Back in the first part of this century,
when I was running MIT’s Computer Science and Artificial Intelligence Laboratory
(CSAIL) and needed to help raise money
for over 90 di;erent research groups, I
tried to use the memory increase on iPods
to show sponsors how things were continuing to change very rapidly. Here are
the data on how much music storage one
got in an iPod for $400 or less:
Then I would extrapolate a few years
out and ask what we would do with all that
memory in our pockets.
Extrapolating through to today,
we would expect a $400 iPod to have
160,000 gigabytes of memory. But the
top iPhone of today (which costs much
more than $400) has only 256 gigabytes
of memory, less than double the capacity
of the 2007 iPod. This particular exponential collapsed very suddenly once the
amount of memory got to the point where
it was big enough to hold any reasonable
person’s music library and apps, photos,
and videos. Exponentials can collapse
when a physical limit is hit, or when there
is no more economic rationale to continue them.
Similarly, we have seen a sudden
increase in performance of AI systems
thanks to the success of deep learning. Many
people seem to think that means we will
continue to see AI performance increase by
equal multiples on a regular basis. But the
deep-learning success was 30 years in the
making, and it was an isolated event.
That does not mean there will not be
6. Hollywood scenarios
more isolated events, where work from the
backwaters of AI research suddenly fuels
a rapid-step increase in the performance
of many AI applications. But there is no
“law” that says how often they will happen.
The plot for many Hollywood science fiction movies is that the world is just as it is
today, except for one new twist.
In Bicentennial Man, Richard Martin,
played by Sam Neill, sits down to breakfast and is waited upon by a walking, talking humanoid robot, played by Robin
Williams. Richard picks up a newspaper to read over breakfast. A newspaper!
Printed on paper. Not a tablet computer,
not a podcast coming from an Amazon
Echo–like device, not a direct neural connection to the Internet.
It turns out that many AI researchers
and AI pundits, especially those pessimists
who indulge in predictions about AI getting out of control and killing people, are
similarly imagination-challenged. They
ignore the fact that if we are able to eventually build such smart devices, the world
will have changed significantly by then.
We will not suddenly be surprised by the
existence of such super-intelligences. They
will evolve technologically over time, and
our world will come to be populated by
many other intelligences, and we will have
lots of experience already. Long before
there are evil super-intelligences that want
to get rid of us, there will be somewhat
less intelligent, less belligerent machines.
Before that, there will be really grumpy
7. Speed of deployment
machines. Before that, quite annoying
machines. And before them, arrogant,
unpleasant machines. We will change our
world along the way, adjusting both the
environment for new technologies and
the new technologies themselves. I am not
saying there may not be challenges. I am
saying that they will not be sudden and
unexpected, as many people think.
New versions of software are deployed
very frequently in some industries. New
features for platforms like Facebook are
deployed almost hourly. For many new
features, as long as they have passed integration testing, there is very little economic downside if a problem shows up
in the field and the version needs to be
pulled back. This is a tempo that Silicon
Valley and Web software developers have
gotten used to. It works because the marginal cost of newly deploying code is very,
very close to zero.
Deploying new hardware, on the other
hand, has significant marginal costs. We
know that from our own lives. Many
of the cars we are buying today, which
are not self-driving, and mostly are not
software-enabled, will probably still be
on the road in the year 2040. This puts
an inherent limit on how soon all our
cars will be self-driving. If we build a new
home today, we can expect that it might
be around for over 100 years. The building I live in was built in 1904, and it is
not nearly the oldest in my neighborhood.
Capital costs keep physical hardware
around for a long time, even when there
are high-tech aspects to it, and even when
it has an existential mission.
The U.S. Air Force still flies the B-52H
variant of the B- 52 bomber. This version
was introduced in 1961, making it 56
years old. The last one was built in 1962, a
mere 55 years ago. Currently these planes
are expected to keep flying until at least
2040, and perhaps longer—there is talk of
extending their life to 100 years.
I regularly see decades-old equipment
in factories around the world. I even see