Getting intelligent about the brain
Richard Shim And Ina Fried / ZDNet India November 29,
2004
There's no mistaking what they study at the Redwood
Neuroscience Institute. There are brains all over the
place.
>From the colorful pictures of brain coral that hang on
the walls to the promotional key chains sporting
little plastic cerebral cortices, you'd have to be
gray-matterless not to notice the decorative theme at
this nonprofit scientific research organization.
Though it may all seem a little over the top to the
average visitor, such brain mania seems excusable for
someone who's spent about 25 years studying the
workings of this most thoughtful of organs.
The institute's director, Jeff Hawkins, was interested
in the brain even before he helped spawn an industry
with his most famous invention, the PalmPilot. In his
spare time, he learned the sciences behind brain
research, and after becoming versed in them he
developed his own theory, which is contrary to some of
the established ideas.
In his first book, "On Intelligence," Hawkins explains
his theory and how it can be used to build truly smart
machines--a question others have tackled, through the
study of artificial intelligence and neural networks,
but haven't resolved.
Hawkins says the main difference between his idea and
others is that the other methods try to copy human
behavior using the wrong notion of how the brain
works. The brain doesn't produce an output for every
input, Hawkins says. Instead, it stores experiences
and sequences and makes predictions based on those
memories. Using that realization about intelligence as
a starting point, scientists and inventors can create
new and smarter machines, he says.
And as if it weren't enough to be designing future
handheld and phone devices at PalmOne while running a
research institute, Hawkins is now debating whether he
wants to head a start-up devoted to creating such
intelligent machines.
He recently spoke with CNET News.com about his book
and his brain theory, and about how long we might have
to wait for the appearance of computers based on that
theory.
This book has been about two years in the writing.
What was its genesis?
I have been working on this theory for a while. I've
been going out and giving talks about it, but in a
limited time period I was trying to present the
theoretical framework and the detailed biology behind
it. I found I just could not cover all the basics in a
talk.
Someone suggested to me, "You know, you need to put
this in book form, because that is the only way you're
going to be able to get it all down and have people
sit down and read it." I realized that they were
right.
How would a machine that worked more like the brain do
a better job?
Current computers just don't understand what is being
done, and they don't do a good job. The problem with
something like speech recognition is that computers
are trying to just recognize speech. They take some
pattern and try to match it against some template. We
understand speech, but with current systems, there is
no understanding. So when you have real data coming in
that is messy for the most part, you can't match it.
In your book, you talk a lot about the cortex. What is
it, and why is it so significant?
If you look at a human brain, you can essentially
divide it into two pieces. You have got this big thing
on top, which is the cortex, and you have everything
else stuck up in the middle. It looks like a little
post and that thing in the middle is the old brain.
It's what every other animal has, but only mammals
have the cortex.
Our brains work on a completely different principle
than computers. It doesn't mean you can't emulate a
brain on a computer, but you have to understand what
the brain is doing first.
The cortex is a thin sheet like a dinner napkin, and
it's about as thick as six business cards stacked flat
on top of one another, about six millimeters thick. It
is important because it was determined many years ago
that this is where all intelligence lies. It is the
location for language, map, music, art, programming
culture - everything that we think about (as) humans.
This is where all the things that we think (of) as
higher-level thought perception occur.
The key to understanding what intelligence is, is in
understanding the cortex..
So if I want to build intelligent machines, I'm not
going to base them on the old brain. I want to base
them on the rational part of the human experience.
Fortunately, the cortex is this extremely uniform
structure.
You talk about the brain as always predicting things.
Humans act on those predictions, and experiences
provide sensory input that's sent back to the brain,
which develops new predictions. A computer is mostly
computing its most recent thing and involves very
little prediction. Elaborate on that difference.
Well, our brains work on a completely different
principle than computers. It doesn't mean you can't
emulate a brain on a computer, but you have to
understand what the brain is doing first. The failings
of (artificial intelligence) come from the idea that
you have some input and then you have some output. You
feed in some information, and the output you get
determines the success of the system.
They didn't have a concept of what thinking is or what
perception is or what it means to understand
something. The biggest conceptual difference between
computers and brains is the ability to predict.
Brains have this input, and their output is this
internal prediction mechanism. It's basically saying,
"Hey, before I act, before I do anything, I need to
check. Do I understand what's going on?" Success is
not whether you have the right behavior; it's whether
you actually compute (with the future in mind) and you
can see what's going to happen next.
Assuming your theories are correct and there is a
common algorithm that allows the brain to essentially
process different sensory inputs in a similar manner,
how close are we to understanding that algorithm?
There are some things that I don't understand, but for
the most part I think I've got the basics of it down.
It's not like years away. I have a graduate student
here who is building this stuff now. There are also a
couple of computer science departments working on
this. Computer scientists love this kind of stuff,
biologists are very receptive to this. So I've had
some really great feedback.
How long before this work moves out of academia and
into commercial uses?
I would predict within a year there will be start-ups
working on this. I am debating whether I want to do
that myself.
What do you see as the challenges to making this into
a commercially appealing product?
It's just time and effort. The idea is there; the
technology is there; it's good enough. The only
hesitation I would have about doing this is that I am
still involved heavily in PalmOne.
I also run this institute...Right at the moment I am
in more of the mood of, "Let's see if I can get 1,000
other people working on this."
But it takes a long time. Two years now, no problem:
It will be happening. You know, there will be
businesses started on this, and people will be working
on it.
Is that project and your work at PalmOne at all
complementary? Or are they really two different things
at this point?
They are complementary, and I am interested in both
projects because I think they represent the future of
computers. In PalmOne, it's the future of personal
computing where devices that fit in your pocket are
going to have superfast wireless connections. The work
here is like the future of computing in general.
Do you feel like you're still able to contribute in
the ways that you want at PalmOne? In the early days,
obviously, you were crafting a whole direction.
In the early days I came up with the direction and
then I would craft the nuts and bolts. What I am doing
now at PalmOne is I have a few really big ideas that I
am pursuing and I can't be as involved in the details.
But the conceptual things, what do you do after smart
phones--I can write a position paper, go and meet with
the team, get a manager to explain what these products
have to do. But I can't be there day to day when
someone comes back and says, "You know, the button is
sticking."
Do you think this book writing effort is a one-time
thing? Or are you going to come out with another one?
Oh boy--I hope so. This is hard work. I found I could
only really write if I had huge blocks of time, and I
only have those on weekends.
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