right, so, what is AI?
well it depends on whom you ask
AI was named a pretty long time ago in the 50s - artificial intelligence
and back then it meant something else in regular usage
and i wonder sometimes whether today's calculators
would have seemed like AI to folks in the 50s
sometimes i like to joke that that version of AI is
whatever would have impressed those folks and whenever that was achieved
you just move the goal posts away a little bit
but in that old school sense it is a
sort of superset
and machine learning would be in there somewhere
where machine
learning is let's remind ourselves
thing labeling using examples
but the way that AI
is talked about today is actually
something else
it's more of a subset to machine
learning
so let's have a look at some "AI tasks"
and see what they have in
common there are tasks like figuring out
whether an image has a cat in it or not
having a natural-sounding, human-sounding conversation
playing games that you don't know the rules for
that you have to use intuition to figure out the rules
well, when you, the human, do these tasks, you are taking in information
through your senses and you get the answer
as if by magic
you don't even know how you know that's a cat
you don't know how you know how to move
that joystick in that game
you just know it
you do something with these pixels
and you don't know what you do
now think about trying to solve a task
like this the traditional way
you have to really think hard, brainstorm
what to do with every pixel
and then give the computer those
instructions by hand:
"here's how you take the pixels for this photograph and here's how you
figure out whether it has a cat in it or
not"
now what recipe are you going to write?
and as you're thinking of that recipe
are you sure it's still gonna work
for that situation?
it's pretty hard to write these rules
you need complicated instructions to do this task
and you have the benefit of eons of evolution
your brain just does this
you have no idea how it does it
and the task is easy for you
and generating the examples and checking
whether the task is done correctly
that's really easy for you
but you don't know how you do the task
so how can you express that to a computer?
you can't solve it the old way
AI (the way we think of it today) is about
succeeding at those complicated tasks
that programmers cannot write
instructions for by hand
and you need super flexible algorithms - 
neural networks - and that is part of a
class of stuff called deep learning
it's part of machine learning
and so when people say "AI" today, they tend to mean "deep learning"
that's the way that it's used
so, solving these really complicated tasks
that you couldn't solve a different way, except by teaching the computer with examples
so this is about automating the ineffable!
you can't say how that task should be done
you can't solve it the way that you do the calorie prediction (example we saw earlier)
now i also want to point out something
really powerful here
when we as humans communicate with one another
when we are trying to get another human
to do something for us
we have two modes of communication
available to us
direct instructions or "hey, look at a
bunch of examples, and *you* figure it out"
and we use both as the situation demands
before machine learning we didn't have the ability to communicate that way with computers
all we could do is give the instructions
directly
so that's like a huge part of our
natural communication
that we want to use... gagged
think of this as an un-gagging
now, as a programmer, you can communicate with the computer two different ways
so don't think of this as something sci-fi
and robot-sy, with a mind of its own
think of it as unlocking a second way to
get computers to do stuff for you
that's what we're about and this is
really powerful because
it's a whole class of tasks that you can
automate
that you just couldn't automate before
you
