NVIDIA AI Podcast

AI is getting better, and it's finding its way into more parts of our lives with each passing day. And talking about the future artificial intelligence has become a surefire way to spawn a thousand debates about the future, and nature, of humankind ourselves. Our guest today, Ken McLeod, is an award winning science fiction author whose work dives deep into the relationship between man and machine. His latest book, "The Corporation Wars: Emergence" is the final volume in an acclaimed trilogy whose cast of characters includes sentient robots, computer AIs that oversee Earth from afar, and, of course, emulated human minds running in digital simulations.

Love. The search for love. The search even for someone you just kind of like. It's been the subject of poems, novels, songs, you name it. For as long as humans have been around, they've been looking for love. But what if you could use AI to automate the process? To help you with everything from finding your true match, to swiping through all those not quite true matches. Oscar Alsing, our guest on this episode, will talk about how he's used AI, and Tinder, to do just that.

Election polling is an inexact science. If you've been paying attention to American politics at all over the past year or two, you don't need us to tell you that. But what if instead of asking voters their opinions on the candidates or the issues you took a different approach, one that involves artificial intelligence... and cars. Joining us for this edition of the AI podcast is Timnit Gebru, a post-doctoral researcher at Microsoft Research in New York and a newly minted PhD from the Stanford Artificial Intelligence Laboratory. Timnit is co-author of a paper titled "Using Deep learning and Street View to Estimate the Demographic Makeup of Neighborhoods Across the United States."

Think you've got no artistic talent? You do now. Vincent AI is an application that lets you pick up a stylus, sketch out a few lines on a screen, and watch as your scribbles are turned into a work of art inspired by one of seven artistic masters. We speak with Monty Barlow, machine learning director for Cambridge Consultants, the technology development house behind this amazing demo.

Ever see a photo of an amazing looking meal, maybe in a food magazine or an Instagram feed, and wish you had the recipe to make it yourself? Thanks to a project born out of MIT's Computer Science and Artificial Intelligence Laboratory we're a step closer to being able to do that. We talk with Nick Hynes, one of the minds and stomachs behind this effort just in time for Thanksgiving and the holiday food season.

Whether you're wandering through the sprawling virtual worlds of Grand Theft Auto... or just trying out a new couch in Ikea's virtual living room, virtual worlds are everywhere. But there's as problem. There just aren't enough artists to build all these virtual worlds and populate them with foes... or furniture. We spoke with Artomatix co-founder Eric Risser about how deep learning can help artists fill such burgeoning virtual worlds.

Tired of waiting in checkout lines? Malong Technologies offers technology that may one day let you grab what you want and go. We spoke to this startup about how it's turning its prowess in some of the world's top image recognition contests into a service businesses can use to put image recognition to work.

Picture this, you find yourself in a tattoo parlor. But none of the dragons, flaming skulls, or gothic font lifestyle mottos you see on the wall seem like something you want on your body. So what do you do? You turn to AI, of course. We spoke to two members of the development team at Tattoodo.com, who created an app that uses deep learning to help you create the tattoo of your dreams.

This might be the first time we've been able to say this, but we might have spoilers ahead on this episode. Joining us we have Zack Thoutt, a data scientist and a developer from Boulder, Colorado. Zack has done something we've all wanted to have done: he's working on finishing the books behind HBO's Game of Thrones - a Song of Ice and Fire - by putting an AI system to work with sometimes comical results.

The robots that have taken on tasks in the real world - which is to say the world where physics apply - are primarily programmed to do a specific job, such as welding a joint in a car or sweeping up cat hair. So what if robots could learn, and take it a step further - what if they could teach themselves, and pass on their knowledge to other robots? Where could that take machines, and the notion of machine intelligence? And how fast could we get there? Those are the questions our guest Sergey Levine, an assistant professor at UC Berkeley's department of Electrical Engineering and Computer Sciences, is finding answers to.