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AI is in the social network you chat on, the engine you search with, the word processor you write with, and the camera you take pictures with. But whats growing fastest in artificial intelligence?

One clue is where the Fortune 50 are placing their AI bets.

And one big tell is what they need training data for.

Training data is really the basis for AI, Wendy Gonzalez, the president and CEO of Samasource told me in a recent TechFirst podcast. At the end of the day, machines need to learn how to speak, see, and hear. And they do so much like a human learns how to speak, see, and hear.

Samasource creates training data the labeled, structured data that teaches a machine or a computer how to do these things for a quarter of the Fortune 50, including top global tech giants like Google and Microsoft. Walmart and GE are customers, as is Nvidia, which makes AI chips that power much of the worlds artificial intelligence. So are automotive giants like Volkswagen and Ford.

That training ranges from as simple as this shape is a car to this is a Louis Vuitton Deauville Mini handbag. But its vital for multiple fields.

So what are the hottest areas that Samasource is getting training data requests for?

We see a lot of growth in AR/VR, Gonzalez says. And this could really include everything, its everything from faces, shirts, shoes, you name it, furniture ... were also seeing a lot of really interesting growth ... in e-commerce. So a lot of things I would describe as visual search: how do you actually look up something and detect whether its a plaid shirt as an example.

Delivery robots also need to know what a sidewalk is, what people and pets look like, how to navigate getting down off a sidewalk and onto a road, and what grass, trees, and bushes look like. Autonomous vehicles need to not just know what a road looks like, and what white or yellow painted lines mean, but also how to recognize a parking space, an upside-down car that might have been involved in an accident ... and all of it in various moderate to extreme weather conditions.

And they have to be able to recognize those objects both with visible light and LIDAR or radar.

The challenge for most AI training data is edge cases, Gonzalez says.

Imagine if you had a representation of hundreds of thousands of vehicles, but only like 10 motorcycles, she told me. Then youve got immediately kind of an inherent bias and so you have to really worry about not just to get the quality data, but do you have the right and most comprehensive representative data.

Interestingly, Samasource isnt just working on the AI projects that youd think. Self-driving cars and delivery robots are fairly obvious applications, after all.

But Gonzalez says AI is getting pervasive across many more domains.

Weve worked on everything from sustainable fishing, to reducing elephant poaching, to financial services classification, Gonzalez says. We definitely see a lot in healthcare. Theres an incredible amount that can be done in the healthcare and life sciences.

Get a full transcript of our conversation here.

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AR, VR, Autonomy, Automation, Healthcare: Whats Hot In AI Right Now - Forbes