Hi everyone, welcome to the A6 and Z podcast. I'm Sonal. Given all the ongoing excitement around artificial intelligence, deep learning and machine learning, especially with the NIFs conference this coming week, today we're talking about what happens when we go from so-called toy problems to practical AI in production. The conversation is also part of our ongoing series on AI and practice. You can find other past and upcoming episodes on our website under that tag. But joining us for this episode, we have Joe Spesak,

who leads strategic and programmatic partnerships for Amazon Web Services, so has a front row seat

on what's happening with a bunch of companies interested in AI and machine learning. We have Scott

Clark, who's a CEO and co-founder of Sigopt, which provides

optimization as a service. And then we have general partner Martine Casado. The discussion covers

everything from taxonomies of startups and methods for AI to a brief debate about whether

AI means the end of theory or not. And we also discuss the problems of data and optimization,

as well as pros and cons of machine learning as a, and touch on the theme of the API economy.

But we begin by quickly reflecting on where we are right now.

What are we seeing with companies adopting AI beyond R&D?

The first voice you'll hear is Scott followed by Joe. Why now?

So I think AI is kind of this, in this unique position that it hasn't been in historically before.

All the pieces are coming together.

People have the data sets now.

They have the tooling and the open source community.

It's been huge in that with tools like MXNet and TensorFlow being widely adopted and

productionalized.

And now they have the infrastructure readily available with things like AWS and all these new Nvidia chips. In addition to a whole bunch of APIs to make a lot of the

hiccup and like difficult parts of the system easier and easier. And so the combination of all these

things together means that instead of spending a decade in the R&D lab to try to come up with

something, now a couple of data scientists can make real business impact almost immediately with the AI go-to-market.

I mean, as AWS, I think we have more than 2 million customers now on our platform.

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