Name: The 2017 Machine Learning Outlook by O'Reilly Radar
Duration: 24 min 56 s
Description: Machine learning has been a mainstream commercial field for some time now, but it’s going through an important acceleration. In this podcast episode, I talk about that acceleration with two executives from MemSQL, a company that specializes in in-memory databases: Gary Orenstein, MemSQL chief marketing officer, and Drew Paroski, MemSQL vice president of engineering.

In this episode, I talk with Kyle Rankin, vice president of engineering operations at Final, a credit card startup. We discuss old versus new approaches to server hardening in light of the cloud, how institutional inertia thwarts change, and the new security-minded desktop OS Qubes.

Kyle Rankin on Modern Server Hardening for the Cloud

Machine learning has been a mainstream commercial field for some time now, but it’s going through an important acceleration. In this podcast episode, I talk about that acceleration with two executives from MemSQL, a company that specializes in in-memory databases: Gary Orenstein, MemSQL chief marketing officer, and Drew Paroski, MemSQL vice president of engineering.

The 2017 Machine Learning Outlook

O'Reilly Media spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. We have a pretty good record at having anticipated some of the big technology developments in recent history. For instance, we launched the first commercial Web site, GNN, in 1993; we organized the meeting at which the term “open source” was first adopted; we were early investors in Blogger, which helped launch the blogging revolution; and more recently, our Web 2.0 conference launched a world-wide meme. We call this predictive sense the “O’Reilly Radar.” And while we’re certainly not always right, we are, at least, good at making interesting guesses.

Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.

The 2017 Machine Learning Outlook

O'Reilly Radar

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