Name: 【TED】Jeremy Howard: The wonderful and terrifying implications of computers that can learn (The wonderful and terrifying implications of computers that can learn | Jeremy Howard)
Uploaded: 2015-07-06T16:00:10.000Z
Duration: 19 min 50 s
Description: Thousands of YouTube videos with English-Chinese subtitles! Now you can learn to understand native speakers, expand your vocabulary, and improve your pronunciation...

Past simple

It used to be that if you wanted to get a computer to do something new,

To-infinitive

Now, programming, for those of you here that haven't done it yourself,

requires laying out in excruciating detail

every single step that you want the computer to achieve, to do

Now, if you want to do something that you don't know how to do yourself,

then this is going to be a great challenge.

So this was the challenge faced by this man, Arthur Samuel.

lay out in excruciating detail, how to be better than you at checkers?

he had the computer play against itself thousands of times

And indeed it worked, and in fact, by 1962,

this computer had beaten the Connecticut state champion.

So Arthur Samuel was the father of machine learning,

because I am a machine learning practitioner.

a community of over 200,000 machine learning practitioners.

to try and get them to solve previously unsolved problems,

and it's been successful  hundreds of times.

So from this vantage point, I was able to find out

a lot about what machine learning can do in the past, can do today,

Perhaps the first big success of  machine learning commercially was Google.

Google showed that it is possible to find information

and this algorithm is based on machine learning.

Since that time, there have been many commercial successes of machine learning.

use machine learning to suggest products that you might like to buy,

sometimes will tell you about who your friends might be

and this is because it's using the power of machine learning.

These are algorithms that have learned how to do this from data

in getting Watson to beat the two world champions at "Jeopardy,"

answering incredibly subtle and complex questions like this one.

This is also why we are now able to see the first self-driving cars.

If you want to be able to tell the difference between, say,

a tree and a pedestrian, well, that's pretty important.

We don't know how to write those programs by hand,

but with machine learning, this is now possible.

And in fact, this car has driven  over a million miles

that we actually sometimes don't know how to do ourselves,

One of the most amazing examples I've seen of machine learning

happened on a project that I ran at Kaggle

where a team run by a guy called Geoffrey Hinton

won a competition for automatic drug discovery.

Now, what was extraordinary here is not just that they beat

all of the algorithms developed by Merck or the international academic community,

but nobody on the team had any background in chemistry or biology or life sciences,

They used an extraordinary algorithm called deep learning.

So important was this that in fact the success was covered

in The New York Times in a front page article a few weeks later.

This is Geoffrey Hinton here on the left-hand side.

Deep learning is an algorithm inspired by how the human brain works,

which has no theoretical limitations on what it can do.

The more data you give it and the more computation time you give it,

The New York Times also showed in this article

another extraordinary result of deep learning

It shows that computers  can listen and understand.

(Video) Richard Rashid: Now, the last step

that I want to be able to take in this process

we've been able to take a large amount  of information from many Chinese speakers

that takes Chinese text and converts it into Chinese language,

and then we've taken an hour or so of my own voice

the standard text-to-speech system so that it would sound like me.

There's much work to be done in this area.

Jeremy Howard: Well, that was at a machine learning conference in China.

【TED】Jeremy Howard: The wonderful and terrifying implications of computers that can learn (The wonderful and terrifying implications of computers that can learn | Jeremy Howard)

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【TED】Jeremy Howard: The wonderful and terrifying implications of computers that can learn (The wonderful and terrifying implications of computers that can learn | Jeremy Howard)

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