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Our Brains Don't Work Like Computers
Roland Piquepaille writes "We're using computers for so long now that I guess that many of you think that our brains are working like clusters of computers. Like them, we can do several things 'simultaneously' with our 'processors.' But each of these processors, in our brain or in a cluster of computers, is supposed to act sequentially. Not so fast! According to a new study from Cornell University, this is not true, and our mental processing is continuous. By tracking mouse movements of students working with their computers, the researchers found that our learning process was similar to other biological organisms: we're not learning through a series of 0's and 1's. Instead, our brain is cascading through shades of grey."
And it is for this reason that I loathe comparisons of computing power to brain power. "By 2015, we'll have computers as smart as humans." What kind of bullshit comparison is that? They're two completely different processes.
That's what I heard. Even if they don't work like sequential or even parallel digital computers, I'm pretty sure that brains still compute. Mine tries, at least.
Fuck off.
How we know is more important than what we know.
Looks like the submitter forgot something. Lemme see if I can help him out a little:
How will this study affect your next thought? Go here to discuss it further.
There, that feels more complete.
I'll turn into a supernova and burn up everything. Well I'll turn into a black little hole and you'll turn into string.
Each neuron is like a tiny, slow analog DSP, feeding back FM around a base frequency (eg. about 40Hz in the brain's neural tract). The neurons have feedback among themselves locally, and send out some larger feedback in fiber bundles, signalling other clusters along the way. It's like a teeming kazoo symphony, without a conductor.
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make install -not war
Yeah. That was pretty much my reaction. Seriously, I think the submitter has been in front of his computer too much.
...with floating point arithmetic. A "double" can represent a number between 0 and 1 with 15 decimals of precision, way more precise than any biological phenomenon. Computers can think like us, it's just a matter of writing the right floating-point code.
The idea that our brains might work like biological organisms is a real breakthrough.
Next week's research topic: Do farts stink?
It was a joke! When you give me that look it was a joke.
More like:
Our Brains Don't Work, Like Computers
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make install -not war
...is that our brains (like TVs) are inferior analog devices and human brains need to be replaced with new digital versions. :-)
I guess some brains just have more contrast then others...
I've been waiting for a scientist to tell me that I'm capable of thinking in abstract and fuzzy terms for years. Things I can now forget thanks to the brilliant scientist:
1.) The GPS coordinates of each key on my keyboard.
2.) The streaming audio of my name and all of my friends and families name.
3.) The bio-mechanical force sequences for the hundreds of muscles used in picking up a glass every morning.
Beer will no longer render my circuits useless!
Headline: Brains More Like Neural Nets Than Traditional Programs
Who woulda thunk it.
ftp://ftp.sas.com/pub/neural/FAQ.html%23A2
'Most NNs have some sort of "training" rule whereby the weights of connections are adjusted on the basis of data.'
Insert joke about the 1980's (or 60's/50's/40's) calling). Somehow I don't think Norbert Weiner would be the slightest bit surprised.
-Tupshin
Maybe one day I will have an amd cluster in my skull. Until then, I will accept my alcohol-cooled brain.
This signature is part of a balanced post.
I presume the info was a byproduct of a useful study (Cog-Neuro-Psy possibly?). I really hate it when the media picks out the And finally bit of science news stories (a la bread-landing-on-the-buttered-side, etc).
I don't know the key to success, but the key to failure is trying to please everybody. Bill Cosby (1937 - )
Are younger people that dumb nowadays?
I hope not, because if they are, I must finally be old.
The article's summation is far more accurate than Slashdot. In TFA, a researcher says our minds don't work like digital computers.
The Slashdot headline says our minds don't work like computers, end of sentence.
Had TFSH (The Fine Slashdot Headline) been accurate, this would've been a mind-blowing result and in need of some extraordinarily strong evidence to support such an extraordinary claim. The question of whether the human mind--sentience, consciousness, and all that goes with it--is a computable process is one of the most wide-open questions in AI research right now. It's so wide-open that nobody wants to approach it directly; it's seen as too difficult a problem.
But no, that's not what these guys discovered at all. They just discovered the brain doesn't discretize data. Significant result. Impressive. I'd like to see significant evidence. But it's very, very wrong to summarize it as "our brains don't work like computers". That's not what they proved at all.
Just once, I'd like to see a Slashdot editor read an article critically, along with the submitter's blurb, before posting it.
> I thought that part of the difficulty in reproducing a mechanical brain was preciously it's shades of grey.
It's even made of grey matter.
Sheesh, evil *and* a jerk. -- Jade
Birds do not fly like airplanes, they continuously wave their wings - and do not have turbines or propellers.
Sure hope my taxes don't pay for that "research".
Does anyone *really* think that computers and the brain work in the same way ? Or even in a significantly similar fashion ?
Well, by 'processors', I assume you mean neurons. These are activated to perform a firing sequence on output connections dependent on their input connections and current state, heavily modified by chemistry, propogation time (it's an electrical flow through ion channels, not a copper wire), and (for lack of a better word) weights on the output connections. To compare the processing capacity of one of these to a CPU is ludicrous. On the other hand, the 'several' in the quote above is also ludicrous... "Several" does not generally correspond to circa 100 billion...
No-one has a clear idea of how the brain really processes and stored information. We have models (neural networks), and they're piss-poor ones at that...
The brain behaves less like a computer and more like a chaotic system of nodes the more you look at it, and yet there is enormous and significant order within the chaos. The book by Kauffman ("The origins of order", I've recommended it before, although it's very mathematical) posits evolution pushing any organism towards the boundary of order and chaos as the best place to be for survival, and the brain itself is the best example of these ideas that I can think of.
Brain : computer is akin to Warp Drive : Internal combustion engine in that they both perform fundamentally the same job, but one is light years ahead of the other.
Simon.
Physicists get Hadrons!
I still believe in the Church-Turing Thesis... Our brains might not work LIKE computers but they don't do work DIFFERENTLY than them either.
Thank god we have someone like Roland Piquepaille to point out these amazing facts to us!
Yes, that was sarcasam!
"reality has a well-known liberal bias" - Steven Colbert
> Last time I checked 'computer brain' (cpu) cannot do multiple operations at the same time, unless you have dual core/cpus.
Yes it can, many have several ALUs and FPUs, and also more than one stage in their pipelines. The above hasn't been true since sometime in the nineties at the latest.
Analog computers still exist in some places, but you list discrete values. An analog computer works with an essentially continuous range of charges instead of discrete values; and it works continuously in time, instead of in discrete steps. They're very good at integrating, which is the application I used them in.
Are you saying that Roland would have pointed us to a somewhat useless article?!?? Piquepaille wouldn't do such a thing! Oh wait, he has for his last 80 damn stories.
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WHO ATE MY BREAKFAST PANTS?
I believe that the mind is (simply?) a quantum computer, and the article seems to support that idea. The human brain utilizes a sort of general interconnectedness of things to process thoughts as dynamic probabilities of state, with conclusions only being properly arrived at after a certain ammount of calculation has occured, but with all probabilities esiting well before the completion of the thought.
Anyhow, I should probably stop rambling and go outside or something.
Never eat more than you can lift -- Miss Piggy
...the researchers found that our learning process was similar to other biological organisms....
That makes perfect sense, seeing as our brains evolved from other biological organisms.
Check out evolutionary psychology for some information. You'll view the world differently afterwards.
Evolutionary psychology (or EP) proposes that human and primate cognition and behavior could be better understood by examining them in light of human and primate evolutionary history... The idea that organisms are machines that are designed to function in particular environments was argued by William Paley (who, in turn, drew upon the work of many others).
Just because brains aren't binary or synchronously clocked doesn't mean much. One can create analog computers to represent shades of gray or create clockless computers that don't operate in lock-step synchronization. Furthermore, any digital, synchronous computer and simulate both shades of gray (with floating point numbers) and continuous processes (with sufficiently small time slices). Moreover, given the messiness of neuro-electrochemical systems, one can argue that it doesn't take a very precise float or a particularly dense time slicing to simulate neurons.
Some people ascribe the seeming magic of consciousness to some ineffable property of the brain, e.g., quantum mechanical effect. While other insist that its just what happens when you connect enough simple elements in a self-adaptive network.
The question is, are there neural input-output functions that are fundamentally not computable? If not, then a digital computer will, someday, reach human brain power (assuming Moore's law continues).
Two wrongs don't make a right, but three lefts do.
That must be why I've been having so much trouble trying to walk and chew gum at the same time.
Your brain is composed of billions of individual processing units. Each of those processing units may be sort of like a stream processor (like in Cell), in that they take inputs, perform a computation, and then fire out an output (although I don't know if anyone's even determined that conclusively). However, your brain is composed of billions of those linked together in very complex ways.
Suggesting that your brain only works on one item at a time is rather naive. It is most certainly doing many things at a time.
I've come for the woman, and your head.
The book "On Intelligence" by Jeff Hawkins (of Palm fame) and Sandra Blakeslee is all about how the brain works, and why people's approach to AI is not going to come anywhere near emulating the brain...
Figured it was worth mentioning given the subject matter of the thread... I liked it.. good read, if a bit dry at times...
http://www.babysmasher.com
http://www.openingbands.com
I don't think the chunk of meat in my head works using digital logic; but I'd like to think my Mind does a reasonable job of it.
Natural numbers (1,2,3...), true/false, up/down...
It's not unnatural to divide everything in half, heck our bodys are mostly symmetrical; the distiction comes in where the dividing line is.
We can weight our decisions in endless ways, if someone makes a statement, our belief of that statement depends on how many times we have heard it, our trust in the stater, if it meshes with known facts in the current context.
What I wonder is how far can a human mind be pushed in terms of concepts it can grasp and control it has, can a human visualise a 5 dimensional virtual object? control emotional responses, without supressing them? hold multiple contridictary world models? accelerate long-term memory access?
Even if you think of an electronic computer, it's just hordes of electrons rushing down pathways, only reliable because the voltage levels are continually refreshed at each step, a few electrons might wander off the path, but they are replaced at the next junction. Quantum Mob Rule.
I thought that part of the difficulty in reproducing a mechanical brain was preciously it's shades of grey.
What, if anything, do shades of grey have to do with Precious Moments?
We have no clue how the brain actually works. Sure, we know how individual neurons work, but no one can explain how a bunch of neurons creates a mind.
We look around our world and notice that computers are superficially similar to brains (e.g. they can both do math), so we hypothesize that they work similarly.
However, there's very little hard evidence supporting this hypothesis in the first place, so there's no "news" in this story.
Bottom line: The brain is not just a super-powerful computer.
The most rabid believers in American Exceptionalism are the exact same people whose policies are destroying it.
How is this different than a schema? Haven't we known this since the 70's?
Dear Slashdot Editors,
Could we pretty, pretty please have a Roland Piquepaille section, so we can opt-out? I've been good all year, and it's almost my birthday, and I won't ask for anything for Christmas.
-Peter
"In this model, perception and cognition are mathematically described as a continuous trajectory through a high-dimensional mental space; the neural activation patterns flow back and forth to produce nonlinear, self-organized, emergent properties -- like a biological organism."
Fine, let's see the math. Let's see the trajectory calculations. How about those calculating the space? Calculating the number of dimensions the space has, and how fast that number changes over time?
40 years ago brain scientists realized that computer architecture made a good metaphor for how the brain works. (They did NOT assume there was no feedback, contrary to the article). It made a handy and productive way to look at things so they could figure out more about what was really going on.
10 years ago brain scientists realized that they could use the way cool chaos stuff the describe the way the brain works. Believe me, I know; I've been to the Santa Fe Institute twice. It worked particularly well for me because I'm essentially a signal analyst -- I HAVE to define a set of variables, estimate how well they work, and decide how many of my arbitrary variables to keep or throw out.
It's still only a metaphor. And unlike the specific specific processes described by cognitive science, the dynamic system stuff remains nebulous. It claims a mathematical legitimacy which it can really claim only in concept because the actual math of the acutal operations are is beyond the abilities of anyone making the claims. The fact that it *can* be described this way is no less trivial than the fact that processes can ge grouped according to the traditional cognitive science concepts.
Trajectories on phase space are soooooooo sexy. But if it's any good, it'll result in something more concrete than more people picking up this flag and waving it while shouting the new slogans and buzzwords. Until that happens I peg this with the study that "calculated" the "fractal dimension" of the cortex just because it has fold and folds in the folds.... so fsking what.
"I may be synthetic, but I'm not stupid." -- Bishop 341-B
Modern processors do in fact, do this. They maintain statistics on the branches and go forward on the branch deemed most likely to be taken. Its based on a simple principal - if you've taken the same branch a few times before, you're likely to keep taking it from now on. Think of how loops work.
Granted, if the processor is wrong, it has to clear the pipeline and start anew (which is costly), but the benefits outweigh the negatives.
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The path planner goes slower and generates paths that are initially ambiguous when faced with multiple alternatives. That's no surprise. I'm working on the steering control program for our DARPA Grand Challenge vehicle, and it does that, too. Doesn't mean it's not "digital".
You mean lime breathing, blinking, pumping blood, and typing? I just did all of those things simultaneously.
"Thus you cannot say human brain does parallelistic operations at the same time"
Unless of course you want to be factually accurate.
Essentially what I got out of this article is that our thought process is much like google's auto-search that will guess the word you want to search for as you;re typing itm but wont know for sure until the entire word is finished.
Hm, duh?
In all seriousness though, I wonder how the curvature of the mouse shows gravitation to one side versus the other, maybe they're just a quake2 player and enjoy cirlce-strafing.
I'd have put this in the "water still wet" department. People have known for decades that the brain used continuous, or analog computing.
Analog computers can be built cheap now using mass produced Op Amps. For the readout you can use a Vellman Oscilloscope which goes for about $150 US.
Yup, the "and finallys" get a little old after a while.
:)
I hope no one was using this research to acquire a PHD or MS. The "brains are not computers" epiphany has been realized about billion times already. And this research could stand to be much deeper.
I'm a little bummed about the shallow linguistics analysis. It's interesting and all, but I wish they would have really jumped into something such as pattern recognition.
I'm and interactive designer, and I tend to believe that language and interaction is based upon pattern recognition. Our brains receive data, and compare them to flexible patterns in order to make decisions. This study certainly supports that theory.
In this case, if you show a candle and a dog to a user, and tell the user to click on the candle, the user will jump directly the candle since a dog does not fit the pattern of a candle at all...both visually and verbally. However, if you present someone with a picture of a candy stick and a candle, they will hesitate upon selecting the candle since they bare verbal and visual similarities. More processing time is needed to compare intricacies.
People probably slow down and curve their mouse movement since they are still comparing patterns while they are selecting. By curving the track path, users increase tracking distance and cognitive processing time. It also allots them a circular motion which can easily translate into a last minute decision change. When people are unsure of things, they usually prepare themselves for backing out.
damn I'm a geek
"Things are more moderner than before- bigger, and yet smaller- it's computers-- San Dimas High School football RULES!"
There's a saying by neurophysiologists: "If the brain were simple enough to be understood, it would be too simple to understand itself"
"Gentlemen, you can't fight in here! This is the War Room!" -- Dr. Strangelove
While the methodology is new, the observation is anything but. Details of how neurons conduct impulses (and the way they self-attenuate, adjust modulation and amplitude, etc.) has been understood for decades. There are no revelations here. In fact, computational neural-nets were a graph theoretical application of communication theory (very) loosely based on those observations -- hence the name. A neural network is a primitive model of a single neuron.
By 2015, we'll have computers sufficiently powerful to simulate a full working model of a human brain...
of course, it will be as large as a four storey building, take all the power of Niagara falls to run it, and all of the water of Niagara falls to cool it.
"I'm not impatient. I just hate waiting." - My Dad
Yeah, they are totaly diffrent. For example a computer would probably never try to base philosophical arguments on a slashdot blurb.
Seriously, computers can work with things more complex then 'ones and zeros'. They can be programed to deal with shades of grey as easily (well, maybe not 'easily' but it definetly can be done)
The fundemental part of the human brain is the neuron, and it's either firing or not. 1 or 0 just like a computer. What triggers it is a bit more complicated, but the process can be emulated by a computer, and eventualy comptuers will be fast enough to do just that.
autopr0n is like, down and stuff.
didn't claim that he did. All I claimed was that Goedels theorem "... shows [read: 'it is reasonable to conclude'] that there are some types of mathematical proofs that a human mathematician can demonstrate to be true, but a turing machine ( read: any current technology computer ) cannot."
Umm... when you say "theorem A shows B" it means that theorem A proves B. Not that it's "reasonable to conclude". It is "reasonable to conclude" just about anything from just about anything - because "reasonable" is a subjective term.
It is also true that there is no instantaneous jump from 0v to firing voltage. A different types of neurons require more or less neurotransmitters to reach the threshold voltage.
Well, there is no instantaneous jump in digital comptuers either, however once theshold voltage is reached in a neuron it fires very quickly and very sharply.
In any event, the voltages inside a neuron are quantized, always an even multiple of the charge on an electron, which obviously can be stored in a computer program, as could the finite number of molicules of neurotransmiter around them.
autopr0n is like, down and stuff.
First of all, I happen to be doing computational modelling of psycholinguistic processes, and I know (some of) Spivey's work.
The claims that are made in the article do not contradict the idea of continuous attraction, but they do not prove it either. There is a much simpler explanatation, which is hinted at near the end of the article: one or more processes that try to solve the problem using competition. As a matter of fact, this study simply provides a little bit more evidence of what has been en vogue for a long time.
This behaviour *can* be mimicked quite easily using digital computers, and is definitely not shown by all biological processes.
So, our minds don't work like digital computers in the sense that they cannot store and delete information in the same way. That's been known for a long time, and this experiment doesn't prove it.
Some of the basic cognitive processes can be modelled on a computer, though, but that's not surprising either, since computers are supposed to be able to compute "everything computable" and there is still no reason to assume that the workings of our brain cannot be approached by a computational model.
So, nothing to see, only of interest to psycholinguistic experts. Move on, please.
Now, the output cannot be any more stable than the input, so if you have a fluctuating input, you will have a fluctuating output. However, I'll assume that the input is stable to some high level of precision. (This requires a screened input and a screened device, but those are doable.)
So we now focus on the device itself. Resistance varies with the exact composition of the material, the exact temperature of the material and the exact thickness of the material.
Problem #1 - it is very hard to make a resistor that is of absolutely 100% perfect even consistancy. So if you move the dial N% of the total length, you expect to get a resistance of (total resistance)*100/N. In practice, this will merely be the average value, there will be some variance. That variance dictates the absolute upper limit of how finely you can tune the dial, because at some point the level of uncertainty will become comparable to the level of adjustment.
The second problem is heat. All resistors generate heat, but heat increases resistance. Thus, all resistors will fluctuate in value. Remeber, though, that the composition is not 100% even, so the temperature cannot be 100% even either. This means that the fluctuation in resistance will be dependent on where you are on the dial, increasing the uncertainty.
The third problem is the thickness. Resistance increases as the diameter of a wire decreases. Variable resistors involve two conductors in contact with each other, thus scraping. Unless the dial is 100% circular, you MUST go over the midsection of the potentiometer more than one or both ends. This means that even if you DO somehow achieve a perfect variable resistor at the start, you won't have one after you start using it. You will vary the thickness across the length, and therefore vary the resistance of any segment.
Normally, these variations are too small to notice, which is why these components are useful in the first place. BUT, as you increase the precision, you increase the importance of these variations. Eventually, the variations will swamp the signal. At that point, tuning the dial with even greater precision will be worse than useless, as the value is utterly non-deterministic.
In reality, power fluctuations are of vital importance and are a big reason ADCs and DACs have not exceeded 26 bits of precision. Nobody has figured out how to get a power source stable enough, or a chip screened enough, to transform signals of one form to the other with greater precision than that.
If the cleanest signals we can get from an analog system are 26 bits wide, then producing a simulation of an analog system that is 64 bits wide will be vastly superior to any actual system we know how to build.
Now, it is entirely possible that the brain has developed a level of precision and signal clenliness that exceeds 26 bits. I'm not disputing that. I am disputing that any physical system you can build can exceed 64 bits and it probably can't get even close to that. So, a 64 bit simulation of analog signals should be as good as the real thing.
But what of waveforms? Can you reproduce waves, using discrete multi-state logic? Sure. It's called a transform. The three best-known transforms are Z transforms, Laplace Transforms and Fourier Transforms. Using these, you can do a surprising amount. Transforms work by turning a domain you can't use into a different domain that you CAN use. They're very useful devices.
Fourier Synthesis (the theory that any wave, of any complexity, can be reproduced with a sufficient number of overlapping sine waves) makes this clearer. We can represent a classic sine wave by denoting amplitude, start point and end point. We just need to be able to build a set of any number of these, and we
It's a small world and it smells funny; I'd buy another if it wasn't for the money; Take back what I paid (SoM)
What cracks me up is the nerd infatuation with, basically, "only the trivia _I_ know are the essential things. And you're an idiot if you don't know them, no matter how utterly useless or irrelevant they are to _your_ job or interests."
No, sorry. The world doesn't revolve around you or your hobbies. There _are_ plenty of jobs for which the computer isn't the important part. It's not what makes them money.
E.g, for a lawyer it's a better investment of their time to study the laws and precendents, than to learn networking protocols. E.g., when you need surgery, better hope that that surgeon spent their time becoming a better surgeon, instead of becoming a networking expert. Etc.
For most jobs the computer isn't even as necessary as you'd think. It's at best "nice to have", but not justifying investing months into learning IT and networking protocols.
E.g., it's nice for a lawyer or doctor to have the client files on a computer instead of looking through a filing cabinet. But it's not as essential as you'd think. If you expect him/her to spend months becoming a computer expert, for something that saves him/her _maybe_ an hour per week, you need to put down the crack pipe. Then the computer would actually waste their time instead of saving them anything.
Here's another idea for you: You are there and are getting those calls not from "idiots" but from basically victims of a scam. All the "computers are easy", "wireless networking is easy" or "connecting through our ISP is so easy that grandma could do it" ads are actually marketting scams.
Computers are nowhere near that easy yet, or not without investing some signifficant time. But if your employer actually told those people "sorry, folks, it's only for IT gurus. Spend some time becoming an IT pro and growing a goatee, and then it'll be for you", then they'd lose business. Then, see above, you'd be surprised for how many people the computer isn't _that_ important.
So your employer, and a bunch of others, lied to those people to get their money. There's a name for that. It's called "fraud".
And now those people merely expect your employer to live up to those fake claims. They were explicitly told that they'll just plug it in and be online, so it's _not_ unreasonable for them to actually expect it to work like that.
Because thet's how any other industry works. If a car manufacturer told you "this model reaches 60mph in 8.9 seconds", you'd damn well expect it to live to those expectations. You'd expect that after 8.9 seconds, that car damn better be at 60mph.
Same here. If your employer told them "just pop in this CD and you'll be online in less than 1 minute", they expect that after 1 minute they damn better be online and surfing.
That's why you get those calls. Because those people expect your employer to live up to some very explicit claims.
A polar bear is a cartesian bear after a coordinate transform.
You know, we're all nerds, and we're all arrogant.
But what cracks me up is that the most arrogant assholes are the ones with the least skill or achievement. When you see someone harping the most about how he's uber-L33T because he knows what an IP address is, and how everyone else is an idiot... chances are it's someone who actually knows the _least_ about those. Chances are it's not a programmer who actually writes socket code, it's not a hardware engineer who's designed a network card, etc. No siree, it's a script-reader from the hell-desk that does the "I'm so l33t and everyone else is an idiot" fuss.
So you want to call people idiots if they don't know some computer trivia you know (off a list of canned answers)? Well, then being an EE and having some 20+ years of programming experience, I'll call _you_ an idiot, because you're below _my_ skill level.
Sure, you know what an IP or port number is or how to find it out in Windows. (Or can find it out on your list of canned answers.) But can you actually _use_ a socket on that port? Can you for example write a game server that listens on that port? If I gave you an old network card, can you find the right Linux kernel driver and change it to make it work with that card? Or what?
Or, ok, you do know what an IP address is. Congrats. Do you also know what a B-Tree is, how it works, and how to implement one in your code? Do you also know the difference between, say, MergeSort and QuickSort, and the influence of external (e.g., DB file on a disk) vs internal (in RAM) sorting on their performance? Can you implement either purely as, say, a state-machine driven by exceptions to signal state changes, just to prove that you actually understand the algorithm, as opposed to copying someone else's code off the net? Do you know the difference between bitmap indexes and b-tree indexes in Oracle, and can discuss when you might need one instead of the other?
Hey, it's computer stuff too. Very basic stuff too, nothing esoteric. We established already that computer stuff matters, and you're an idiot if there's something you don't know about them.
A polar bear is a cartesian bear after a coordinate transform.
NO! The brain is NOT a Turing Machine.
There is something called the 'Halting problem'. Basically, for any computation, a Turing Machine can:
-halt with success
-halt with failure
-get caught in a loop
The question is, if it hasn't halted yet, will it halt in the future or will it get caught in a loop? And you can prove that it is impossible to construct a Turing Machine that is able to answer that question. This is called the halting problem.
It can be generalised to prove that you cannot construct a single Turing Machine to decide whether a given statement is true or false and this is where it ties back into Gödel's theorem and it is this argument that some people use to relate Gödel's incompleteness theorem to the brain (which I find intriguing but I'm not sure whether I agree with it.) The important point here, however, is that you, as a human being, can solve the Halting Problem. It follows, that you are NOT a Turing Machine.
It can also be proven that Quantum Computers are not Turing Machines by the way, but even Quantum Computers are unable to solve the Halting Problem, so our brain is a step up even from Quantum Computers.
Let me repeat the point here again: The brain is NOT a Turing Machine and as such the limitations of a Turing Machine do not apply.
Takes it at least 10 minutes to boot up in the morning.
Single? Canadian? We can help. Visit http://www.l
It can be shown however, that humans can solve it in certain cases, which is still more than Turing Machines can do.
No, it's not. I can easily write a program that solves the halting problem for certain special cases, for instance for turing machines without "loops".
Be wary of any facts that confirm your opinion.
For centuries, people have compared the human brain with the most advanced technology of the era : clocks in the 17th century, automatons in the 18th, Jacquard weaving machines or steam engines during the 19th, automated telephone exchanges in the 1920's, and digital computers from the 1950's on. Now it's (neural) networks, quantum computers or fuzzy logic, but the idea is the same.
Google passes Turing test : see my journal
Some examples of people who continue to argue for sequential processing and/or discrete representation and/or modular cognitive architectures are Jerry Fodor, Zenon Pylyshyn, and Eric Dietrich (Philosophy of Mind), John Anderson and Art Markman (Cognitive Psychology), Doug Lenat (Artificial Intelligence), Steven Pinker and Elizabeth Spelke (Developmental Psychology), Leda Cosmides and Nancy Kanwisher (Cognitive Neuroscience)... the list goes on.
One of God's properties is that He or It or Whatever is omnipotent, no? The _supreme_ being? Why would a supreme being need to obey logic? Your riddle supposes that logic is the supreme entity or force in the universe. I would expect a omnipotent, supreme-being type God to be able to do non-sensical, as well as sensical things.
Computers are useless. They can only give you answers.
-- Pablo Picasso