data

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

O'REILLY

big data

O'Reilly Ben Lorica chats with Ion Stoica, UC Berkeley Professor and Databricks CEO, about the rise of Apache Spark and Apache Mesos.

Apache Spark's Journey From Academia To Industry

O’Reilly’s Mac Slocum talks with Edd Dumbbell, VP of strategy at Silicon Valley Data Science, about the data lake, the opportunities the model presents, and the driving forces behind the concept. In the second segment, O’Reilly’s big data guru Ben Lorica chats with Rajiv Maheswaran, CEO of SecondSpectrum, about spatial-temporal pattern recognition — what Maheswaran calls “the science of moving dots.”

The data lake model is a powerhouse for invention

O’Reilly’s Roger Magoulas chats with Tricia Wang, a global tech ethnographer and co-founder of PL Data, about how qualitative and quantitative data need to work together, reframing "data-driven decision making," and how to build the ideal team.

An alternate perspective on data-driven decision making

O'Reilly's Ben Lorica chats with David Blei, co-author of the seminal paper on topic models, and who remains one of the leading researchers in the field. They talk about the origins of topic models, their applications, improvements to the underlying algorithms, and his new role in training data scientists at Columbia University.

Topic models: Past, present, and future

John Follett, editor of "Designing for Emerging Technologies" sits down with Dirk Knemeyer, founder of Involution Studios, who contributed to the book. Knemeyer discusses the changing role of design and designers in emerging technology.

Designers are engineers

O'Reilly's Jenn Webb chats with John Carnahan, executive vice president of data science at Ticketmaster, about Ticketmaster's evolving approach to data analysis, the avenues of user engagement they're investigating, and how his genetics background is informing his work in the big data space. Also, Three Questions with Michael Abbott, a general partner at VC firm Kleiner Perkins Caufield & Byers.

Bridging the gap in big data silos

O'Reilly's Ben Lorica chats with Erich Nachbar, founder and CTO of Virtual Power Systems, about the ease with which Nachbar integrates new open source components into existing infrastructure, his contributions to Mesos, and his new “software-defined power distribution” startup.

Redefining Power Distribution Using Big Data

O'Reilly's Mike Hendrickson chats with database pioneer and 2014 Turing Award recipient Michael Stonebraker about winning the award, the future of data science, and the importance — and difficulty — of data curation.

The Future of Data at Scale

Paco Nathan and Jesse Anderson on the evolution of the data training landscape.

O’Reilly’s Ben Lorica chats with Paco Nathan, director of O’Reilly Learning, and Jesse Anderson, technical trainer and creative engineer at Confluent, about the training landscape in the big data ecosystem, their teaching techniques and particular content they choose, and a look at some expected future trends.

Training in the Big Data Ecosystem

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

Jon Bruner and Mike Loukides talk about the classical music publishing industry and how it's being disrupted by projects like the Petrucci Music Library (http://imslp.org/) that make public-domain scores available online.

The future of classical music

Jim Stogdill, Edd Dumbill and Roger Magoulas have a conversation about in-memory databases and the impact on real time analysis. Leave questions and comments for us at http://radar.oreilly.com/2013/05/talking-about-in-memory.html

Talking about in-memory

Jon Bruner, Mike Loukides and Jim Stogdill from O'Reilly Radar muse on the return of software to the physical world.

Software and the physical world

Jon Bruner, Jim Stogdill, and Roger Magoulas talk about anthropology in big data, advances in JavaScript, searching for ancient civilizations, the importance of context, and good sites for checking the weather.

Related blog post: http://radar.oreilly.com/2013/06/radar-podcast-anthropology-big-data-and-the-importance-of-context.html

Anthropology, big data, and the importance of context

Jon Bruner, Jim Stogdill, and Roger Magoulas talk about what's been on their minds this week: the NSA's surveillance programs, what defense contractors will do with their technology as defense budgets dry up, and a Californian who isn't doing what you think he's doing with hydroponics.

For more on these topics, and links to the things we talked about, see http://radar.oreilly.com/2013/06/radar-podcast-the-internet-of-things-prism-and-defense-technology-that-goes-civilian.html.

The Internet of Things, PRISM, and defense technology that goes civilian

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.