extended so animals are also included and Earth becomes a Pandora like planet where every living thing is connected and they all live in harmonius resource optimized world where AI tries to maximize happiness of every living being.
The hype chamber in SV is on overdrive on AI at this point.
Singularity AI concept has gone from the neat Sci Fi idea it was, to being treated as a serious possibility. This is Absurd. The modern version of Malthus, and a community of people who pride themselves on their reason, should do a basic sniff test.
The author has it correct - human brains themselves are significantly impressive on a weight/power/capability scale.
But forget all of the intelligence debate, consider the things that people magically ignore: emotions.
Take a look at how people who are depressed function. They measured as being more aware than (better assessment of their surroundings/relations/self assesment) people who were not.
At the same time, they lack motivation, or desire - there is a lack of impulsive force to move forward.
Intelligence doesn't give human beings purpose. Emotion does.
This isn't feel good psychobabble, its a fundamental part of good mind/body housekeeping which a huge chunk of SV follows every day to reach "peak performance".
How are you going to create a general purpose AI which has any motive force?
Its actually MORE LIKELY, that if a GP AI is created, its just going to sit on its ass and pretend not to understand instructions.
So would an explicit goal function, which is how we already give "purpose" to algorithms.
> How are you going to create a general purpose AI which has any motive force?
In any other out of countless of ways to do that. What makes you think that emotions are necessary to create a powerful optimization process?
The "motive force" is mostly a solved problem for now, we can code that explicitly (the issue is with figuring out a right goal and how to write it down). AI development is mostly about the way it works, not why it should do the work.
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No offense meant to you personally, but I find that most of the comments about "overdriven AI dangers focus in SV" to reveal that authors don't have a fucking clue what the issue is about, and never spent time actually reading up the reasoning behind the AI X-risk potential.
I'll give an ultra-compressed super-TLDR of that reasoning for benefit of future conversations. It goes like this:
- intelligence is a super-strong optimization process; it doesn't necessarily have to look the way humans think (humans generally suck at reasoning, which is well established; see: cognitive biases, probability theory, decision theory, etc.)
- intelligence is an independent factor from values/goals, a mind can have any combination of the two - i.e. just because it's smart, it doesn't mean it will develop the same morality humans do, or any morality whatsoever; see https://wiki.lesswrong.com/wiki/Orthogonality_thesis
- combining the two, the danger of super-human AI is not something that's hostile to us - it's something that's indifferent about us, and is more powerful than us, the same way we don't give a second thought about e.g. ants
That's interesting. Do you have a reference for that?
This is me if i was an AI.
1. Bootstrap. In order to really take off, AI needs to be able to build better AI.
2. AI needs to be adaptable. Any human go player can play on 19x20 board. AlphaGo (a program that that on 19x19 board beats top professionals 60:0) could not even make a legal move.
3. AI should be resilient. Right now it runs on hardware made by humans and blindly relies on that hardware working perfectly all the time.
There is nothing magical about anything. There is however a bunch of unkowns, and a lot of knowns that point in directions away from singularity babble.
This is exactly the point of the article - that we aren't going to a singularity, we are going towards a "Cambrian explosion"
That may not even be true, we're just not smart enough to make the call one way or the other. Dolphins come to mind, as well as several other creatures (Squid, Apes). The fact that we can't rule it out is in a way proof that maybe we're not as smart as we would like to think we are.
Same with the solar system. We can create simulated solar systems. We will probably be able to make simulated brains. What is your point?
Alright, assuming the first AI even is a simulated brain (I don't see why we can't invent intelligence from first principles first.) We could definitely tweak it. We know of drugs like amphetamines that enhance human ability. That's like Stone Age tech compared to what's possible if we had unlimited control over every neuron in the entire brain. Not to mention just adding more neurons and making a larger brain. This is just touching on what's possible, I could go on for ages on possible improvements.
In everyday life, we treat other minds more like "maps" than like "nuclear reactions". We interact with nuclear reactions by getting radiation sickness and dying. We interact with people through more indirect channels. A simulation could be at the other end of the channel and we wouldn't know. Maybe he wouldn't now, either!
We don't get electrocuted when our interlocutor's neurons are firing, the effects on us are only through his external behaviour. It's the abstract informational flow what seems to matter.
That sounds like a really interesting experiment. Have you published your data?
A nitpick: the neurons actually do use electricity to send signals and (looking at the neuronal model in its history¹) it actually evolved to send signals along as fast as it could. The chemical component, AFAIK, is the physical implementation for memory, so this is kind of the storage class regarding operation performance. Overall though, I agree that our cerebral organ may not be the apogee of computational performance.
¹ As far as I remember, the dinosaur neurons didn't had myelin, which for some large animals caused non-trivial sensorial delay.
What other intelligence evolved, and in what sense human brain is first in evolution?
We've seen no other creatures on Earth being able to grow beyond using basic tools.
But this also somewhat implies (which is GP's point) that we're close to the dumbest possible mind that evolution could make that could still develop science. Or think of it as a crude MVP that ended up being a production system.
To claim something as first, there must be others in reality to have followed it. If there is no second, there would be no first. Is there a second intelligence to have invented science, or we are the only ones?
When somebody comes up with a reasonable, detailed model of how my memories are stored (just to name an example), I shall once again start paying close attention to the whole AI field.
Human brains are incredibly small, a few pounds of matter. Any bigger and your mother would be killed giving birth or you would take 10x as long to grow up. They are incredibly energy constrained, only using a few watts of power. Because any more and you would starve to death. They are incredibly slow and energy inefficient; communication in the brain is done with chemical signals that are orders of magnitude slower than electricity and use much more energy. And they are very uncompact - neurons are enormous and filled with tons of useless junk that isn't used for computation. Compared to our transistor technology which is approaching the limits of physics and built on an atom by atom scale.
That's just the hardware specs of the human computer. The software is hardly better. There are just more unknowns because we haven't finished reverse engineering it (but we are getting there, slowly.)
But beyond that, the human brain evolved to be good at surviving on the Savanahs of Africa. We didn't evolve to be good at mathematics, or science, or engineering. It's really remarkable that our brains are capable of such things at all! We have terrible weaknesses in these areas. For instance, a very limited working memory. We don't realize how bad we are, simply because we have nothing else to compare ourselves to.
Consider how even today, relatively primitive AIs are vastly superior to humans at games like chess. Human brains also didn't evolve to be good at chess after all. Even simple algorithms designed specifically for this game easily mop up humans. And play at a level of strategy far above what even the best human players can comprehend.
Imagine an AI brain that is optimized for the purpose of mathematics, or computer programming, science, or engineering. Or at doing AI research... Imagine how much better it could be at these tasks than humans. It could quickly solve problems that would take the greatest human minds generations. It could manage levels of complexity that would drive humans crazy.