WEBVTT

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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 sure

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what I'm gonna 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 realize 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? 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 two 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 gonna 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 gonna talk about philosophy, science fiction.

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I'll talk about algorithms

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and I'm gonna talk about deep learning

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and how to think about things beyond deep learning.

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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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It's not working.

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It's not working, this.

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That's fine.

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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 civilization got here

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and where we are 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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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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If you look at our transportation

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we have 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...

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Since Galileo, 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 and all 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 a machine.

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There's no human on the planet

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who can play Jeopardy better than a 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 you also saw

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how machines are able to create pictures, right?

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So this is one of the things

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that we saw what 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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We would want to stress the limits

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so one of the holy grails of AI

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is to have a machine have a conversation with a human being.

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We all know the Turing test

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and the repercussions of this will be huge.

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If you think about how we talk to the internet today

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we carefully craft three-word, four-word queries, right?

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

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We craft the queries again, 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 day and age needs of massive data computers, NLP

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and all this deep-learning stuff, imagine what a shameful thing 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 have created Yahoo Answers, we have created Quora

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and people who type questions, we do a match.

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Between the questions and the answers

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and then we again do retrieval.

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We're still not answering questions.

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Now think about conversations.

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Conversation is an even more complex thing.

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If it works out, what are the repercussions?

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I don't want to study physics from my physics teacher.

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I want to study it from Einstein or Feynman.

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

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

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and have a conversation with that person?

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So, just imagine the future of what will happen

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if we are able to just have conversations with the machines.

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So, there's a long way to go between

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keyword search and conversations.

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Can we discover a cure for cancer?

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There are a lot of diseases out there.

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Now, obviously there is a lot

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of research pharma companies are doing.

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There's a lot of new initiatives in how

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to use the high-end machine learning in pharma research.

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But my contention is that I believe that the cure for a lot

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of diseases is already out there.

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In all the medical literature, if somebody

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could actually read them, hold that knowledge

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in the brain, in RAM, and do interconnections

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we should be able to find a lot of things.

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But what is the problem?

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A single human expert, even in one field

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cannot keep up with that quest of knowledge, right?

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We'll forget some things, we won't read certain papers.

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And therefore, it's the other problem.

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We have too much knowledge and our individual brains

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are not capable of forming those connections in the...

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Because we can't even read that many documents, right?

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But if a machine could do it

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the way NLP has progressed

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can we not find cures or new medicine?

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Can I crack the next IIT Entrance Exam?

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You're laughing today, but you never know.

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Five years from now, what will happen?

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And we should hope that if Watson is a test of intelligence

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if Igloo is a test of intelligence

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could this not be a test of intelligence?

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The ability of AI system to be able

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to actually solve an IIT paper and get a rank 1.

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Can I search all the video scenes

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which only have a goal shot

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in the football videos and nothing else.

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I don't want to watch the rest of it.

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A lot of balls going here and there.

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I just wanna see the goal shots.

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Today I cannot do that.

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Can my machines be intelligent enough

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the vision part, that can actually find

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this is a goal, this is a goal, this is a goal

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the rest of it is something else.

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So we can imagine the applications out there.

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We were talking about sarcasm a lot

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and we all understand sarcasm is a very hard thing to do.

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

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You're writing an email to your boss

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you're angry, you have written a sarcastic comment

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and Gmail says, "Hey, are you sure about this?"

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In the heat of the moment
(audience laughs)

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can I put it this way?

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So, like, today we do attachments

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can we detect sarcasm and things like that?

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And to me the holy grail of AI is not really

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all these big things, but a very simple thing.

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Can a machine find a joke funny?

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Now there are a lot of...

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I don't know if you guys watch Star Trek

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but Data, in 300 years, 400 years from now

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is an android.

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He is capable of all these other things.

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He's a great supercomputer in a human form

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but he's still struggling with humor.

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That's how hard the problem is.

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So obviously we have a long way to go.

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We have 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?

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We want something like this.

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Good and bad, hopefully good.

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We want a Jarvis, right?

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We all want a Jarvis

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who'll takes care of the chores

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and get rid of whatever

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and we all want a Jarvis right?

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So if you watch these movies again

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after watching this talk

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you'll have a very different perspective

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on what we need to do to get here.

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It's not gonna happen just because we're gonna

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make more and more Hollywood movies like this.

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I mean, Asimov wrote "I, Robot" in the 70s

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and we're still not there.

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It's not gonna happen because we keep doing

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"data science"

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And that's one of the reasons why I wanted

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to do this talk 'cause a lot of people keep

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thinking "data science is the end of the world"

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but there's a lot more to data science

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and I want to see how we can go beyond

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data science

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- and this is not data science.

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This is artificial intelligence.

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Right? So I want to draw the distinction

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and say how we can move beyond data science

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- nothing wrong with it -

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but it's, it's a done deal.

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Right? We have software you can download,

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you can put up whatever you want,

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it's a done deal. Data science has been

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packaged, already.

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Right? If you look at Microsoft Azure,

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or some of these other softwares, right?

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It has already been packaged

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All you have to do is download the right

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software, put your data in the right format,

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and you're done.

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Right? So there's nothing "great"

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about data science anymore.

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Sorry about that, but, you know,

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we need to jolt ourselves out of this

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comfort zone, and say

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"okay, we are all data scientists"

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- that's not it, right?

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How do we get here?

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How will data science get here?

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Alright. So, we'll get here by asking

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a lot of deeper questions.

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Right? Not the questions like

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"Why is this customer
returning from Flipkart?", right? or

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"Who's -- what is the next product to
recommend to somebody?", or

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"Which movie you're going to ask?"
These are not the questions

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that'll take us to the next stage. Right?

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So the question that'll take us
to the next stage is

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"what is learning?" Fundamentally, 
philosophically.

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"What is learning?" We see that we
are learning, children are learning,

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everybody is going to school, 
we all are learning.

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We think that machine learning is learning,

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but what is learning really, right?

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"What is understanding?"

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What does that mean?
What does the word "mean" mean?

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What is thinking? We keep saying

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"Oh -- I'm thinking about this"

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What are you doing when you're thinking?

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So, today I'm going to show you an
equation of thinking.

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Okay? So, it'll be fun -- I don't claim

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this is - THE - equation of thinking,

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but I'm trying to get to that plot point

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where we start thinking about thinking,

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and not just think.

99:59:59.999 --> 99:59:59.999
"What is creativity?" Now, creativity is,

99:59:59.999 --> 99:59:59.999
if you look at an artist, or a musician,

99:59:59.999 --> 99:59:59.999
or even a scientist, we create 
new inventions

99:59:59.999 --> 99:59:59.999
out of the knowledge we have,

99:59:59.999 --> 99:59:59.999
and innovation is a manifestation of
the knowledge in a certain form.

99:59:59.999 --> 99:59:59.999
Right? A poet creates, a musician creates --

99:59:59.999 --> 99:59:59.999
so what is creativity?

99:59:59.999 --> 99:59:59.999
And the last question I have, here is

99:59:59.999 --> 99:59:59.999
"What is consciousness?" Right?

99:59:59.999 --> 99:59:59.999
So, ultimately, if you look at movies like
"I, Robot",

99:59:59.999 --> 99:59:59.999
the word "I" from the robot is
not really about

99:59:59.999 --> 99:59:59.999
the robot's great abilities at
mundane tasks,

99:59:59.999 --> 99:59:59.999
but really it's about the "I" in it.

99:59:59.999 --> 99:59:59.999
"I am a conscious being", and now what are
the consequences.

99:59:59.999 --> 99:59:59.999
Right? So what is consciousness, and

99:59:59.999 --> 99:59:59.999
can we have sentient machines at the
end of the day, right?

99:59:59.999 --> 99:59:59.999
So, we won't go there today,
maybe we'll see

99:59:59.999 --> 99:59:59.999
if we have time we'll watch a video,

99:59:59.999 --> 99:59:59.999
but I'll try to cover the bottom three and

99:59:59.999 --> 99:59:59.999
see if we can find something interesting.

99:59:59.999 --> 99:59:59.999
So, learning. Learning is one of the
most basic things,

99:59:59.999 --> 99:59:59.999
we all do learning all the time.

99:59:59.999 --> 99:59:59.999
-- at least we all claim to
be learning all the time