But here's how the whole thing fits together.

Forecast

And now, that gives us the new state.

If that guy's going down to zero, I'll know.

He is very unpredictable. He can't be trusted.

With any luck at all, we may be able to anticipate where in the infrastructure they're targeting next.

These are old faculty salaries.

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Monthly estimates

And the reason that we need to use science is because then we can reproduce what we're doing it's not just wisdom or guesswork.

That's called correlation.

So this happens in physics all the time.

What's our time frame?

I don't know what you do.

Anticipation.

There's also a measurement update step where we use the measurement z.

Everything went according to our projections. The Empire's been stabilized.

Before, when we just did simple regression, that was our equation.

And then I'll observe again the 2.

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Here are my best guesses. Okay?

Try to feel his next movement.

Take upstairs.

We're expecting resistance

I am just going to show you two. So we have, our first one is uh, we can predict why from the mediator variable.

We can just conclude that. This more complex model.

That's a bit unusual.

Do research where two models are competing against one another.

We actually think the future's going to be event driven.

So that's a toggler.

You can follow it through the fossil record.

And they estimated that in 2008,

And who knows?

Have you anydea how he intends to do that?

You won't see the next one coming either.

Here is another vehicle, and another one.

Here is the demand forecast for 1998.

But most of the world in the middle are pushing forwards very fast.

So this scenario makes predictions.

There's different things you could try to do with machine learning technique.

Bush count 'em again ... You can violate your expectations about experience.

This should be very familiar to you.

And there's another example.

Become unpredictable.