
The Brain is Not Computable - petermlm
http://www.technologyreview.com/view/511421/the-brain-is-not-computable/
======
rm999
>But Nicolelis is in a camp that thinks that human consciousness (and if you
believe in it, the soul) simply can’t be replicated in silicon. That’s because
its most important features are the result of unpredictable, non-linear
interactions amongst billions of cells, Nicolelis says.

This is a fringe opinion, and I really wish the title reflected that. Ignoring
the absurd 'linear' part of the article, I don't believe predictability is
important to the brain. While it's possible quantum effects could explain
unpredictability in the physical universe, there is no scientific evidence
this is relevant to the brain; the brain operates at a much higher, more macro
level than quantum mechanics. Besides, randomness can be introduced into
silicon if it's that important. I hope the article is misrepresenting his
opinion, but they seem dangerously close to 'the brain is more complex than I
can comprehend, so it must be magic'.

I and many cognitive and neuroscientists I've spoken to consider this whole
line of reasoning to be anti-scientific philosophy (although I may be biased
because I studied AI, which rests on the idea that silicon can recreate
intelligence).

~~~
bascule
According to Max Tegmark's calculations, the importance of quantum mechanical
effects on brain processes is negligible:

<http://arxiv.org/abs/quant-ph/9907009>

This paper posits the brain can be modeled as a classical (e.g. Newtonian,
"billiard ball"-style) physical system

~~~
api
This is based on the idea that the sum total of what the brain does can be
explained by and represented by neural network type models.

The conventional neural network model neglects the interior of the neuron.
Gene regulatory networks for complex eukaryotes are on the order of neural
networks in complexity and involve quantum-scale interactions, which opens the
possibility of quantum effects being significant. Gene regulation within the
neuron affects neural firing behavior and, more importantly, profoundly
affects neural growth patterns and thus learning and longer term forms of
cognition.

This also neglects the possibility (now considered probable) that more cell
types than just neurons are involved in brain activity:

<http://en.wikipedia.org/wiki/Gliotransmitter>

In short: the brain is not a neural network. Rather, those mathematical
connectionist models are just that: _models_ of _aspects_ of the brain. We do
not yet know to what extent these other mechanisms play a role, and what their
role is. Given their nature it seems in both cases that their role might be
more long-term, affecting long duration learning, planning, etc.

It really seems to me as if the most ardent and enthusiastic adherents of the
Kurzweilian vision are computer scientists who don't really respect the domain
of biology and like to hand-wave away its complexity as "background noise."
You can't do that. I say this as a lifelong computer programmer who has
studied biology. Studying biology really blew away any notions I had of
simple, classical computer programs becoming movie-style AI.

The author is _not_ making an anti-scientific "magic" argument. He is simply
pointing out that biological systems are analog, embodied, electrochemical
(and thus physical and possibly quantum), nonlinear complex systems, and he is
being skeptical about the idea that such a system is going to yield readily to
digital computer simulation. I agree with his skepticism.

Prediction: brain simulations will simulate superficial brain behavior but
they will not become sentient. More specific prediction: they will get stuck
in closed cycle loops. They will not exhibit the higher order motivation,
creativity, or learning behavior seen in brains, which is probably because
these behaviors emerge from all the real embodied biophysical stuff the CS
people are ignoring.

~~~
bascule
This paper specifically addresses microtubules and is definitely not
neglecting the interior of neurons. I suggest you read the paper instead of
just the abstract before you give feedback.

~~~
api
Microtubules, maybe, but that's only one of a billion things going on in
there.

Here's a pretty decent article:

<http://www.nature.com/news/2011/110615/pdf/474272a.pdf>

My point is that a neuron is not an equation in a connection model. It's a
cell. You can't hand-wave away its identity as such or all the things that
happen in cells.

Even if nothing quantum is involved (and I didn't say it was... we don't
know), including significant aspects of intra-cellular activity and including
other cell types (glia, etc.) and other types of interactions adds
exponentially to the classical computation requirements.

I didn't mean that I _dismissed_ the idea of classical computers simulating
the brain or the implications. I just meant that I'm skeptical. Even if it is
possible I'm very skeptical of it happening soon due to the absolutely insane
computational requirements. My intuition is that it would require a leap on
the order of vacuum tube ENIAC -> Intel Core i7. Meanwhile consumer demand for
faster and faster chips is giving way to demand for slower but more energy
efficient chips for mobile devices, which is subtracting from the economic
incentive to continue Moore's Law. (AMD just bowed out of the x86 race for
instance, leaving us with an Intel monopoly at the high end. Monopolies get
lazy and stagnate.)

Personally I'm much more optimistic about "wet" transhumanism-- life
extension, augmentation, brain hacking, etc., than I am about "real" AI in the
near term or mind uploading. I also see computers stagnating a little for a
while the way aerospace did from the Apollo era until about now... entirely
for economic rather than physical reasons.

~~~
bascule
A cell is a physical system. A physical system can either:

1) Be sufficiently large that quantum effects are irrelevant, like a billiard
ball, and thus it can be modeled deterministically inside of a computer. The
Tegmark paper proposes this is how the brain works.

2) Rely on quantum mechanical effects (which are non-deterministic, but can
still be simulated inside a computer if you trust a computer's opinion of
"random"). Penrose, Searle, etc. would argue otherwise, that there's a method
to the madness, and that there's something "special" about the quantum
mechanical effect on microtubules. We still don't understand quantum mechanics
very well, so if human consciousness really relies on quantum mechanics, there
is arguably a bit of wiggle room here, especially if you're a physicist of the
same caliber as Penrose.

Microtubules are specifically of interest because they're one of the few brain
structures small enough to arguably be subject to quantum mechanical events.

Tegmark argues that they're not small enough and that it's irrelevant.

The real question is:

Is it _possible_ to simulate a brain within a computer?

\- not -

Is it really hard? Is it too hard for modern technology? Is this problem
simply too complex for us to understand? Do we lack the technology to build
sufficient understanding today? Etc. Etc.

This article is claiming it's IMPOSSIBLE to simulate a brain within a
computer. Proving that is a tall order.

~~~
lutusp
> Be sufficiently large that quantum effects are irrelevant ...

This misunderstands the role of quantum theory in macroscopic systems. There
is never a scale so large that quantum effects can be safely ignored. All that
happens is that the specific effects, and probabilities, change.

The Heisenberg Uncertainly principle doesn't build a wall between the
microscopic and macroscopic realms, it makes a probabilistic prediction about
quantum events at all scales -- larger scale, lower probability.

But a macroscopic system that has a very low probability of exhibiting classic
quantum behaviors as a whole, will nevertheless show quantum behaviors at some
level. An easily understood example is a radioactive sample -- let's say a
kilogram of uranium. The sample isn't going to behave like Schrodinger's cat,
but its constituent atoms certainly will.

In one sense, the uranium is a classical mass with no contribution from
quantum theory. In another sense, it's highly influenced by quantum theory --
were this not so, there would be no nuclear disintegrations.

An observer can examine the sample and, intent on demonstrating that it's a
classical system, use the half-life equation to predict its future --

a' = a 2^-t/f

a = activity level at time zero

a' = activity level at time t

t = time, consistent units

f = half-life factor

\-- And the outcome looks very classical, but only because the sample is
large. But the timing of the next disintegration is quantum-deterministic. So
the uranium is a chimera -- part classical, part quantum. This is an example
that makes the point very clearly, but all classical systems (and scales)
possess quantum properties, usually not so obvious as it is with a radioactive
sample.

> Rely on quantum mechanical effects (which are non-deterministic, but can
> still be simulated inside a computer if you trust a computer's opinion of
> "random").

Quantum effects aren't merely random. What connects an event to quantum theory
isn't its randomness, but the nature of the randomness -- its genesis. No
matter how carefully I design a random number generator, I won't be able to
imitate quantum entanglement unless the system is actually capable of this
specific physical behavior.

------
Xcelerate
I'm going to take the unpopular stance and say that it's very hard to make a
prediction like this. Anyone who has a very strong stance one way or another
probably needs to reevaluate their predictive capabilities.

I do work in molecular dynamics. To even simulate a million atoms requires
huge approximations. You can get more accurate as you simulate less. If you
want an almost perfect match with reality, simulation will get you about 2-3
helium atoms. Now consider how many atoms are in a human brain.

So it's hard for me to imagine fully simulating a human brain, although I
don't see why it is theoretically impossible. Brains behave according to the
same laws of physics as everything else in the universe.

On our _current_ technological improvement path, I don't see a brain
simulation occurring any time soon. If quantum computers were developed, it
would make things much easier, but we would still need a new "kind" of
technology. I wouldn't rule it out completely though. Who in the 1600s would
have predicted microprocessors?

As for his talk about souls or consciousness, that just confuses me (and I'm
religious too). Everything that we have thus far discovered obeys the laws of
physics, so ruling out a simulation via some mystical "property" that human
brains have seems sketchy to me.

Now, if you want to talk about things that really aren't computable, I'll
direct you to Chaitin's constant:
<http://en.wikipedia.org/wiki/Chaitins_constant>

~~~
muglug
As I understand it, currents attempts to simulate brain activity operate on a
slightly higher scale, mimicking the behaviour of neurons and the electronic
signals between them, without resorting to modelling the behaviour of
individual atoms.

~~~
Xcelerate
Yeah... what I've found from my work is that higher-order modeling tends to
leave out important effects. Which is okay when you're specifically trying to
understand one particular property of a system (diffusivity, charge
distribution, etc.), but when you want ALL properties to be accurate? That's
difficult.

Edit: I'll elaborate a little bit more. We currently simulate large proteins
using force fields like CHARMM or AMBER. The problem we're trying to solve is
what structure these proteins will fold into, and these force-fields work
pretty well for that.

But consider this: these potentials are basically a handful of equations that
describe stretching, bending, torsional, van der Waals, and electrostatic
interactions. The parameters for these equations come from measurements of
simple compounds that have similar structure, and these are used to
extrapolate what will happen in a different substance. Good enough for
folding, but if you want accurate energy levels? No way.

------
guylhem
Not with our current technology, I agree

But saying the problem can't be solved ever seems dead wrong to me.

We humans excel at understanding and replicating what nature did - then at
improving it.

Once we clearly understand how memories are stored, if they can be read _and
written_ that'll be half of the problem : accessing the data.

If the theory about memory being encoded in the microtubules is right, imagine
some nanomachines that could read it from a "live" human - by broadcasting
radio waves, or emitting photons (we started doing that for proteins with
antibodies glued to radioactive markets, then we improved and glued them
luciferase, now we do multiple colors and IIRC it's being experimented for
DNA), whatever.

Now imagine other nanomachines that could rearrange the microtubules to match
that - voila, you've got Matrix-style "uploading" of knowledge once we
understand how the memory bits interact with eachother, how they can be
accessed by the subject. Maybe it's like a SQL database fk/pk - we don't know.
But something must exist to allow it. When we figure it out, there is no
reason why it couldn't be done too.

My own predictions : after we confirm how memories are stored, if we have
nanotechnologies to create nanomachines, we will start reading memories just
like we did with DNA and proteins.

It will take a while, we will only have a read-only access at first- and with
many bugs just like how introns and TATA boxes could be mysterious initially -
but we will understand in the end, and that will be half of the problem
solved.

Downloading will require additional advances in computer technology (at least
faster cpus, in 3d instead of 2d to get more interconnections and raw
computing power, and maybe some integration of processing and memory to match
how neurons work), but it does not seem far-fetched to me.

~~~
kybernetikos
Computability in this case is a theoretical term and doesn't really relate to
levels of technology.

Whether or not all physical processes are computable in the sense that they
can be simulated by a turing machine is an open question, although my
impression is that most folk who care to express an opinion think that they
can. There's a little bit more on the Wikipedia article on the Church-Turing-
Deutsch principle.
[http://en.wikipedia.org/wiki/Church%E2%80%93Turing%E2%80%93D...](http://en.wikipedia.org/wiki/Church%E2%80%93Turing%E2%80%93Deutsch_principle)

~~~
guylhem
Regarding computability, I wouldn't dare giving any opinion on that, and
hopefully didn't in my original post. All I'm saying that once we figure how
information is stored and processed, with enough technology we could replicate
the process. It's not about computability- if you are making a biological
duplicate I'd expect it to work the same way. Some might say this is not the
"singularity", but it walks like a duck, quacks like a duck...

Also, it would help creating silicon equivalent. Imagine we have something
just as small (or smaller) than a biological neuron, which can interface and
work in the very same way.

Computability or not, if it works in exactly the same way, I'd guess it could
work the same on a higher level too - like, in a brain, especially if we have
figured how to extract the stored information and if we can feed it back.
(unless there are emergent properties we missed in the first place, but then
if they can be identified, maybe they can be replicated too?)

That would allow an iterative trial/error (ex: if it doesn't work - why?)
which might not resolve the computability question, but bring even more
interesting issues about why it might not possible - something we can learn
only from an experimental approach.

~~~
kybernetikos
As far as I can tell, there's a hidden (but not unreasonable) assumption in
what you're saying; that it is _possible_ to simulate what is going on. There
are many things that cannot be computed, e.g. the Busy Beaver sequence, and
it's quite possible that a simulation of true physics also involves
noncomputable problems which would mean that it's not possible for a turing
machine to simulate it.

I like this blog's [http://michaelnielsen.org/blog/interesting-problems-the-
chur...](http://michaelnielsen.org/blog/interesting-problems-the-church-
turing-deutsch-principle/) take on it:

"Yet our ease with the CTD Principle is an ease brought by familiarity. One
hundred years ago the statement would have been far more surprising, and, I
suggest, even shocking to many people.

Viewed from the right angle, the CTD Principle still is shocking. All we have
to do is look at it anew. How odd that there is a single physical system –
albeit, an idealized system, with unbounded memory – which can be used to
simulate any other system in the Universe!"

You say "once we figure how information is stored and processed", but how do
you know that what is going on in the brain is just a matter of storing and
processing information in a way that can be mimicked by a turing machine?

------
mistercow
>That’s because its most important features are the result of unpredictable,
non-linear interactions amongst billions of cells, Nicolelis says.

Replace "cells" with "molecules" and "consciousness" with "fluid dynamics",
and you can see what a vague, hand-waving argument this is.

>“You can’t predict whether the stock market will go up or down because you
can’t compute it,” he says. “You could have all the computer chips ever in the
world and you won’t create a consciousness.”

You can't predict the precise behavior of an analog amplifier, either, but you
can still model it and produce a digital equivalent.

~~~
VMG
This quote also stumped me

>“You can’t predict whether the stock market will go up or down because you
can’t compute it,”

If you had an accurate model of the agents, you could easily compute the stock
market.

~~~
defen
But as soon as you want to use that knowledge to actually make money, your
agent is participating in the market, so it has to account for itself...

~~~
VMG
True, but irrelevant in context of the analogy.

------
icegreentea
I don't think the non-linearity argument is too convincing. Certainly, I
accept that you cannot simulate a specific brain/mind - that is, if you
somehow knew the exact structure and inner workings of a specific mind that
you could then run a simulation of that mind which returns the same outputs as
the original mind. I can buy that our simulations of non-linear problems will
not fully match 'reality' and cause divergence.

However, that doesn't mean we cannot run a model. Exactly what the model's
output 'means'... well, that's a different question. To use his examples, our
simulations of weather or the stock market do not produce the same output as
the future. But their outputs (hopefully) represent actually realizable states
of the world.

In other words, as long as our model gives us 'human enough' output, then I
guess it's sufficient? I mean, it really comes down to 'why do you want to
simulate the human brain'. If you want to be able to upload your brain, then
that probably isn't good enough. But I can imagine for various other uses, it
could be enough.

I do think Kurzweil is at best... wildly optimistic though.

------
kristofferR
I simply can't understand why people feel the need to proclaim that something
plausible will never ever happen some time in the (possibly very distant)
future. It's both stupid, unproductive and often embarrassing (when they are
proven wrong).

>"But Nicolelis is in a camp that thinks that human consciousness (and if you
believe in it, the soul) simply can’t be replicated in silicon.

I'm guessing/hoping that the silicon reference was made by the author of the
article and not Miguel Nicolelis, considering that silicon is extremely likely
to be replaced by graphite or something else in the next decade or two, at
least with almost full certainty by the next century. If it actually was
Nicolelis who spoke about silicon, it automatically discredits him from having
anything to say about the distant future of computing.

>That’s because its most important features are the result of unpredictable,
non-linear interactions amongst billions of cells, Nicolelis says."

Even if that was true, which I doubt, so what? There has to be some kind of a
system behind those "unpredictable, non-linear interactions" in order for the
brain to have any functionality at all, and every system can be figured out
and simulated. It might be incredibly complex and take centuries for us to
gain the required knowledge and processing power, but even that doesn't make
it impossible.

~~~
JoeAltmaier
Agreed. The brain was 'invented' by non-intelligent evolution, a blind
drunkard's walk of chemistry and biology. I am amazed we haven't figured out
what mind-bogglingly simple premises are required to build a brain - it
happened through a series of alway-stable always-useful small steps. I've seen
a car designed by a web page through random 'genetic algorithm'. How about a
simple random walk through neuron interconnection until something useful pops
out?

------
mehwoot
I too believe this. Here is my argument:

1) If we have to simulate it at a low level, the human brain is far too
complex for any computer in any timeframe of our current lives to have enough
power to simulate properly

2) Working backwards and simulating the high level processes (AI, etc) have
been a dismal failure at actually replicating human thought processes, and
will continue to be. While NN or the like can theoretically simulate any
algorithm, we have no idea how to effectively train them in a way that
produces high level thought similar to a human brain.

Generally when discussing this with people, I say this: if you disagree, give
me a date by which you think I will be shown wrong, and then we'll reevaluate
at that point.

I fully expect I could be proven wrong, and that would be an awesome world to
live in, but my bold and unfortunate prediction is that I won't be.

~~~
VMG
_> I too believe this._

You don't. The article argues that there is a theoretical barrier that
prevents a brain emulation _in principle_ , you argue that technology isn't
ready _yet_ and won't be in our lifetimes.

Opponents of your viewpoint argue that you simply can't imagine the state of
technology in 50 years.

~~~
mehwoot
The subject is, "The Brain is Not Computable". I too believe that. The article
itself is quite vague in what particular objections the guy has. It doesn't
actually state he thinks it is not computable in theory, just in practice

> That’s because its most important features are the result of unpredictable,
> non-linear interactions amongst billions of cells, Nicolelis says.

If he thought it was theoretically impossible, then the "billions of cells"
would be redundant. It would only take 1 un-computable cell. Without a longer
interview, we can't be sure what exactly he means.

My interpretation was "unpredictable, non-linear" (i.e. not computable by a
simple algorithm, would have to be very complex, because of non linear
interactions between inputs) amongst "billions of cells" = an obscene amount
of computational data. I don't think he means unpredictable to mean strictly
uncomputable.

> Opponents of your viewpoint argue that you simply can't imagine the state of
> technology in 50 years.

Yes, but at the same time there are things we thought we would be able to do
50 years ago that there is no way we can do now. There are physical
constraints to the universe, and we can't just assume "technology" will
overcome all of them. Nobody can imagine the state of technology in 50 years
accurately, but I am still willing (and have done) to take bets on this 50
years into the future.

------
tibbon
My girlfriend is a neuroscientist. Every time she sees something about them
'modeling the brain' she is visibly amused/unhappy. It might be possible, but
our current understanding of the brain feels much further away.

The concept that we're going to hit some moore's law style thing in science
that will propel us to just automatically understand things, which we can
barely measure currently, just doesn't line up. Just the process to understand
how a single thing functions on a single channel seems to take forever now,
and most neuroscience labs aren't limited by the speed of their desktops...

~~~
Aqueous
Right, it takes forever now - and it took twice as long five years ago.

~~~
tibbon
But the thing is most neuroscientists don't just sit at a computer all day.
95% of the tasks they do are not computer-bound.

If you're doing animal-based research (the majority of real neuroscience
currently), then its time spent with behavior testing, surgeries, waiting for
the drug to be in an animal for 72 (or however many) hours, processing slides,
pipetting, etc.

The time spent at a computer is mostly data analysis, reading papers, ordering
supplies and grantwriting. A huge amount of time seems to be spent jumping
through hoops, ordering things, working with vendors of equipment that doesn't
frequently work as advertised, and dealing with broken stuff overall. The
data-analysis they are doing again, isn't bound by the computer's speed. It
generally is working with a few dozen (or hundred) samples of relatively
computationally easy data.

There's not much for a computer to speed up.

------
api
I'm somewhere in between. I think it might be possible to create a machine
that does what the brain does, or even to "upload," though I don't see the
latter anytime in the foreseeable future.

But if so, I don't think it'll be with a standard von Neumann machine. Not
that such a computer _couldn't_ perform the required computations... it's
Turing complete. But I think it would be a very poor fit for the problem
domain. You'd want some kind of radically different incredibly highly parallel
architecture. You also might want it to be analog or analog-like. There's been
some interesting renewed interest in analog computers for a little while, and
in probabilistic processors that can run incredibly fast by discarding the
requirement of perfection.

------
chevreuil
There is one constant in the History showing that a generation of human can
achieve goals that were admitted impossible by their predecessor

Apart from that, there is this thing called ethnobiology, a sub-dicscipline of
anthropology, that studies the way civilizations understand and represent the
living things.

Ethnobiology reveals another constant in History : we tend to compare our
brain to the most complex technology we know.

At the Renaissance, philosopher assimilated the brain to a very complex and
subtle clockwork, Freud compared it to a steam engine, which pressure should
be evacuated to avoid explosion. In the 40's, schoolboy and schoolgirls were
told that brain was like a telephone exchange. Today, computers are the most
advanced technology we know, so we tend to compare our brain to it. But like
our predecessors, it's very likely that we are wrong.

Let just think forward, and admit that we are totally biased by the fact that
computer are now inherent part of our life. Let's admit that there is a chance
that our brain may never be modeled by a computer.

PS: for those who read french, a part of the above is largely inspired by a
talk of Ted CHIANG, available here :
<http://www.actusf.com/spip/article-9802.html> (sorry I can't find an English
version)

------
TeMPOraL
Such opinions happened before, and I guess will keep happening again.

> But the greater lesson lies in the vitalists' reverence for the elan vital,
> their eagerness to pronounce it a mystery beyond all science. Meeting the
> great dragon Unknown, the vitalists did not draw their swords to do battle,
> but bowed their necks in submission. They took pride in their ignorance,
> made biology into a sacred mystery, and thereby became loath to relinquish
> their ignorance when evidence came knocking.

> The Secret of Life was _infinitely_ beyond the reach of science! Not just a
> _little_ beyond, mind you, but infinitely beyond!

[http://lesswrong.com/lw/iu/mysterious_answers_to_mysterious_...](http://lesswrong.com/lw/iu/mysterious_answers_to_mysterious_questions/)

------
coopdog
Surely if you created a physics virtual machine and loaded an image with all
of the atoms and electrons in place.. you'd simulate the brain. I imagine it
would take a lot of computational power, but it's not 'never'

Unless we're talking about souls here or something

~~~
stefantalpalaru
If we really need to simulate interactions at molecular level we're fracked.
That kind of computational power is unimaginable.

~~~
kristofferR
So was Petabytes 60 years ago, yet today there are people who have single-
handedly uploaded more than that on private BitTorrent trackers.

Never say never.

------
aaron695
LOL what total bunk, "unless" of course you practice some sort of magic and
believe by definition humans cannot replicate this form of magic, then his
theory might fit.

Besides which the Singularity has nothing to do with the 'soul' and
consciousness. It's about super intelligence, this is possible without being
self aware. IE Deep Blue I assume is not considered 'conscious' but it can
solve the chess problem better than us, why would you think a super
intelligent machine that can solve general problems has to also be 'self
aware', bizarre.

------
bmh100
Is anyone familiar enough with this argument that they can lay down the
premises? It is not clear what makes him think that the brain and, by
extension, physics are not computable.

------
Vivtek
Oh come on. I'm not going to make a prediction one way or the other, but
there's one thing I do know: simulating the brain and simulating the current
stock market to predict the outcome of a stochastic process (which is
unknowable because you don't even know the inputs) are two vastly different
things. So that's a really weak argument for his position. Not an argument for
it at all, actually.

------
carwithcookies
Has anyone seen a better critique of Kurzweil's "How To Create A Mind?" I'm
reading it now and have been kind of hankering for an analysis to compare my
own issues/questions with.

------
amalag
Assuming the brain is an instrument or computer machine as many seem to be
doing in the comments. Who is the operator of the machine?

------
Aqueous
Of course the brain is computable. The brain is a computer.

~~~
nisa
[citation needed]

~~~
Aqueous
The brain is made up of neurons. The neuron is a device that stores and
processes information. Does it do so using a finite set of logical steps? We
don't quite know yet, but it seems likely, since the behavior of the neuron
has been shown to closely follow a known set of differential equations (the
cable equations - <http://en.wikipedia.org/wiki/Cable_theory>). But using the
broadest definition of a computer, a device that stores and processes
information, the brain is most certainly a computer.

------
JoeAltmaier
tl;dr: guy says the brain is not computable.

I say: Is too! Dialogue complete.

