[ExI] A million lines of code

[Ryan Rawson]

Unlike most of the blog writers I actually attended Kurzweil's talk on
Saturday (sadly though it was by videoconference)... He didn't really
say anything new there, and he was just pointing out that if you use
information theoretical analysis of the unique available information
(ie: dna) you can get an estimate of how much _information_ goes to
constructing the brain.  He was NOT saying "1 million lines of code =
adult human", and I don't think anyone there got that sense.  What he
said is with a million lines of code you can have a program that
_builds_ a brain, and then you have to go forth and teach it from that
point.  You know, what we do to develop a neural network in all new
humans.  Oh yes and his argument was we'll see this full reverse
engineering thing come to fruition in 2030 (not 2020).

I used to be a sceptic, and when you are caught up in the daily
struggles of making silicon nanolithography work it can be easy to be
pessimistic. But even so, the data looks good - every time a previous
generation of computing architecture hits it's limit, a new one comes
on the scene. We might as well be talking about the limits of vacuum
tube computing and the upcoming computation disaster/crunch.

And Kurzweil's prediction is based on solid projections of an
exponential growth in computing technology. Exponential trends are
powerful and difficult to spot sometimes.

On Tue, Aug 17, 2010 at 3:15 PM, Keith Henson <hkeithhenson at gmail.com> wrote:
> On Tue, Aug 17, 2010 at 2:12 PM,   Bryan Bishop <kanzure at gmail.com> wrote:
>>
>> ---------- Forwarded message ----------
>> From: Seth Woodworth <seth at isforinsects.com>
>> Date: Tue, Aug 17, 2010 at 11:37 AM
>> Subject: Re: [Body Hacking] Reverse-Engineering of Human Brain Likely
>> by 2030, Expert Predicts
>> To: bodyhacking at lists.caughq.org
>> Cc: Bryan Bishop <kanzure at gmail.com>
>>
>>
>> Um, no?
>>
>>> Here?s how that math works, Kurzweil explains: The design of the brain is in the genome. The human genome has three billion base pairs or six billion bits, which is about 800 million bytes before compression, he says. Eliminating redundancies and applying loss-less compression, that information can be compressed into about 50 million bytes, according to Kurzweil.
>>>
>>> About half of that is the brain, which comes down to 25 million bytes, or a million lines of code.
>>
>> How does the genome explain protein folding?
>>
>> Just because a million lines of code describe the genesis of the
>> brain's biological systems, doesn't mean that we understand the
>> interactions of the subsequent structures.
>
> There is an interesting analogy here.  People do understand
> microprocessors which are up in this class of complexity (it takes a
> million lines of code to describe one).
>
> Sort of.
>
> Anyone can grasp the functional level of how a microprocessor works,
> but as you get deeper into the modules (pipelines circuits for
> example) the understanding fades out for all but a small number of
> experts on that particular section--and they don't understand the next
> section over.  *Nobody* understands a modern microprocessor from the
> highest levels down through the modules to the transistors.
>
> Incidentally, you have no need I can think of to invoke protein
> folding as a problem for specifying brain development.  In fact, you
> probably don't even need to know what they are, diffuseable attractor
> proteins A-Z is probably detail enough.
>
> In any case, modeling the brain is going to be a big enough problem
> that the simulation hardware/software that results may be
> "understandable" only in the same sense that people "understand"
> microprocessors.
>
> Keith Henson
>
> PS apologies to anyone who speaks up and says they understand a modern
> microprocessor from the top level all the way down to the transistor
> level.
>
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