Software Architecture

devops

O'Reilly Radar tracks the technologies and people that will shape our world in the years to come. Each episode of O'Reilly Radar features an interview with an industry thought leader, with topics touching on everything from programming to data to experience design. We also take a step back from the breathless pace of the latest tech news to examine why new developments are important and what they might mean down the road.

O'Reilly Radar Podcast

Micro Services

Building a DevOps Team

O'Reilly's Mac Slocum talks with Neal Ford, a software architect and meme wrangler at ThoughtWorks, about software architecture, its relationship with DevOps, and the growing influence of microservices.

How The DevOps Revolution Informs Software Architecture

This week, I sit down with anthropologist, futurist, Intel Fellow, and director of interaction and experience research at Intel, Genevieve Bell. We talk about what she’s learning from current AI research, why the resurgence of AI is different this time, and five things that are missing from the AI conversation.

Genevieve Bell on Moving From Human-Computer Interactions to Human-Computer Relationships

This week, I sit down with Tom Davenport. Davenport is a professor of Information Technology and Management at Babson College, the co-founder of the International Institute for Analytics, a fellow at the MIT Center for Digital Business, and a senior advisor for Deloitte Analytics. He also pioneered the concept of “competing on analytics.” We talk about how his ideas have evolved since writing the seminal work on that topic, Competing on Analytics: The New Science of Winning; his new book Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, which looks at how AI is impacting businesses; and we talk more broadly about how AI is impacting society and what we need to do to keep ourselves on a utopian path.

Tom Davenport on Mitigating AI's Impact on Jobs and Business

In this week's Radar Podcast, O’Reilly’s Mac Slocum chats with Sara Watson, a technology critic and writer in residence at Digital Asia Hub. Watson is also a research fellow at the Tow Center for Digital Journalism at Columbia and an affiliate with the Berkman Klein Center for Internet and Society at Harvard. They talk about how to optimize personalized experience for consumers, the role of machine learning in this space, and what will drive the evolution of personalized experiences.

Sara Watson on Optimizing Personalized Experiences

This week, I sit down with David Beyer, an investor with Amplify Partners. We talk about machine learning and artificial intelligence, the challenges he’s seeing in AI adoption, and what he thinks is missing from the AI conversation.

AI Adoption at the Atomic Level of Jobs and Work

This week, I sit down with Aman Naimat, senior vice president of technology at Demandbase, and co-founder and CTO of Spiderbook. We talk about his project to build a knowledge graph of the entire business world using natural language processing and deep learning. We also talk about the role AI is playing in those companies today and what’s going to drive AI adoption in the future.

Aman Naimat on Building a Knowlege Graph of the Entire Business World

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.