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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.