An equation for intelligence: Alex Wissner-Gross at TEDxBeaconStreet

What is the most intelligent way to behave? Dr. Wissner-Gross explains how the latest research findings in physics, computer science, and animal behavior suggest that the smartest actions -- from the dawn of human tool use all the way up to modern business and financial strategy -- are all driven by the single fundamental principle of keeping future options as open as possible.

Intelligence, what is it?

If we take a look back at the history
of how intelligence is being viewed,

one seminal example has been
Edsger Dijkstra's famous quote

that the question of
whether a machine can think

is about as interesting as the question of

whether a submarine can swim.

Now, Edsger Dijkstra, when he wrote this,
intended it as a criticism

of early pioneers of computer science
like Alan Turing.

However, if you take a look back

and think about what have been
the most empowering innovations

that enabled us to build
artificial machines that swim

and artificial machines that [fly],

you find that it was only through
understanding the underlying

physical mechanisms of swimming
and flight that we were able

to build these machines.

And so, several years ago,
I undertook a program

to try to understand the fundamental
physical mechanisms

underlying intelligence.

Let's take a step back.

Let's first begin
with a thought experiment.

Pretend that you're an alien race

that doesn't know anything
about Earth biology or Earth neuroscience

or Earth intelligence, but you have
amazing telescopes

and you're able to watch the Earth
and you have amazingly long lives

so you're able to watch the Earth
over millions, even billions of years.

And you observe a really strange effect,

you observe that over the course
of the millennia,

Earth is continually bombarded
with asteroids up until a point

and that at some point,
corresponding roughly

to our year 2000 AD, asteroids that are
on a collision course with the Earth,

that otherwise would have collided,
mysteriously get deflected

or detonate before they can hit the Earth.

Now, of course, as Earthlings,
we know the reason would be

that we're trying to save ourselves,
we're trying to prevent an impact.

But if you're an alien race
that doesn't know any of this,

that doesn't have any concept
of Earth intelligence,

you'd be forced to put together

a physical theory that explains how,
up until a certain point in time,

asteroids thad would demolish
the surface of the planet,

mysteriously stop doing that.

So, I claim that this is the same question

as understanding the physical
nature of intelligence.

So, in this program that I undertook
years ago, I've looked at a variety

of different threads in crossed science
across a variety of disciplines,

pointing, I think, towards a single
underlying mechanism for intelligence.

In cosmology, for example,

there has been a variety
of different threads of evidence

that our universe appears to be
finely tuned for the development

of intelligence, and in particular,
for the development

of universal states that maximize
the diversity of possible futures.

In gameplay, for example in Go,
everyone remembers in 1997

when IBM's Deep Blue beat
Gary Kasparov at chess.

Fewer people are aware
that in the past ten year or so,

the game of Go, arguably a much more
challenging game because it has

a much higher branching factor,
has also started to succumb to computer

game players for the same reason.

The best techniques, right now,
for computers playing Go,

are techniques that try to maximize
future options during gameplay.

Finally, in robotic motion planning,

there has been a variety
of recent techniques

that have tried to take advantage
of abilities of robots to maximize

future freedom of action in order
to accomplish complex tasks.

And so, taking all of these different
threads and putting them together,

I asked, starting several years ago,
is there an underlying mechanism

for intelligence that we can factor out
of all of these different threads?

Is there, as it were,
a single equation for intelligence?

And the answer, I believe, is yes.

What you're seeing is probably the closest
equivalent to an E=mc2 for intelligence

that I certainly have ever seen.

So, what you're seeing here

is a statement of correspondence
that intelligence is a Force (F)

that acts so as to maximize
future freedom of action;

It acts to maximize future freedom
of action or keep options open

with some strength (T),

with the amount of the diversity
of possible accessible futures (S),

up to some future time horizon (Ƭ).

In short, intelligence doesn't like

to get trapped, intelligence tries
to maximize future freedom of action

and keep options open.
And so, given this one equation

it's natural to ask:
So, what can you do with this?

How predictive is it? Does it predict
human-level intelligence?

Does it predict artificial intelligence?

So, I'm going to show you now a video
that will, I think, demonstrate

some of the amazing applications
of just this single equation.

(Video) Recent research in cosmology
has suggested that universes

that produce more disorder or "entropy"
over their lifetimes should tend

to have more favorable conditions
for the existence of intelligent beings

such as ourselves.

But what if that tentative
cosmological connection

between entropy and intelligence
hints at a deeper relationship?

What if intelligent behavior
doesn't just correlate

with the production of long-term entropy,
but actually emerges directly from it?

To find out, we developed
a software engine called ENTROPICA

designed to maximize the production
of long-term entropy of any system

that it finds itself in.

Amazingly, ENTROPICA was able to pass
multiple animal intelligence tests,

play human games
and even earn money trading stocks;

all without being instructed to do so.

Here are some examples
of ENTROPICA in action:

just like a human standing upright
without falling over, here we see

ENTROPICA automatically
balancing a pole using a cart.

This behavior is remarkable, in part,
because we never gave ENTROPICA a goal,

it simply decided on its own
to balance the pole.

This balancing ability would have
applications for humanoid robotics

and human assistive technologies.

Just as some animals can use
objects in their environments

as tools to reach into narrow spaces,

here we see that ENTROPICA,
again on its own initiative,

was able to move a large disk,
representing an animal,

around so as to cause a small disk,
representing a tool,

to reach into a confined space
holding a third disk

and release the third disk
from its initially fixed position.

This tool usability would have application
for smart manufacturing and agriculture.

In addition, just as some other animals
are able to cooperate

by pulling opposite ends of a rope
at the same time to release food,

here we see that ENTROPICA
is able to accomplish

a model version of that task.

This cooperative ability has interesting
implications for economic planning

and a variety of other fields.

ENTROPICA is broadly applicable
to a variety of domains.

For example, here we see it successfully
playing a game of pong against itself

illustrating its potential for gaming.

Here, we see ENTROPICA orchestrating

new connections on a social network
where friends are constantly

falling out of touch and successfully
keeping the network well connected.

This same network orchestration ability
also has applications in health care,

energy and intelligence.

Here we see ENTROPICA directing
the paths of a fleet of ships

successfully discovering and utilizing
the Panama Canal to globally extend

its reach from the Atlantic
to the Pacific.

By the same token, ENTROPICA
is broadly applicable to problems

in autonomous defense,
logistics and transportation.

Finally, here we see ENTROPICA
spontaneously discovering and executing

a buy low, sell high strategy
on a simulated range traded stock

successfully growing assets
under management exponentially.

This risk management ability
would have broad applications

in finance and insurance.

AWG: So, what you've just seen
is that a variety

of signature human
intelligent cognitive behavior

such us tool use and walking upright

and social cooperation, all follow
from a single equation

which drives a system to maximize
its future freedom of action.

Now, there's a profound irony here.

Going back to the beginning
of the usage of the term robot,

the play RUR,

there was always a concept
that if we develop machine, intelligence,

there will be a cybernetic revolt,
that machines would rise up against us.

One major consequence of this work
is that maybe all of these decades

we've had the whole concept
of cybernetic revolt in reverse.

It's not that machines
first become intelligent

and then megalomaniacal,
and try to take over the world.

It's quite the opposite:
that the urge to take control

of all possible futures
is a more fundamental principle

than that of intelligence;
that general intelligence may, in fact,

emerge directly from this sort
of control grabbing,

rather than vice versa.

Another important consequence
is goal seeking.

I'm often asked how does the ability
to seek goals follow from this framework

and the answer is:

the ability to seek goals, for example
if you're playing the game of chess,

to try to win that game of chess
in order to accomplish worldly goods

and accomplishments outside of that game,

will follow directly from this
in the following sense:

Just like you would travel
through a tunnel, a bottleneck,

in your future path space
in order to achieve many other

diverse objectives later on
or just like you would invest

in a financial security reducing
your short term liquidity

in order to increase your wealth
over the long term,

goal seeking emerges directly
from a long term drive

to increase future freedom of action.

Finally, the famous physicist
Richard Feynman once wrote

that if human civilization were destroyed
and you could pass only a single concept

on to our descendents
to help them rebuild civilization,

that concept should be
that all matter around us

is made out of tiny elements
that attract each other

when they're far apart,
but repel each other

when they're close together.

My equivalent to that statement
to pass on to descendents

to help them build
artificial intelligence,

or to help them to understand
human intelligence, is the following:

Intelligence should be viewed
as a physical process

that tries to maximize
future freedom of action

and avoid constraints in its own future.

Thank you very much.

(Applause)