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Okay, so, good morning everyone.

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I'll just get started.

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My name is Shailesh and I give these talks

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

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The only thing different this time

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is the stage is slightly thinner.

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But great crowd, great list of talks so far.

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

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

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

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I've given four talks at different forums

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with The Fifth Elephant and I wasn't so sure

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what I want to talk about.

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So, then, one of these days I was talking

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to one of my non-geek friends

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and he was very excited about what I do

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so he said, 'What do you do?'

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and I, you know, it was on the phone

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

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And for about 45 minutes I was rambling

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and this guy was very quiet.

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I didn't realise he wasn't a techie

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

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and said, "Are you still there?

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"Are you listening?"

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

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

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

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

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

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

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So that's how the title came by

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and obviously we're not building thinking machines

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

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So, we have a long way to go.

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So I added the word "towards" later.

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

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

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I'm going to talk about algorithms

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

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and how to think about things beyond deep learning.

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All right?

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

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So I'll take questions at the end.

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Start working this.

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

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

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So I like this quotation because it puts a lot

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of things into perspective of what we're doing,

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

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

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"We created them to extend ourselves

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

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

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they don't create machines to extend themselves.

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They just have instincts and they follow their instincts.

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Right, that's very unique about human civilization.

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We've created Taj Mahal, and space flights, and internet

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and so we've come a very long way.

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So if you think about the tools, right?

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The cavemen had tools and now we have

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a completely robotic assembly line with no humans

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and you could turn the lights off and nothing will happen

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the cars will get produced, right?

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We've gone from just on-road, bullock carts,

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to massive amounts of transportation that we can do now.

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If you look at our ability to look further

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into space, again, since Galileo,

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we have made a lot of progress.

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Recently we saw the news of Pluto flyby

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so now we're able to send satellites into space.

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If you look at the first computer we built

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and where we are today, right?

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We have a huge data center, and really

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if you look at the whole thing in perspective

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we have made an enormous amount of progress

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in the last so many centuries, right?

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So if you look just at the technical part

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the IT kind of intelligent machines

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we're not talking about mixies

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and other things, just look at what AI

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and deep learning, this stuff, has produced.

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Today's machines can play chess.

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And there's no human on the planet

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who can play chess better than the machine.

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

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There's no human on the planet

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who can play chess better than the machine.

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There's no human on the planet

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who can play Jeopardy better than the machine.

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And recently, Google came out with automatic cars

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so the machines can drive cars and record show

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that these cars are better than humans under ideal conditions

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And they have much less accident rates

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and all the accidents happened because of other humans drivers.

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They're not because of cars.

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And recently also saw how machines

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are able to create pictures, right?

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So this is one of the things

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that deep learning is internally doing.

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And now think about all this.

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Just think about where machines have gone today.

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How many things they can do

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which are way beyond our imagination

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that machines could have done.

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So obviously there's a lot they've done.

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But can they do the following?

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So obviously there's a lot they've done.

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

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have a conversation with a human being.

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We all know the Turing test and the

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repercussions of this will be huge.

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

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We carefully craft word-for-word queries, right?

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And you know, we allow the internet to make mistakes.

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

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

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Now in the daily needs of massive data computers, NLP

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and all its deploying staff, imagine how shameful it is

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to talk to a computer like a 3-year-old.

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So it's got the capacity of thousands of people

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but it can't understand language.

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So we need to change that.

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Now imagine beyond keywords what can happen.

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We can do question answering

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but how do we do question answering today?

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We've created Yahoo Answers, we've created Quora

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where people can type questions

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We do a match between the questions and the answers

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and then we again do retrieval.

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So not answering questions.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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and our individual brains are not
capable of forming those connections

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

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

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Can we not find cures or new medicine
too.

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

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

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

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

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actually solve an IIT paper and get a
rank 1.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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So this talk is really about the way
forward.

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

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Golden ?
We all want a Jarvis, right?

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

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

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

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

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Hollywood movies like this.