Face It, Your Brain Is a Computer(nytimes.com)
nytimes.com
Face It, Your Brain Is a Computer
http://www.nytimes.com/2015/06/28/opinion/sunday/face-it-your-brain-is-a-computer.html?action=click&pgtype=Homepage&module=opinion-c-col-right-region®ion=opinion-c-col-right-region&WT.nav=opinion-c-col-right-region&_r=0
13 comments
I agree; saying "the brain is a computer" is much like saying "the universe is a computer".
We can simulate the universe with astounding accuracy on many levels (though not all) with computers. Furthermore, when studying the universe deeply we see astoundingly computer-like traits[1]. But to express this by saying the universe is a computer is very misleading.
Similarly, artificial neural networks simulated by computers achieve huge strides in AI, accomplishing things many said would always be impossible (e.g. art[2]). Also, we see many computer-like traits in the brain. But to express this by saying the brain is a computer is very misleading.
[1] http://lmgtfy.com/?q=the+universe+is+a+computer+simulation
[2] http://googleresearch.blogspot.ca/2015/06/inceptionism-going...
We can simulate the universe with astounding accuracy on many levels (though not all) with computers. Furthermore, when studying the universe deeply we see astoundingly computer-like traits[1]. But to express this by saying the universe is a computer is very misleading.
Similarly, artificial neural networks simulated by computers achieve huge strides in AI, accomplishing things many said would always be impossible (e.g. art[2]). Also, we see many computer-like traits in the brain. But to express this by saying the brain is a computer is very misleading.
[1] http://lmgtfy.com/?q=the+universe+is+a+computer+simulation
[2] http://googleresearch.blogspot.ca/2015/06/inceptionism-going...
> and my brain doesn't have a von neumann architecture
"Computer" doesn't automatically equal "von neuman architecture".
> nor does it run something similar to our software
A lack of software-equivalent is a pretty good criticism, though.
"Computer" doesn't automatically equal "von neuman architecture".
> nor does it run something similar to our software
A lack of software-equivalent is a pretty good criticism, though.
>"Computer" doesn't automatically equal "von neuman architecture".
No, but that's what most people are familiar with (if they are familiar with computer architectures in the first place), so it pretty much equals that for them.
No, but that's what most people are familiar with (if they are familiar with computer architectures in the first place), so it pretty much equals that for them.
> that's what most people are familiar with (if they are familiar with computer architectures in the first place)
They're not. There's really only two kinds of people here—those who are unfamiliar with computer architecture (99% of the population), and those who are familiar with Von Neumann architecture, and know that it's not the only game in town.
They're not. There's really only two kinds of people here—those who are unfamiliar with computer architecture (99% of the population), and those who are familiar with Von Neumann architecture, and know that it's not the only game in town.
I agree, calling it a computer is the origin of a lot of confusion. Perhaps "information processing" is a better term.
I think the key fail is hidden beneath this statement, 'many “digital” computer switches are built out of analog components and processes'. In fact obviously, all computers are built out of analog components, in the sense that the entire universe is analog.
However, this is the problem. Computers are designed to interpret or translate the messy analog world where nothing is exactly 1 or 0, into a precise, deterministic digital world where everything is either 1 or 0. And I think it's highly likely that the brain does not work in this manner whatsoever, and that in fact, in the translation of reality into 1s and 0s, you've lost far too much to properly "compute consciousness"
Would it be possible to build a synthetic brain out of some form of "analog computer", capable of consciousness? Almost certainly. But since we have no idea what sort of architecture or paradigm that would use, or how we would program it or whether it would even "execute instructions" in a way remotely similar to digital computer software, such a declaration becomes meaningless.
However, this is the problem. Computers are designed to interpret or translate the messy analog world where nothing is exactly 1 or 0, into a precise, deterministic digital world where everything is either 1 or 0. And I think it's highly likely that the brain does not work in this manner whatsoever, and that in fact, in the translation of reality into 1s and 0s, you've lost far too much to properly "compute consciousness"
Would it be possible to build a synthetic brain out of some form of "analog computer", capable of consciousness? Almost certainly. But since we have no idea what sort of architecture or paradigm that would use, or how we would program it or whether it would even "execute instructions" in a way remotely similar to digital computer software, such a declaration becomes meaningless.
> Computers are designed to interpret or translate the messy analog world where nothing is exactly 1 or 0, into a precise, deterministic digital world where everything is either 1 or 0. And I think it's highly likely that the brain does not work in this manner whatsoever
But neurons totally do work by encoding information with discrete signals.
https://en.wikipedia.org/wiki/Action_potential#Process_in_a_...
Action potentials are discrete events, and just like hi or lo in a silicon computer actually correspond to a range of voltages, the exact voltage-vs-time curve of an action potential likely has considerable flexibility.
But neurons totally do work by encoding information with discrete signals.
https://en.wikipedia.org/wiki/Action_potential#Process_in_a_...
Action potentials are discrete events, and just like hi or lo in a silicon computer actually correspond to a range of voltages, the exact voltage-vs-time curve of an action potential likely has considerable flexibility.
The brain is neither analog nor digital. The brain encodes information sent between cells as pulses. The timing of these pulses is where the information is encoded.
As such it is transmitting a fourier transform of the signal it is transmitting between the cells (but with different basis functions, not cosines). When a pulse is received, this will result in a sudden jump of the action potential, and then slowly die down. If a second pulse comes while the first is still in action it gets multiplied by the current value of (this particular) input potential. Rapid pulsing (3-4 ms between pulses) means something along the lines of "multiply membrane potential by 10 for every pulse", whereas a pulse width of ~350ms means "keep the membrane potential constant". Any one of these pulses may push a neuron "over the edge" and have it transmit a pulse of it's own (or a series of pulses as pulsing the axon lowers the membrane potential by a factor. This may or may not cause it to go below the trigger level, and so sometimes the axon needs to pulse multiple times to get the membrane potential back below the trigger).
This is a beautiful way to encode simplifications of analog signals. It's log scale in the sense that 2 rapid pulses encode that the function value should be an order of magnitude larger than 2 slow pulses. It is extremely sparse (pulsing speeds rarely exceed 1hz, and only for short times) so it is quite energy efficient. Your brain quite literally does nothing at all unless there's actual information to process. I find it a bit misleading that wikipedia says that the frequency of pulses encodes the info : it's true, but makes one think this frequency is constant, when in fact it is changing rapidly. Does the word frequency really make sense when any 2 measurements of pulse frequency will be different ?
Normally one would call pulses digital, because they are 1 or 0. Values in between are interpreted as being either 1 or 0, definitely not analog. But the time spacing between the pulses is what matters, and this is measured to astonishing accuracy by a chemical reaction. A measurement like that, one would normally call analog. So it doesn't really match either signal type ... It is very different from any analog or digital signal I know about.
One might say your neurons contain an encoded, but uncompressed mp3 of the signal they're transferring between neuron membranes : it's transmitting in the frequency domain, but without the compression that reduces the zeroes, so it's sending very long series of zeroes, interspersed with the very occasional one. This works well because transmitting a zero is done by doing nothing at all.
As such it is transmitting a fourier transform of the signal it is transmitting between the cells (but with different basis functions, not cosines). When a pulse is received, this will result in a sudden jump of the action potential, and then slowly die down. If a second pulse comes while the first is still in action it gets multiplied by the current value of (this particular) input potential. Rapid pulsing (3-4 ms between pulses) means something along the lines of "multiply membrane potential by 10 for every pulse", whereas a pulse width of ~350ms means "keep the membrane potential constant". Any one of these pulses may push a neuron "over the edge" and have it transmit a pulse of it's own (or a series of pulses as pulsing the axon lowers the membrane potential by a factor. This may or may not cause it to go below the trigger level, and so sometimes the axon needs to pulse multiple times to get the membrane potential back below the trigger).
This is a beautiful way to encode simplifications of analog signals. It's log scale in the sense that 2 rapid pulses encode that the function value should be an order of magnitude larger than 2 slow pulses. It is extremely sparse (pulsing speeds rarely exceed 1hz, and only for short times) so it is quite energy efficient. Your brain quite literally does nothing at all unless there's actual information to process. I find it a bit misleading that wikipedia says that the frequency of pulses encodes the info : it's true, but makes one think this frequency is constant, when in fact it is changing rapidly. Does the word frequency really make sense when any 2 measurements of pulse frequency will be different ?
Normally one would call pulses digital, because they are 1 or 0. Values in between are interpreted as being either 1 or 0, definitely not analog. But the time spacing between the pulses is what matters, and this is measured to astonishing accuracy by a chemical reaction. A measurement like that, one would normally call analog. So it doesn't really match either signal type ... It is very different from any analog or digital signal I know about.
One might say your neurons contain an encoded, but uncompressed mp3 of the signal they're transferring between neuron membranes : it's transmitting in the frequency domain, but without the compression that reduces the zeroes, so it's sending very long series of zeroes, interspersed with the very occasional one. This works well because transmitting a zero is done by doing nothing at all.
Though, not all neuroscientists are on the same page nor agree with the claims some people want to make…
"The frequency of action potentials (APs) generated by neurons is correlated with different events; however, it does not mean that such events are ‘encoded’ in the brain using the firing rate or any other ‘temporal code ’ (e.g. interspike interval)…
…Simultaneous firing of action potentials (synchrony) in a neuronal ensemble increases the interaction of many- body systems and implicitly boosts the computational power [7]. The well accepted model of ‘activation function’ that describes artificial neurons simulated on Turing Machines does not approximate the process of ‘solving equations’. Therefore, the popular claim that current artificial neurons and neural networks are ‘realistic’ models of their biological counterparts is misconstrued and untrue."[0]
[0] http://arxiv.org/ftp/arxiv/papers/1210/1210.1983.pdf
"The frequency of action potentials (APs) generated by neurons is correlated with different events; however, it does not mean that such events are ‘encoded’ in the brain using the firing rate or any other ‘temporal code ’ (e.g. interspike interval)…
…Simultaneous firing of action potentials (synchrony) in a neuronal ensemble increases the interaction of many- body systems and implicitly boosts the computational power [7]. The well accepted model of ‘activation function’ that describes artificial neurons simulated on Turing Machines does not approximate the process of ‘solving equations’. Therefore, the popular claim that current artificial neurons and neural networks are ‘realistic’ models of their biological counterparts is misconstrued and untrue."[0]
[0] http://arxiv.org/ftp/arxiv/papers/1210/1210.1983.pdf
Wow, fantastic paper:
However, the relevance of Turing model is questioned even in case of present-day computing [33] [34]. Indeed, any computing machine that follows a Turing model would be highly inefficient to simulate the activity of biological neurons and experience an increased slowdown. Since the super-Turing computing power of the brain has its origins in these ‘strong’ interactions that occur inside neurons, current models have missed the most important part. Simply, Nature doesn’t care if the N-body problem has analytical solutions [36] or can be simulated in real time on a Turing machine [37].
...
While previous models have attempted to represent Hamiltonians using Turing machines [35] the paper [1] shows that the Hamiltonian model of interaction can represent itself a far more powerful model of computation. Turing made an important step forward; however, there is no need to limit natural models of computation to Turing models. In this sense, the new framework of computation using interaction is universal in nature and provides a more general description of computation than the formal Turing model. In other words God was unaware of Turing's work and has put forward a better model for physical computation in the brain.
However, the relevance of Turing model is questioned even in case of present-day computing [33] [34]. Indeed, any computing machine that follows a Turing model would be highly inefficient to simulate the activity of biological neurons and experience an increased slowdown. Since the super-Turing computing power of the brain has its origins in these ‘strong’ interactions that occur inside neurons, current models have missed the most important part. Simply, Nature doesn’t care if the N-body problem has analytical solutions [36] or can be simulated in real time on a Turing machine [37].
...
While previous models have attempted to represent Hamiltonians using Turing machines [35] the paper [1] shows that the Hamiltonian model of interaction can represent itself a far more powerful model of computation. Turing made an important step forward; however, there is no need to limit natural models of computation to Turing models. In this sense, the new framework of computation using interaction is universal in nature and provides a more general description of computation than the formal Turing model. In other words God was unaware of Turing's work and has put forward a better model for physical computation in the brain.
I thought it was fantastic as well (because you know a theory that tries to incorporate our understanding of matter and energy [which the brain is a subset of] in a field with a lot of hand-waving going on, shouldn't be that radical…), though for most neuroscientists it is out of reach because for the most part, have little to no understanding of electromagnetism (let's set aside the QED versions of Maxwell's equations) from my experience, which is quite ironic considering the tools that are in heavy use…
The amount of money being wasted trying to make special FMRI's and custom EEG caps is lost on me when attempting to solve equations along variable boundary conditions seems like it should come first…
Here's the paper the author wrote which that paper is branched from: http://www.researchgate.net/profile/Dorian_Aur/publication/2...
The amount of money being wasted trying to make special FMRI's and custom EEG caps is lost on me when attempting to solve equations along variable boundary conditions seems like it should come first…
Here's the paper the author wrote which that paper is branched from: http://www.researchgate.net/profile/Dorian_Aur/publication/2...
Thanks! That paper/book is going on the reading list. I need to bring this up with some neuroscience friends.
You can approximate any analog value to arbitrary precision using a (by nature binary) Turing Machine, therefore you can bring the loss of information as low as needed.
The question is whether the brain offers a more complete framework than all the models of computation we know today (which are equivalent to one another). To put it another way : is there a function that the brain can compute that a Turing Machine cannot. We know of no such function now, but have ruled out yet that there is none, although most computer scientist agree with the Church-Turing hypothesis.
The question is whether the brain offers a more complete framework than all the models of computation we know today (which are equivalent to one another). To put it another way : is there a function that the brain can compute that a Turing Machine cannot. We know of no such function now, but have ruled out yet that there is none, although most computer scientist agree with the Church-Turing hypothesis.
But this is effectively begging the question. If you assume that reality can be completely described by functions that compute on natural numbers, then obviously anything within reality, including consciousness, can be simulated by a Turing machine.
Unless I've missed something, it's not actually been shown that the universe itself is Turing-computable, therefore there's no reason to assume everything within the universe could be equivalently simulated on a Turing machine.
It could also be that in theory, consciousness is Turing computable, but not in practice. For example just computing a protein fold for 1 millisecond takes hundreds of ASICs days of compute time. This might give some clue that complex physical wetware processes are not able to be efficiently simulated in real time on any realistic Turing machine.
Unless I've missed something, it's not actually been shown that the universe itself is Turing-computable, therefore there's no reason to assume everything within the universe could be equivalently simulated on a Turing machine.
It could also be that in theory, consciousness is Turing computable, but not in practice. For example just computing a protein fold for 1 millisecond takes hundreds of ASICs days of compute time. This might give some clue that complex physical wetware processes are not able to be efficiently simulated in real time on any realistic Turing machine.
> And I think it's highly likely that the brain does not work in this manner whatsoever, and that in fact, in the translation of reality into 1s and 0s, you've lost far too much to properly "compute consciousness"
You act as though the only datatype usable by computers is bool. That's ridiculous. Yes, computers are binary, but they can compute analog things just fine via floating or fixed point arithmetic to arbitrarily high precision, among many other things. To claim that the brain has a fundamental advantage over a Turing machine is to claim that there's some magical quantum (or otherwise) advantage in the brain's physical system that is un-simulate-able by a Turing machine.
You can't even argue that analog provides superior precision to digital representation of continuous values, because the analog part of the brain is represented with discrete units (accumulation of neurotransmitter molecules in various parts of the neuron)! In other words, our brain actually uses fixed point math (granted, incredibly complicated fixed point math :))
You act as though the only datatype usable by computers is bool. That's ridiculous. Yes, computers are binary, but they can compute analog things just fine via floating or fixed point arithmetic to arbitrarily high precision, among many other things. To claim that the brain has a fundamental advantage over a Turing machine is to claim that there's some magical quantum (or otherwise) advantage in the brain's physical system that is un-simulate-able by a Turing machine.
You can't even argue that analog provides superior precision to digital representation of continuous values, because the analog part of the brain is represented with discrete units (accumulation of neurotransmitter molecules in various parts of the neuron)! In other words, our brain actually uses fixed point math (granted, incredibly complicated fixed point math :))
> To claim that the brain has a fundamental advantage over a Turing machine is to claim that there's some magical quantum (or otherwise) advantage in the brain's physical system that is un-simulate-able by a Turing machine.
Again, please point to any research you know of indicating that the universe itself is fully Turing-computable.
Again, please point to any research you know of indicating that the universe itself is fully Turing-computable.
Universe doesn't have to be, just neurons and other brain hardware.
Of course you can always see quantum phenomena affecting outcome, you just have to rule those out as neligible / much lower than noize threshold.
Of course you can always see quantum phenomena affecting outcome, you just have to rule those out as neligible / much lower than noize threshold.
There are many functions which cannot be computed on a Turing Machine.
https://en.wikipedia.org/wiki/Computable_function#Uncomputab...
https://en.wikipedia.org/wiki/Computable_function#Uncomputab...
>in the sense that the entire universe is analog.
Citation needed.
Citation needed.
The only serious counter-argument I've heard against the hypothesis that the brain goes further than a Turing machine is that the brain does not implement an algorithm, with one input, some processing steps, and one output.
Instead, it processes information as it comes, this information comes during the processing of previous information and the output partly loops back to the input. Short-circuits everywhere, no clock, etc. I'm unconvinced but I could not refute the argument formally.
Note that this does not contradict the Church-Turing Hypothesis : if you restrict the brain to one input, some processing steps with a pen and paper without arrival of new information, and an output, then it is very possible that the brain can only work out Turing-computable problems.
Instead, it processes information as it comes, this information comes during the processing of previous information and the output partly loops back to the input. Short-circuits everywhere, no clock, etc. I'm unconvinced but I could not refute the argument formally.
Note that this does not contradict the Church-Turing Hypothesis : if you restrict the brain to one input, some processing steps with a pen and paper without arrival of new information, and an output, then it is very possible that the brain can only work out Turing-computable problems.
'information comes during the processing of previous information and the output partly loops back to the input"
Computers do this all the time. Simplest example is "cancel" button everywhere.
Computers do this all the time. Simplest example is "cancel" button everywhere.
The point is that out definition of the computability of a function is too narrow, and does not take into account the real-time all connected nature of the computation the brain does.
Therefore, we lack formal way of satisfactorily compare the brain to a Turing Machine.
Therefore, we lack formal way of satisfactorily compare the brain to a Turing Machine.
I don't see why. Your computer reacts to keyboard and mouse in the real time, also for network packets going in and out. And it's plain turing machine. It does so by regarding every input as they become available, one by one.
Information comes to brain via neurons, and those have finite speed, it's not as they had quantum-like properties. Signal in; signal out, with delay and altered magnitude.
Information comes to brain via neurons, and those have finite speed, it's not as they had quantum-like properties. Signal in; signal out, with delay and altered magnitude.
The important word is : formal.
I, too, think that the brain is 'a computer'. But the formal definitions of computation we have today require the computer to be left alone for some time between the moment the input is given and the moment the output is due. The brain does not work like that, ergo we lack a formal model of how the brain operates, and thus the definition of 'computable function' -which is based on our model of computation- is less general than what the brain can do.
e.g. We have no proof that the only way neurons communicate with one another is via the synapses.
I, too, think that the brain is 'a computer'. But the formal definitions of computation we have today require the computer to be left alone for some time between the moment the input is given and the moment the output is due. The brain does not work like that, ergo we lack a formal model of how the brain operates, and thus the definition of 'computable function' -which is based on our model of computation- is less general than what the brain can do.
e.g. We have no proof that the only way neurons communicate with one another is via the synapses.
Brain, too, needs some time to react to any incoming event.
I fail to capture the difference.
I fail to capture the difference.
I don't think that we are in the territory of having that argument at all to be honest. We don't know what the processes that the brain self evidently generates are - for example Intelligence, Consciousness. It isn't possible to discuss how these are executed (or not, depending) until we have some understanding of what they really are.
And we don't, and worse, we may not ever have access to these concepts, as Hofstadter and others have argued. It may not be possible to represent the idea of ideas in an idea.
That of which we cannot speak that thereof we must remain silent, or something.
And we don't, and worse, we may not ever have access to these concepts, as Hofstadter and others have argued. It may not be possible to represent the idea of ideas in an idea.
That of which we cannot speak that thereof we must remain silent, or something.
> The only serious counter-argument I've heard against the hypothesis that the brain goes further than a Turing machine
I'm confused... is the counter-argument AGAINST the brain being BEYOND a Turing machine (if I am to interpret your sentence literally)?
Or by this double negative do you actually mean the counter argument is AGAINST the brain being ONLY a Turing machine? (Because that's what the rest of your post sounds like.)
> and the output partly loops back to the input.
So? Turing machines have no issues with feedback loops; what would lead you to think they do?
I'm confused... is the counter-argument AGAINST the brain being BEYOND a Turing machine (if I am to interpret your sentence literally)?
Or by this double negative do you actually mean the counter argument is AGAINST the brain being ONLY a Turing machine? (Because that's what the rest of your post sounds like.)
> and the output partly loops back to the input.
So? Turing machines have no issues with feedback loops; what would lead you to think they do?
The counter argument to the CT hypothesis, i.e. the argument against, sorry for my ambiguous phrasing.
I'm a dualist but for the sake of argument, one approach is to claim that however the brain functions, it should be explainable by physics, and if physics is computable, then it should in principle be simulable by a Turing Machine.
The question of whether physics is computable is a fascinating one I'd really like to see solved before I die.
Physics is most probably computable, since people created it; the real question is whether the world is (Turing) computable, and from my point of view it is clearly not. I find it remarkable that most people believe it is or that it might be.
I'll never forget hearing Jerry Lettvin [0] pronounce, in his slow, measured, way: "The brain is not a computer. The brain is a gland."
I think he said it partly to tweak his MIT AI Lab audience (this must have been about 1982). But he had a point: a lot goes on in the brain that is not digital.
[0] https://en.wikipedia.org/wiki/Jerome_Lettvin
I think he said it partly to tweak his MIT AI Lab audience (this must have been about 1982). But he had a point: a lot goes on in the brain that is not digital.
[0] https://en.wikipedia.org/wiki/Jerome_Lettvin
My computer also doubles as fan and vacuum cleaner.
This is entirely backwards.
Computers are designed to emulate brains. More specifically, to perform a certain category of brain activity (calculation).
To date, a brain is still needed to make a computer do anything. No brain, no software; no software, all we have is an inert lump of metals and plastics.
We should be quite wary of reversing metaphors in this fashion. 19th century psychology contained a number of metaphors derived ultimately from the steam engine, for human consciousness, and for reality. All we've done is update the machine; the comparison is still backwards.
Computers are designed to emulate brains. More specifically, to perform a certain category of brain activity (calculation).
To date, a brain is still needed to make a computer do anything. No brain, no software; no software, all we have is an inert lump of metals and plastics.
We should be quite wary of reversing metaphors in this fashion. 19th century psychology contained a number of metaphors derived ultimately from the steam engine, for human consciousness, and for reality. All we've done is update the machine; the comparison is still backwards.
Any reasonable definition of computer includes things that can do arithmetic, and since brains can do that, brains are computers.
The distinction between analog and digital computers doesn’t seem to be so important to me. Any computation that an analog computer can do, can also be done with digital computers and vice versa. Digital computers can process continuous-time signals as precise as analog computers, and analog computers can do logic. Which kind of computer you use depends on convenience with respect to the resources and computational problem in hand.
The “brains don’t download software” part also isn’t convincing. Brains are capable of manipulating symbols, but the rule set needs to be learned in the case of arithmetic, or selected, in the case of natural language according to inputs. Also, software doesn’t have to be like “1. Do this, 2. Do that, 3. End”, like the article implies. The brain can be running on a game loop, planning future actions according to some stochastic utility function.
Also, I find it useful when thinking about brains to separate the functions that are done unconsciously from those that are not. To me, unconscious functions of the brain seem more like using specialised hardware. Of course, those parts are almost certainly doing computation to full their functions, but it is “not abstract symbol manipulation according to some learnable rules” that people associate with consciousness.
The distinction between analog and digital computers doesn’t seem to be so important to me. Any computation that an analog computer can do, can also be done with digital computers and vice versa. Digital computers can process continuous-time signals as precise as analog computers, and analog computers can do logic. Which kind of computer you use depends on convenience with respect to the resources and computational problem in hand.
The “brains don’t download software” part also isn’t convincing. Brains are capable of manipulating symbols, but the rule set needs to be learned in the case of arithmetic, or selected, in the case of natural language according to inputs. Also, software doesn’t have to be like “1. Do this, 2. Do that, 3. End”, like the article implies. The brain can be running on a game loop, planning future actions according to some stochastic utility function.
Also, I find it useful when thinking about brains to separate the functions that are done unconsciously from those that are not. To me, unconscious functions of the brain seem more like using specialised hardware. Of course, those parts are almost certainly doing computation to full their functions, but it is “not abstract symbol manipulation according to some learnable rules” that people associate with consciousness.
As long as science keeps thinking this, we won't have to worry about the singularity any time soon.
The problem here is that the so called singularity does not necessarily depend on machines having the so called qualia.
My closest belief is near similar as mentioned in article, that brain, at some level has some "computational primitive", which resembles transistor functionality.
But that is only one level. There can be additional layers of function, which can be influenced by sub-atomic entities, like elementary particles. We still don't know how deep this goes. This is, what most likely, provides depth of our consciousness.
Our biological hardware is built out of finite atoms. Consciousness unfolds out of "electrochemical circuits". Electricity == consciousness.
We have what is called "human energy" - emotions are one example of expressions out of it.
For AI, to be human like, it has to simulate physical behaviour of human energy.
I see, that out of this energy behaviour simulations can emerge what I call "computational psychology". That is, computer could analyze and decode human behaviour and "understand" like psychologist does this.
Thing is, that many people don't see these subtle patterns - they are learned over lifetime with different success rates. Once they are aware of these patterns, they can function more efficiently as a human. Such "psychologist as app in your pocket" potentially can raise overall quality of society.
But that is only one level. There can be additional layers of function, which can be influenced by sub-atomic entities, like elementary particles. We still don't know how deep this goes. This is, what most likely, provides depth of our consciousness.
Our biological hardware is built out of finite atoms. Consciousness unfolds out of "electrochemical circuits". Electricity == consciousness.
We have what is called "human energy" - emotions are one example of expressions out of it.
For AI, to be human like, it has to simulate physical behaviour of human energy.
I see, that out of this energy behaviour simulations can emerge what I call "computational psychology". That is, computer could analyze and decode human behaviour and "understand" like psychologist does this.
Thing is, that many people don't see these subtle patterns - they are learned over lifetime with different success rates. Once they are aware of these patterns, they can function more efficiently as a human. Such "psychologist as app in your pocket" potentially can raise overall quality of society.
You should read the book On Intelligence by Jeff Hawkins. Pay attention to Chapter 6, "How the cortex works". Our "consciousness" is derived of the same stuff in all animals, we just have more cortical layers. We also have fuzzy algorithms which allow the brain to recognize patterns, and associate x with y.
http://www.amazon.com/On-Intelligence-Jeff-Hawkins/dp/080507...
I think to postulate that there's a yet undiscovered subatomic elementary particle that gives rise to consciousness is hogwash. "Consciousness" or awareness of self has been shown in other animals. Humans are distinct in their ability to couple self-awareness and toolmaking.
There is no "human energy" it's the same material as in all other animals, we just have more of it. The "human energy" could be classified as distinct fuzzy algorithms found in humans which aid pattern recognition.
http://www.amazon.com/On-Intelligence-Jeff-Hawkins/dp/080507...
I think to postulate that there's a yet undiscovered subatomic elementary particle that gives rise to consciousness is hogwash. "Consciousness" or awareness of self has been shown in other animals. Humans are distinct in their ability to couple self-awareness and toolmaking.
There is no "human energy" it's the same material as in all other animals, we just have more of it. The "human energy" could be classified as distinct fuzzy algorithms found in humans which aid pattern recognition.
Not one elementary particle, but whole interaction of many of them.
Yes, animals have that same substance, but at lesser scale.
I make distinction between pure intellect, which computer can do fine, and other component, which I doubt that it can be accessed by computer without connecting silicon with biological material.
Yes, animals have that same substance, but at lesser scale.
I make distinction between pure intellect, which computer can do fine, and other component, which I doubt that it can be accessed by computer without connecting silicon with biological material.
(1) A computer is anything that does computations, and a computation is just a set of states that are partially ordered with respect to a “next” state relation.
(2) A universal computer is a computer that can simulate any other computer with some bounded slowdown in performance (the actual important thing about such computers is that they can simulate better computers).
So, while the brain seems to have a universal computer (since it can design and run universal computers), it’s not obvious that a universal computer can simulate a brain without infinite slowdown. Some evidence against brains being equivalent to Universal Turing Machines is that some brains can perceive real numbers. Thus, it’s conceivable that even if the mind (the thing that is realized by a brain) is a partially ordered set of states, it’s possible that the states themselves are not computable.
Now, I am not claiming that we cannot eventually build a brain, just suggesting that maybe the only thing that can simulate a brain is another brain.
(2) A universal computer is a computer that can simulate any other computer with some bounded slowdown in performance (the actual important thing about such computers is that they can simulate better computers).
So, while the brain seems to have a universal computer (since it can design and run universal computers), it’s not obvious that a universal computer can simulate a brain without infinite slowdown. Some evidence against brains being equivalent to Universal Turing Machines is that some brains can perceive real numbers. Thus, it’s conceivable that even if the mind (the thing that is realized by a brain) is a partially ordered set of states, it’s possible that the states themselves are not computable.
Now, I am not claiming that we cannot eventually build a brain, just suggesting that maybe the only thing that can simulate a brain is another brain.
It's totally a computer! Not like how 99% of the world uses the word "computer" but it computes things and is vaguely like a FPGA so it's a computer! Not serial but parallel! Like computers!@ But not parallel like the computer you have. Like a computer that doesn't actually exist. But it's a computer!
An interesting opposing view http://www.technologyreview.com/view/511421/the-brain-is-not...
The only way I can explain the (almost entirely american) backlash at the idea of the human brain being a computer that we can emulate is that a lot of them are religious. That is sad.
In academic circles most of it comes from philosophers of mind, e.g. https://en.wikipedia.org/wiki/Hard_problem_of_consciousness
Who in their right mind would go to philosophers to get an understanding on how the human brain works at a physical level? Why not go to your priest instead? Same level of understanding.
I think that's somewhat unfair to philosophers. Besides the fact that science grew out of philosophy, even today philosophers are very good at defining problems and finding logical inconsistencies. As a scientist, that seems very useful indeed. To understand the brain on a "physical level", we have to know what questions we're asking first.
My experience is that philosophy of mind has almost nothing to offer to modern neuroscience. The questions being asked are the unhelpful ones and signify a general obsession with semantics, subjectivity and language tricks.
Perhaps less: Priests may have more direct experience with a variety of minds :p
Do you know what philosophy is? Do you know what science is?
The GP was not a high-quality comment, but please don't make things personal.
You only think that I'm making things personal because you think those questions, "what is philosophy?", "what is science?" are basic questions that it would be an embarrassment not to know the answers to.
That's sort of true, but misses my point. I'll try to be clearer. Such questions are commonly used as rhetorical weapons, so if you don't mean them that way, it's incumbent on you to make the distinction.
In this case that might mean (a) providing enough information to explain why escalating the question is necessary to the discussion, as opposed to a closet insult, and (b) using impersonal language. For example, you already changed your wording from "do you know what science is" to "what is science". That's a big difference.
In this case that might mean (a) providing enough information to explain why escalating the question is necessary to the discussion, as opposed to a closet insult, and (b) using impersonal language. For example, you already changed your wording from "do you know what science is" to "what is science". That's a big difference.
OK, I appreciate your feedback.
Hmmm, They don't cover an important fact: Our intestinal microbiome of bugs that live inside our stomach, affecting our moods and behaviour [1].
[1] http://news.nationalgeographic.com/news/2014/11/141114-autis...
[1] http://news.nationalgeographic.com/news/2014/11/141114-autis...
I could think of another 10 things that affect humans moods and behavior that is not mentioned in this article. Your point being?
That its an important part of how our brain is influenced in working, and might have been mentioned in the article to give the reader a better understanding of underlying mechanisms.
My brain might work like a computer (computation et al), but the word computer evokes actual existing computers to a layman -- and my brain doesn't have a von neumann architecture, nor does it run something similar to our software.
A neural network does computation of course, but we wouldn't call it a "computer" in the sense we use the word when dealing with, well, computers.