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We might well ask what does all this data
have to do with intelligence in any way?

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To paraphrase Einstein, who made this a,
comment, data is about knowing things or

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knowing facts, or data points.
The point is to understand and then to

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predict.
And that's what all knowledge and use of

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knowledge is all about.
I'll illustrate this with a simple

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example.
This is a simple game and the red dots are

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following the eyes of the player.
As the game is played.

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Notice where the dots are, and notice
this, look at this player on the right

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instead.
There's a marked difference between.

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How the player on the left plays, which is
how the player on the right plays.

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Can any of you figure this out?
It's quite simple/ The player on the left

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is reacting to where, the ball is.
Whereas the player on the right, is.

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Predicting, where the ball is going to go.
If you were to, wonder, which kind of game

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you played, what would your guess be?
Turns out that almost all of us play the

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game on the right.
Which is predictive intelligence.

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The question is how.
And we learn to play the game on the right

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from all the data that we encounter in our
lives.

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So what we're gonna talk about in this
course is organized.

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In the following way.
The kind of data that we find, in the

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world.
By looking around.

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How we dis, figure out which data to tune
into versus ignore.

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What kind of facts or knowledge we can
learn from such data.

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How we can put two and two together and
connect different pieces of data with each

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other just.
An then use these connections to predict.

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What's going to happen next?
And finally, though we might not get to

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that in this course, how do use these
predictions to figure out where to move

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the paddle, and correct our own actions?
Turns out that prediction, based on past

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experience, is what all conscious human
beings, conscious animals, in fact, do all

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the time.
And that is exactly what big data enables

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large number of machines to do every day
on the web.

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Let's see how.
