

Human-Level AI Is Harder Than It Seemed in 1955 – John McCarthy (2006) - shawndumas
http://www-formal.stanford.edu/jmc/slides/wrong/wrong-sli/wrong-sli.html

======
tr352
What I miss in these notes, and what I think is the main question we should be
asking ourselves, is the question of the black-box approach. That is, do we
understand what intelligence amounts to? On the one hand, we want to be able
to say yes but on the other hand, we haven't been able after all these years
to formalize the concept of intelligence in a satisfactory or even meaningful
way. So the answer seems to be no. Moreover, do we even know what intelligence
is?

Thus, should we instead be building black-box systems that behave seemingly
intelligently without understanding _why_ they behave intelligently? I.e.
neural networks, deep learning? Is this a good investment? It seems so, at
least in the short term. But what about the long term? I don't know the
answer.

Having said that, I've been working for some time on non-monotonic reasoning
and related subjects, which are typical symbolic logic approaches to AI, and I
believe that what I am doing, while intellectually very worthwhile, is a dead
end in the context of AI. I'm sometimes surprised at how easily we get money
to get to work on this stuff. So I agree with the point that lack of funding
is not the problem.

~~~
harperlee
Could you please elaborate on why do you believe it is a dead end? I'm
learning about symbolic logic and I would love to have some pointers on the
limitation of the approach... From what I've read to date, it's just too
expensive to have a proper rule set, but I haven't found a good discussion on
the limitations of the approach!

------
serf
_John von Neumann was busy dying. Anyway he disapproved of the Newell-Simon
work on chess, probably of AI in general._

made me laugh.

When McCarthy had just died I remember a video from a fellow that worked with
him somewhere talking about how until the day of his death he had massive
amounts of bandwidth piped into his house, and that the fellow wondered what
he did with it all, sort of like a mad scientist.

I still wonder sometimes when I think about him. I sort of like to think that
he was busting out work towards the 'obstacle' points in this paper 'til the
very end.

------
dicroce
The human brain has about 100 billion neurons. The human genome is 770MB (in
.2bit format)... So, we know the genome doesn't have even close to enough
information to describe all of the connections within the brain... This means
that the brain must be an emergent phenomenon.. There must be some gross
structure, or general mechanisms described in the genome and the rest is left
to learning...

Andrew Ng at Stanford built the largest neural network to date, with 11.2
billion parameters (which I'm going to take to mean 11.2 billion neurons, as
I'm assuming the parameters are the neuron weights)... So we're still pretty
far off of human numbers of neurons... In addition, humans have the be bathed
in sensory input for years before they begin to show intelligence..

~~~
sk5t
Did anyone ever suppose the genome could possibly describe the functioning of
the brain? After all, learning to play an instrument doesn't change your
genome, and who could even take a stab at estimating how many bits of storage
it takes to "store" mastery?

~~~
tmzt
I took it to mean that there isn't enough storage in the genome to encode the
initial full linkage of neurons, not that learning would have to be written
back to the genome in order to change the ongoing network.

------
cLeEOGPw
We will have article with same title, just years changed to 2045 and 2015
respectively. And probably one or two 30 year periods after that too. People
underestimate the complexity of intelligence because of how common sense it
seems to us.

------
superobserver
It shouldn't actually be hard, especially when you look at how our brains lead
to a recognizably human intelligence. Problem is, as has been pointed out by
Jeff Hawkins, no one in AI research care(d/s) to look at biology to see what
might be learned.... So much heat and funding without light.

Edit: this was meant somewhat ironically to get the point across that we can't
be expected to succeed with AI unless we know how HI actually works.

~~~
simonh
The problem with that is, we still dont really know how the brain works
either. Yes we know roughly how neurons work, but how does that lead to the
making of a decision? No clue. The best we can do is look at various
activation patterns in the anterior cingulate cortex and wonder. It's like
trying to figure out how a CPU works by measuring fluctuations in its
temperature and power draw as it performs calculations.

~~~
superobserver
Well, yes, which is the point. If we don't know how our brains do this
intelligencing, then how can we expect any program or machine to do the same?
This is a part of the failure of AI research. Can't put the cart before the
horse. Well, you can, but it probably won't work.

~~~
threatofrain
Well it is possible that human-like intelligence is a lot harder to build, and
that you are unnecessarily complicating your journey by asking for human-like
intelligence straight off the bat as a requirement of definition.

Like, I would think an AI that can perform capricious causal modelling from
sensory or experimental data is already really sexy, even if it couldn't match
up to human intelligence, or if it wasn't built in the same way as a brain.

Or, an AI that can perform capricious maps or analogies between situations.

~~~
superobserver
I'm not suggesting a HI emulation, actually. If you're interested, you can get
a gist of what I'm suggesting by reading Hawkins "On Intelligence". The basic
building blocks of intelligence in the brain will be the principles on which
legitimate, workable AI research programs will have their first start. From
there I'd anticipate radicalization and innovation based on a profound
understanding of those principles which will have been shown to work. But we
have to do that by understanding what intelligence actually is - and the best
available model we have for that is human intelligence, and thus the human
brain.

