when and how could humans build things as smart as a mouse?

Click here to see a new paper on this subject

I sometimes hear people say: "Don't worry... yes, the human race is on track to kill itself off, but
before that happens, we can build artificial (general) intelligence which will  carry on. We can even download ourselves to those computers and live forever." And I sometimes hear major
corporations say "We have already built the equivalent of a cat brain, in hardware.."

In all fairness, those folks are not at the real forefront of the neural network field, and don't
really know what kind of engineering it takes to make such visions real.  The paper above
was written this past week for an invitation-only workshop at Yale, aimed at the kind of people
who are most serious about being able to make real progress in building such systems.

But a warning -- I tried to give a very clear overview of the reality, and the schedule (about a century if people work harder and faster than they seem to be doing now, with funding support beyond what
I really see out there now).  As clear and as earthy as possible... bit what's clear to one person may not be easy for another.


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What really is easy for different types of people?

At one time, back in the 1970s, I woke up one day to learn that I had actually become a tenure track faculty member in political science at a major university. (How could something like
that happen by accident? The story of my life... But, in brief, the department location was the accident.) And lots of people exhorted me: "Say it in plain English. Don't use equations.
Use the simplest plainest English you can."

Many years later, I came to understand how bad that advice was. People would go back to
some of those articles and say : "Why didn't you just say the same thing in equations? It would have been so much easier to see what you are really saying." Or flow charts.

In 2008, I had a paper published (and paid for open access) in the International Journal for
Theoretical Physics, on the subject of temporal physics, which I worked EXTREMELY hard to write in the most baisc possble English, using only a sprinkling of very crucial basic equations. A FEW people said "yes, this is very clear and very decisive," but it seems a lot of folks simply found it hard to understand. That was a bit surprising to me.

How could they have problems with something so simple and straightforward? Later,
I got some inkling of the problem, when a famous physicist (whom some regard as the
champion of backwards time physics, though he came to the subject much later) explained how
the metojd of backwards time physics allows one to predict experiments we could not predict before.
"It is exactly the same theory as standard quantum field gthoeyr, but it gives us different predictions."
In my paper, I had made some tacit assumptions, like that a theory gives predictions, and that systems which give different predictions are different theories. I guess that kind of simple idea was
so alien to lots of folks they found it hard to imagine what it is like to reason about
theory and experiment ... from... the viewpoint of the scientific method.
It reminds me of the joke one can sometimes hear at NSF: "The gap between theorists and experimental people has becme so great that the scientific method itself has become a
rare exercise in crossdisciplinary cooperation.  At least we do try to encourage such
cooperation.. sometimes."

I also remember giving a kind of flow  chart description of simple brains or intelligent systems
at a workshop led by eminent neuroscientist and psychologist Karl Pribram. I was really happy
when the dean commented, in his introduction to the workshop, "hey, here is a paper I can actually understand, which makes some kind of sense." (It is in one of the edited books by Karl Pribram, under Erlbaum and INNS.) But Karl later said to me: "Why is your model of the brain so complicated? Can't it be said in simpler terms?"

My response: "It really is simple... in the same way that general relativity is simple. But it does require some prerequisites.
    "One can wtte a simple description, or 'poem to the brain,' which is true and useful but does
not fully answer the question. By analogy, one can describe a factory or a robot in a useful simple way... but you can't actually build one, or understand how it really works, without knowing certain basic principles.'

So this paper is written to be as simple as possible, but for folks who are demanding about knowing what the basic principles really are...

And yet, it fits other things which I have posted on this blog, which are much less demanding, but express some of the same ideas. But since there were no equations, did you truly understand?
Whatever...

But