Re: Guessing?

On Jul 12, 6:03 am, JOG <j...@xxxxxxxxxxxxx> wrote:
On Jul 12, 2:27 am, Marshall <marshall.spi...@xxxxxxxxx> wrote:

I am calling bull*** on the above position, attributed to
Wittgenstein.
I am calling bull*** on the idea that "meaning and knowledge
cannot be encoded in any formal representation."

Then we disagree whole-heartedly. Great guns.

I know! It's like the first time I've ever disagreed with
someone on the Internet! :-)


Either way, knowledge is generally accepted in AI research as
unencodable in a descriptive model. I would love to claim to have
formulated such conclusions myself, but I am merely reiterating
Clancey, Brookes and Cantwell-Smith famous papers, the well documented
demise of expert systems, the $35million wasted on projects like CYC,
etc, etc, etc.

Lately I have developed an allergic reaction to various ideas
asserting that brains are somehow magical and mystical,

This is a straw man. You are attributing mysticism
where it is not claimed.

I am clear that no one is using the term "magic" to describe
how brains work. Nonetheless, I assert that this is what
various claims of the uncomputability of the brain reduce to.

http://xkcd.com/373/


It is merely as statement that meaning comes from how our
senses react to the world, as opposed to your view of the brain as a
turing machine churning up statements of first order logic.

"How our senses react to the world" is entirely mechanizable.
I would agree that a computer with no inputs or outputs is
not going to be able to do anything useful, in exactly the
same way that a brain floating in a vat of nutrients also
won't.


and thought is
something that we not only can't currently explain computationally,
but never will be able to explain computationally. It's just bull***.

Yeah, that's right. Human thought is not like a big calculator.
Go figure.

Go "figure" you say? As in, "to compute or calculate?"
(To be said in a Dr. Evil voice.) (OK, that was completely
lame of me, I admit.)


Earlier you mentioned "What Computers Still Can't Do."

Reading for example this:

http://en.wikipedia.org/wiki/What_Computers_Can%27t_Do

I see no argument that doesn't amuse me with its lameness.

I would type more, but I have a pressing engagement. Perhaps
later?

Absolutely. I'm interested in how you have formulated your wishful
1960's style opinions - misguided as they are ;)

That AI researchers of the past were overly optimistic is no
indication, one way or the other, of what is possible mechanically.
We programmers are often excessively optimistic in project
estimates. Guilty! And of course where decades are involved,
the error factor may also be in decades.

I will also acknowledge up front that this question is not
settled, and the only thing that will settle it for sure is
when we have a machine that is obviously as smart as
a human, and as generally capable cognitively. (Alternatively,
a solid refutation of the Church-Turing thesis would prove
it impossible. But that won't happen.) Nonetheless I claim
that the evidence, while not absolute, has already moved
beyond a reasonable doubt as to the outcome. And the
astonishingly poor arguments mustered against the
inevitable, despite the failure of _every_ _single_
previous man-will-never-build argument just piss me
off.

The brain does some amazing things. How might it
accomplish them? By processing information. It has
inputs and outputs. Yes, these are amazingly complex,
but even the physiology of the brain is exactly what
we would expect from a mechanical model. We see
a large bundle of nerves that pass information into
and out of the brain at the base, down the spinal
column. We see that the highest-bandwidth inputs,
vision, have a dedicated, wide channel. We see that
we can map, for example, specific areas of the
primary motor cortex directly to specific motor
activities, and in fact the map itself has the same
physical layout of the thing it is mapping. (The
so-called sensory and motor homunculi.)

Today, we cannot build a robot that has the flexibility,
the suppleness, the self-contained power system,
the self-repairing capabilities of the human body.
And yet no one ever writes a book saying we *never*
will be able to. Why is that? Because it's a stupid
claim; we can trivially see from extrapolation that
such a thing is possible. In fact, we have an obvious
existence proof: the human body. The situation with
the brain is no different. We can't build it today, but
it is simply because we aren't there yet; we will be at
some point in the future. Nothing magically prevents
us from ever getting there. No signs of any invisible
barrier have yet been reported. And again, we have
an obvious existence proof of a mechanical object
that is as cognitively able as a brain, and that is the
brain itself.

What other candidates besides "computation" exist
for describing what the mind does? If it's not
computation, then it's ... ?

What must be necessary for the mind to be non-algorithmic?
The brain must have, at some fairly low level, some
fundamental operation that is non-algorithmic. The idea
requires that the brain has some primitive operation that
is instantiable in a physical object (three pounds of
fatty meat) but that it is impossible to abstract over.
For if we could abstract this primitive, we could
compute with it.

Consider that idea: impossible to abstract over.

THAT is an extraordinary claim. Has there ever been
any process in history that we haven't been able
to abstract?

Or again we have the computational equivalence of
every computational system ever designed (above
a certain low threshold.) Where does that ceiling
come from? It might be credible to suggest that
there are processing primitives we haven't thought
of yet, that might be necessary for consciousness,
IF we saw that the existence of a great diversity of
computational models which had a great diversity
of expressive power. That might indicate we hadn't
covered them all yet. But instead we see exactly the
opposite: *every* computational model, *every* set
of primitives we can design, above a low threshold
of power, is equally expressive. Clearly we well
understand when we have reached a full set of
processing primitives: any Turing-complete system
will do. HERE now is a hard invisible barrier, and
this barrier strongly denies the possibility of the
existence of a mechanism that would be available
to the brain but not to a machine.

Various claims are sometimes made about possibilities
in physics that might account for some special mechanism
the brain has access to. Usually these are some kind
of quantum effects. My understanding is that the idea
that the brain takes advantage of quantum effects is
not generally accepted, but even if it were true,
that doesn't change the situation. Quantum effects
are computable. Quantum computers cannot compute
anything that regular computers can't. Even if some
hitherto-undescribed quantum effect exists, it will be
possible to build an abstraction for it. I would be
astonished to find that our computational models
aren't already up to the task, but even if they aren't,
we can simply expand them.

The greatest weakness in the entire debate, however,
is the capacity issue. Lack of computing capacity is
a complete explanation for what computers can't do
(yet.) The entire issue is quantitative, not qualitative.
The quantitative issue defeats all the anti-computation
arguments handily, from the Chinese room on. The
quantitative argument handily explains exactly what we
are seeing. Computers get more capable every year.
Tasks that were once beyond reach come into reach,
then become easy. 3D rendering was once completely
out of reach. Then it was possible, but very slow. Then
it was possible in real time, then it was cheap to do on
an XBox. Our primitive wireframe drawings give way to
scanline rendering, and to raytracing, and to radiosity.
Each step requires more computing power, and there
is no indication that this process has some intrinsic
hard upper limit.

Certainly some problems remain out of reach. These
problems are hard. Some problems are hard even for
humans. Consider that a baby sits there and listens
to people talking for a year before attempting single
word utterances. Consider how hard it is to learn a
new language. Is it any surprise then that mechanical
translation is hard for machines? No it is not. It is a
question of capacity. As we see more language
translation efforts using very large corpora, we see
ever greater success: again it is a capacity issue.
That we can mechanize an English-Arabic,
Arabic-English dictionary might cause us irrational
exuberance around the idea of translating one into the
other, but it turns out that natural language translation
is about a lot more than just dictionaries.

In short, it is obvious at this point that man-will-never-build
arguments are doomed. They didn't hold for flying,
swimming, driving faster than a horse, walking on
the moon, or anything else; they do not hold for
thinking. There is no hint of a mechanism available
to the brain that is not available to a computer
circa 1950. There *is* a huge difference in power
between those two, and between the fastest things
we have today, and this power difference is a complete
explanation for the situation we find ourselves in as
far as what cognitive tasks our computers can handle
and what ones they can't. And our computers continue
to get faster and yes, smarter, all the time.


Marshall
.

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