In this final video, I was tempted to make some predictions about the future of
research on neural networks. Instead, I'm going to explain to you why
it would be extremely foolish to try to make any long term predictions.
I'm going to try and explain why we can't predict the long term future by using an
analogy. Imagine you're driving a car at night,
and you're looking at the taillights of the car in front.
The number of photons that you receive from the taillights of the car in front
falls off at one over d squared, where d is the distance to the car in front.
That's assuming that the air is clear but now suppose there's fog.
Over short ranges, the number of photons you get from the tail lights in front of
you, still falls off as one over d^2. Because over a short range, the fog
hardly absorbs any light. But for large distances, it falls off as
E to the -D. And that's because fog has an exponential
effect. Fog absorbs a certain fraction of the
photons per unit distance. So for small distances, fog looks very
transparent, but for large distances, it looks very opaque.
So, the car in front of us becomes completely invisible at a distance at
which our short range model, the one of a discreet model, predicts it will be very
visible. That causes people to drive into the back
of cars in fog. It kills people.
The development of technology is also typically exponential.
So over the short term, things appear to change fairly slowly.
And it's easy to predict progress. All of us, for example, can probably make
quite good guesses about what will be in the iPhone six.
But in the longer run, our perception of the future hits a wall, just like with
fog. So the long term future of machine
learning in neural nets is really a total mystery.
We have no idea what's going to happen in 30 years' time.
There's just no way to predict it from what we know now.
Because we're going to get exponential progress.
In the short run however, in a period of say three to ten years, we can predict it
fairly well. And it seems obvious to me that over the
next five years or so. Big deep neural networks, you are going
to do amazing things. I'd like to congratulate all of you who
stuck it out long enough to get this far. I hope you've enjoyed the course and good
luck with the final test.