Karen Hao

And you're just pumping a bunch of data into it, and then it's analyzing the data and creating this, all of these, finding all these correlations in the data, finding all these patterns.

And then it's through those patterns that the machine is then able to act autonomously, right?

And so the way that they're training a self-driving car is they're recording all this footage, and then they have tens of thousands or hundreds of thousands of human contractors that draw...

literally around every single vehicle in the footage, every single pedestrian, every single traffic light, every single lane marking, and label it exactly as such.

So that then it's fed into an AI model that can identify all of these different components.

And then it's connected to another piece of software that is not AI that's saying, okay, if the AI model recognizes the pedestrian, we do not run over the pedestrian.

If the AI model recognizes a red traffic light, we stop.

And so...

The thing about statistical engines is that it's based on probabilities.

It's not based on deterministic logic.

So systems make errors all the time and it's impossible.

It is technically impossible to get them to stop making errors.

Yeah.

It depends on the place.

It depends on whether the Tesla was trained to specifically navigate the place that you're driving.

Because if it's in Mumbai, in some place in Vietnam...

No, it would not be safer.

I would much rather be driven by someone that has been driving in that place their whole life.

I'm not arguing against the fact that in certain places where the car has been explicitly trained to drive in this place, that it has a better safety record than the humans that are driving in that place.

But you specifically asked if I think that all of the... Most cars.