

Human brain has more switches than all computers on Earth - cwan
http://news.cnet.com/8301-27083_3-20023112-247.html

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mrb
The title and article are not clearly written IMHO. What they mean is that the
brain has more molecular switches than the number of _transistors_ (switches)
of all computers. Some numbers:

    
    
      * 1.25e14 synapses in a brain
      * they discovered each synapse has 1000 molecular switches
      * so 1.25e17 molecular switches in a brain
      * a post-2005 CPU has 1e8 transistors or so (2010 CPUs barely hit 1e9 transistors)
      * I estimate 1e9 computers on earth
      * so 1e17 transistors in all CPUs
      * 1.25e17 > 1e17 so the statement is right

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AngryParsley
While comparing apples and oranges, they neglected to mention the speed of the
"molecular switches." The fastest neurons fire at around 200Hz. Most fire at
around 20Hz. Transistors are around 100,000,000 times faster.

Oh and circuits conduct signals at 0.5c while neurons are lucky to go at
0.000001c (300 meters/sec).

~~~
phlux
True, but our brains absorb massive amounts of information and process it in
parallel whereas it is much more serial for computers.

~~~
AngryParsley
All parallel tasks can be efficiently serialized on a fast CPU but not all
serial tasks can be efficiently parallelized on many slow CPUs.

From <http://lesswrong.com/lw/k5/cached_thoughts/> :

 _Can you imagine having to program using 100Hz CPUs, no matter how many of
them you had? You'd also need a hundred billion processors just to get
anything done in realtime._

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iandanforth
Having read the original paper I can tell you a couple things:

1\. The technique used to visualize synapses is awesome. 2\. This quote about
molecular switches comes out of nowhere. It's related but not really part of
this study.

More importantly though the idea that these are switches and that there are
way more of them than transistors in the world misses two important points.

1\. Are the molecular switches relevant to the computation performed by the
brain?

Only in so much as to build a transistor you need materials with certain
specific properties, and to build a calcium channel you need proteins with
certain specific responses to the environment. Comparing the computational
unit of one to the building blocks of another isn't quite accurate.

2\. Even if they were computationally relevant are they comprable in terms of
key metrics like performance?

Two important things to remember about the brain are that its slow and very
very efficient. Silicon logic on the other hand is very very fast and
inefficient. Even if there were a thousand fold increase in the number of
computational units assigned to the brain the processing speed of a modern
transistor decimates synaptic level computation.

~~~
roel_v
"...about the brain are that its slow and very very efficient. Silicon logic
on the other hand is very very fast and inefficient..."

Can you elaborate? In what way is the brain efficient in a sense that a
transistor isn't?

~~~
pygy_
In the energetic efficiency meaning of the word.

The energy consumption of the brain is around 20W in an adult human.

Compare that to the multi hundred Watt consumption of the meager machine
you're reading this on...

~~~
roel_v
Oh I see. But like the rest of your comment indicated, it's hard to compare
until we understand more of the brain, right? Depending on the speed of the
brain, the 'energy per thought' or 'energy per operation' can go either way
when we have better measurements and understanding of the things brains are
good at and not so good at?

~~~
berntb
I don't think the analogy was pulled out of ... hrm, /dev/random. afaik, the
brain researchers have data for opinions.

E.g. the functions of the first levels of the visual cortex is relatively well
understood -- _both_ from mapping the nerve connections and from copying the
mechanism in computers.

There is a long time evolutionary pressure to conserve energy, all the way
back to the evolution of nerves. (The brain use quite a lot of your total
energy use, unless you're a non-mechanized lumberjack...)

Edit: The visual cortex might work differently than other parts of the brain
(ask a researcher) because of speed demands, which otoh supports the point
about energy efficiency.

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Udo
Low-level neurological concepts like synapses do not translate well into (low-
level) computer terms if you do it by force instead of by reasonable
consideration. A synapse is not a switch. A neuron is neither a simple
weighted node nor is it an 800 MHz signal processing device with gigabytes per
second of throughput. By going arbitrarily deep into the biochemistry, people
could (and probably do) come up with ridiculous numbers. For example, maybe
somebody wants to count and represent all the macromolecules in a neuron that
modulate its function. It's easy to come up with an arbitrarily large number
and land a nice gig on CNet for it.

~~~
arethuza
When I was working on AI research in the late 80s and 90s (on the symbolic
reasoning side of things) I got the distinct impression that Artificial Neural
Networks were really just a nice statistical technique that had a marketing
breakthrough - they really appeared to have very little to do with exploiting
the behaviors found in actual brain cells.

~~~
Udo
Artificial neural networks do work well as a model of behavior of biological
neural nets, up to a point. They are definitely a piece of the puzzle, a
module to duplicate a certain type of information that is represented in
biological brains. When they became suddenly famous in the 80s and 90s, the
mistake was to assume we could build everything, including an artificial mind,
if we just had a large enough neural net. That was essentially the IBM
approach: just throw enough resources at it and it will become intelligent.
Turns out, more is needed for building actual intelligence.

I firmly believe that neural nets and other techniques are still essential
components needed for implementing artificial minds. We now know that
processing power and storage space are alone are not enough, a brain needs
actual software that tells it what to do with information and how to organize
itself. That's essentially how I became very skeptical of the kind of brute
force AI research that is being conducted today. For instance, modeling a
synapse chemically down to the atomic level is nice for basic research, but
it's definitely not the way to implement AI. For this, we need larger
abstractions that are functionally equivalent and translate well into
efficient computer code, and we need to figure out how to make these pieces of
code interact with each other in a meaningful way. My wild guess would be that
today we're not even constrained by computing power or storage needs, we just
lack the correct design.

~~~
arethuza
My own suspicion is that real "general" AI probably will be developed by
reverse engineering the human brain and working backwards to the key processes
and structures that provide general intelligence.

Of course, this is assuming that there isn't something deeply spooky going on
driving human consciousness - which is a possibility I used to regard as
terribly silly but some of the concepts alluded to (in all places) Neal
Stephenson's _Anathem_ have got be wondering about such things again.

~~~
bradley
Thank you for mentioning Stephenson. I haven't read him other than Snow Crash,
and I don't think I finished it.

Googling Anathem brought me to this blog review of it:

[http://neopythonic.blogspot.com/2008/10/thoughts-after-
readi...](http://neopythonic.blogspot.com/2008/10/thoughts-after-reading-neal-
stephensons.html)

which reminded me of this NIH neuro anatomist who studied her own stroke,
including during her multi-year recovery.

Her TED talk:
[http://www.ted.com/talks/jill_bolte_taylor_s_powerful_stroke...](http://www.ted.com/talks/jill_bolte_taylor_s_powerful_stroke_of_insight.html)

YouTube of same: <http://www.youtube.com/watch?v=UyyjU8fzEYU>

She sees the right brain hemisphere as being our "consciousness" wetware
connecting us to others.

Parts of the video are esoteric, but it's fascinating to hear this first-
person account from a brain researcher, especially of the morning of her
stroke when her left hemishphere was damaged by a spontaneous brain
hemorrhage.

Edit: couple of typos

~~~
arethuza
Cool - thanks, that looks pretty interesting.

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charlesju
I think the REAL question we're all wondering is when we will have access to a
super computer with the capacity of the brain IF we follow Moore's Law.

~~~
powrtoch
I don't think this question is well defined enough to be meaningful. In terms
of how quickly it can carry out complex calculations, low end modern laptops
leave your brain in the dust. What few functions the brain can still claim any
advantage on are the result of dedicated wetware and our ability to learn and
thereby specialize software. Computers will get there, but it's not really a
Moore's Law problem.

The title of this article should not be misconstrued to mean that the brain is
a more powerful computation device, only that it is more complicated.

~~~
randallsquared
_I don't think this question is well defined enough to be meaningful._

You can certainly get closer than asserting that, e.g., a hand calculator is
more powerful than a human brain because it can do 7 digit long division
almost instantly.

At some point, we'll have computers powerful enough to run a working
simulation of a human brain. Shortly before that, there will be a point when
computers of that sort are "as powerful as a human brain", though we might not
realize it when that happens if the software lags.

So that's an upper bound on charlesju's question.

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tectonic
Computational Neural Networks are getting further and further from the reality
of their inspirational biological models. It'd be interesting to see some of
this physiology research transition into revised computational models.

~~~
pavs
There's more than one way to skin a cat.

By design Evolution is not perfect, which suggests there are better ways to
create AI. To me it seems that trying to replicate how our human brain works
is a wrong approach.

On the other hand, there is no reason why we cannot replicate human brain
design if we wanted to[1]. Evolution had millions of years and we are just
getting our hands wet.

[1]<http://www.bbc.co.uk/news/technology-11734909>

~~~
_delirium
AI is also not always about building a human out of silicon, but about
building something that is in some specific ways better (albeit much worse in
other ways). For example, we ideally want to understand what it's doing and
why, something we so far understand fairly imperfectly for humans. We also
want to be able to control it fairly directly and reliably--- a society of AIs
that you have to herd like cats and coax into doing what you want isn't quite
what most engineers looking to plug in intelligent modules into their systems
are looking for. We also want it to be very reliable and fast at tasks that
humans do poorly or get bored doing, like scanning huge quantities of data to
find patterns.

At least, that's how it looks from an engineering side. If the end result is
that all you get is a human, well, we already have humans; just hire them
instead. From a philosophical and technical side creating artificial humans
does still remain quite fascinating.

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marze
Take that, Mr. Kurzweil.

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badave
Hehehe, and 83% of brains are only used to watch porn...

