Shailesh Kumar - Towards “Thinking Machines”

Okay, so, good morning everyone.

I'll just get started.

My name is Shailesh and I give these talks

almost every year so this is a very deja-vu feeling for me.

The only thing different this time

is the stage is slightly thinner.

But great crowd, great list of talks so far.

So, Daniel called me a couple of weeks ago and said

"Why don't you give a keynote again?"

And I said, "You know, I'm running out of things to say now."

I've given four talks at different forums

with The Fifth Elephant and I wasn't so sure

what I want to talk about.

So, then, one of these days I was talking

to one of my non-geek friends

and he was very excited about what I do

so he said, 'What do you do?'

and I, you know, it was on the phone

and I started talking to him about this, that, and the other.

And for about 45 minutes I was rambling

and this guy was very quiet.

I didn't realise he wasn't a techie

and I was going on and on and after 45 minutes I stopped

and said, "Are you still there?

"Are you listening?"

And he said, "Yeah, I'm listening.

"Can you tell me what do you do again?"
(audience laughs)

And then I realized, how do I summarize this in 2 words?

So then I told him, "Hey, I'm building thinking machines."

And that's when he said, "Why didn't you say that before?

"It was so easy to say that, right?"

So that's how the title came by

and obviously we're not building thinking machines

but what I'm going talk about is towards thinking machines, right?

So, we have a long way to go.

So I added the word "towards" later.

So what I'm gonna talk about is all over the place.

I'm going to talk about philosophy, science fiction.

I'm going to talk about algorithms

and I'm going to talk about, you know, deep learning

and how to think about things beyond deep learning.

All right?

And let me give you a perspective and then we'll start.

So I'll take questions at the end.

Start working this.

All right, so, I ended my last year's talk on this quotation

So I thought I'll start on this quotation this time.

So I like this quotation because it puts a lot

of things into perspective of what we're doing,

how our civilisation got here, and where we're headed.

So it says, "Our technology, our machines, is part of our humanity.

"We created them to extend ourselves

"and that is what is unique about human beings!"

And if you look at chairs, and dogs, and animals, and cats

they don't create machines to extend themselves.

They just have instincts and they follow their instincts.

Right, that's very unique

about human civilisation. We've created
Taj Mahal, and space flights, and internet

And so we've come a very long way.
So if you think about the tools, right?

The cavemen had tools and now we have
a completely robotic assembly line

with no humans and you could turn the
lights off and nothing will happen.

The car would get ???, right? We've gone
from just on-road, bullock carts,

to massive amounts of transportation we
can do now.

If you look at our ability to look further in
the space, again, since Galileo,

we've made a lot of progress, ???
he's certainly a thousand years off our

Pluto fly by. So now we're able to send
satellites into space.

If you look at the first computer we built
and where we are today, right?

We have a huge data centre, and really, if
you look at the whole thing in perspective

we have made an enormous amount of
progress in the last so many centuries.

So if youlook just at the technical part,
the IT kind of intelligent machines,

we're not talking about mixies? and other
things, just look at what AI

and deep learning, this stuff, has
produced. Today's machines can play chess.

And there's no human on the planet who can
play chess better than the machine.

I want to take a pause and think about
where we are.

There's no human on the planet who can
play chess better than the machine.

There's no human on the planet who can
play Jeopardy better than the machine.

And recently, Google came up with
automatic cars, so the machine can

drive cars and record show, that this cars
are better than humans under rider?

conditions. And they have much less
accident rates, and all the accidents

happened because of other humans drivers.
They're not because of cars.

And recently also saw how machines are
able to create pictures, right, so this is

one of the things that deep learning is
internally doing.

And now think about all this. Just think
about where machines have gone today.

How many things they can do which are
way beyond our imagination

that machines could have done.
So obviously there's a lot they've done.

But can they do the following?
We would want to stress their limits

So one of the holy grails of AI is to have
a machine have a conversation with

a human being. We all know the Turing test
and the repercussions of this will be huge

We could think about how we talk to the
internet today. We carefully craft word

for word queries, right, and you know, we
allow the internet to make mistakes

We craft queries again, and we take the
suggestions or not

We talk to the internet like we're talking
to a 3-year-old

Now in the daily needs of massive data
computers, NLP? and all its deploying

staff, imagine how shameful it is to talk
to a computer like a 3-year-old.

So it's got the capacity of thousands of
people but it can't understand language.

So we need to change that. Now imagine
beyond keywords what can happen

We can do question answering, but how do
we do question answering today?

We've created Yahoo Answers. We've created
Quora, where people can type questions

We do a match between the questions
and the answers, and then

we again do retrieval. So not answering
questions.

Now think about conversations.
Conversation is an even more complex thing

If it works out, what are the
repercussions? I don't want to study

physics from my physics teacher. I want to
study from Einstein or Feynman.

We already know all the language and
knowledge of these people.

Can we not have a persona or a person
Feynman or Einstein,

and have a conversation with that person,
right? So just imagine the future

of what will happen if we're just able to
have conversations with the machines.

So there's a long way to go between
keyword search and conversations.

Can we discover a cure for cancer?
There are a lot of diseases out there.

Now obviously there is a lot of research
pharma companies are doing.

There's a lot of new initiatives on how
to use the high end machine learning

in pharma research. But my contention is
I believe that the cure for a lot of

diseases is already out there. In all the
medical literature, if somebody could

actually read them, hold that knowledge in
the brain, in RAM, and do interconnections

we should be able to find a lot of things.
But what is the problem?

A single human expert, even in one field
cannot keep up with that quest of

knowledge, right. We forget some things,
we want to read certain papers.

And therefore, it's the other problem.
We have too much knowledge

and our individual brains are not
capable of forming those connections

in the - because we can't even read that
many docs, right?

But machines could do it, the way, and
then there's progress.

Can we not find cures or new medicine
too.

Can I crack the next IIT Entrance Exam?
You laughing today, but you never know.

Five years from now, what will happen?
We should hope that if Watson is

a test of intelligence, if Igloo is a test
of intelligence, could this not be

a test of intelligence.
The ability of AI system to be able to

actually solve an IIT paper and get a
rank 1.

What about, can I search all the video
scenes, which only have a goal shot

in the football videos and nothing else.
I don't want to watch the rest of it.

A lot of balls going here and there.
I just want to see the goal shots.

Today I cannot do that.
Can my machines be intelligent enough

to vision part, to actually find, this is
a goal, this is a goal, this is a goal -

the rest of it is something else.
So we can imagine the applications now.

We were talking about sarcasm a lot and we
all understand sarcasm is a very hard

thing to do. And imagine if you could
detect sarcasm, what else can you do?

You writing an email to your boss
You're angry, you've written

a sarcastic comment, and ? says,
'Hey are you sure about this?'

In the heat of the moment, can
I put it this way?

So, like, today we do attachments. Can you
detect sarcasm and things like that.

And to me the holy grail of AI is not
really all these big things,

but a really simple thing. Can a machine
find a joke funny?

Now there are a lot of - don't know if you
guys watch Star Trek - but data entry

300, 400 years from now, is an android who
is capable of all these other things.

He's a great supercomputer in human form
but he's still struggling with humans.

That's how hard the problem is.
So obviously we have a long way to go.

We've come a long way and we have a long
way to go.

So this talk is really about the way
forward.

So, what do we imagine the future to be?
We want something like this.

Golden ?
We all want a Jarvis, right?

Who takes care of the chores and gets rid
of the whatever and then we all want

a Jarvis right? So if you watch these
movies again, after watching this talk,

you'll have a very different perspective
on what we need to do to get here.

It's not going to happen just because
we're going to make more and more

Hollywood movies like this.