The O'Reilly Design Podcast explores how experience design -- and experience designers -- are shaping business, the Internet of Things, and other domains.

O'Reilly Design Podcast

The O'Reilly Media Podcast 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. The O'Reilly Media Podcast features interviews with the people working on the forefront of technology.

O'Reilly Media Podcast

The O'Reilly Security Podcast examines the challenges and opportunities for security practitioners, with a focus on the people on the frontlines of security, working to build better defenses.

O'Reilly Security Podcast

The O’Reilly Programming podcast features conversations that give developers, engineers, and architects tips on getting projects done better and faster.

O'Reilly Programming Podcast

The O'Reilly Data Show explores the opportunities and techniques driving big data and data science. Through interviews and analysis, we highlight the people putting data to work.

The O'Reilly Data Show Podcast

O'Reilly's Mary Treseler talks with information architect Jorge Arango about the state of IA and the importance of designers' understanding of context and perspective.

Information Architecture's Role in UX Design

O'Reilly's Ben Lorica chats with Mike Cafarella, assistant professor of computer science at the University of Michigan and co-founder of both Hadoop and Nutch.

From Search to Distributed Computing to Large-scale Information Extraction

In this special holiday episode of the Radar Pocast, we’re featuring a podcast cross-over of the O’Reilly Design Podcast, which you can find on iTunes, Stitcher, TuneIn, or SoundCloud. O’Reilly’s Mary Treseler host’s the Design Podcast, and in this episode, she chats with Airbnb’s head of experience design Katie Dill about the values that drive design at Airbnb, the triforce structure of the company, and the process of journey mapping their users’ experience.

Katie Dill on Heading Up Experience Design at Airbnb

O’Reilly’s Jenn Webb chats with Eric McNulty, a consultant, writer, speaker, and catalyst for positive leadership. McNulty talks about real-time disaster response, the connections between disaster response and organizational leadership, and how today’s leaders can achieve order beyond control and influence beyond authority. McNulty will talk more about instituting effective leadership at the Cultivate leadership training at Strata + Hadoop World in San Jose in March.

Eric McNulty on Real-Time Disaster Reponse and Leadership Beyond Control

David Beyer, co-founder and CEO of Chart.io, principal at Amplify Partners, and part of the founding team at Patients Know Best, chats with Risto Miikkulainen, professor of computer science and neuroscience at the University of Texas at Austin. They chat about evolutionary computation, its applications in deep learning, and how it’s inspired by biology.

Risto Miikkulainen on Evolutionary Computation and Making Robots Think For Themselves

In this week's episode, Hannah Grenade, a tech entrepreneur and former partner at McKinsey, chats with Matt Harris, managing director at Bain Capital Ventures. They talk about the most interesting areas in fintech innovation, taking a look at some hits and misses, and potential untapped areas of opportunity. Harris also talks about why the merchants payment battleground is no longer a great space for startups and why insurance is poised to be the final frontier for fintech innovation.

Matt Harris on Fintech Sectors Ripe for Innovation

In this episode of the O’Reilly Data Show, I spoke with Rajat Monga, who serves as a director of engineering at Google and manages the TensorFlow engineering team. We talked about how he ended up working on deep learning, the current state of TensorFlow, and the applications of deep learning to products at Google and other companies.

Building Intelligent Applications with Deep Learning and TensorFlow

This week, I chat with Othman Laraki, co-founder of Color Genomics. We chat about challenges and opportunities in genetic testing, the future of precision medicine, and the hurdles medicine and health care are currently facing (and how we can overcome them).

Othman Laraki on Achieving the Long-Tail Distribution of Genetic Insights

In this week’s Design Podcast, I sit down with Kristin Skinner, managing director at Adaptive Path, head of design management at Capital One, and co-author of "Org Design for Design Orgs."  We talk about managing design teams, scaling design, and what we can learn from the Golden State Warriors.

Kristin Skinner on Designing Design Organizations

What does it take to build a data-driven culture? In this O’Reilly Podcast episode, I pose that question to Ashish Thusoo, founder of Qubole. With his co-founder Joydeep Sen Sarma, Thusoo built a self-service data infrastructure at Facebook beginning in 2007. That infrastructure transformed Facebook’s culture and became part of practically every product decision that the company made.

Building a Data-Driven Culture

In this week's episode, O'Reilly's Mac Slocum sits down with Richard Cook and David Woods. Cook is a physician, researcher, and educator, who is currently a research scientist in the Department of Integrated Systems Engineering at Ohio State University, and emeritus professor of health care systems safety at Sweden’s KTH. Woods also is a professor at Ohio State University and is leading the Initiative on Complexity in Natural, Social, and Engineered Systems, and he's the co-director of Ohio State University’s Cognitive Systems Engineering Laboratory. They chat about SNAFU Catchers; anomaly response; and the importance of not only understanding how things fail, but how things normally work.

Richard Cook and David Woods on Successful Anomaly Response

This week, I sit down with Hilary Mason, who is a data scientist in residence at Accel Partners and founder and CEO of Fast Forward Labs. We chat about current research projects at Fast Forward Labs, adoption hurdles companies face with emerging technologies, and the AI technology ecosystem—what's most intriguing for the short term and what will have the biggest long-term impact.

Hilary Mason on the Wisdom Missing in the AI Conversation

In this episode, I talk with Steven Shorrock, a human factors and safety science specialist. We discuss the dangers of blaming human error, studying success along with failure, and how humans are critical to making our systems resilient.

Steven Shorrock on the Myth of Human Error

In this episode, I talk with Jessy Irwin, VP of security and privacy at Mercury Public Affairs. We discuss how to communicate security to non-technical people, what security might look like for small businesses, and moving beyond shame. We also meet her neighborhood gang of grannies who’ve learned how to hack back.

Jessy Irwin on Making Security Understandable for Everyone

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

In this episode of the O’Reilly Programming Podcast, I talk about Swift with Paris Buttfield-Addison, co-founder of Secret Lab, a mobile development studio that builds games and apps for mobile devices. He is the co-author of "Learning Swift," and a presenter of the Learning Path "Getting Started with Swift on the iPad" and the video "Ultimate Swift Programming."

Paris Buttfield-Addison on Whats New in Swift Programming

This week, I sit down with Travis Lowdermilk senior UX designer at Microsoft, and Jessica Rich, UX researcher at Microsoft; Lowdermilk and Rich are also co-authors of the "Customer Driven Playbook." We talk about why failing fast is not always a good approach, sensemaking, and never losing track of the customer’s voice.

Travis Lowdermilk and Jessica Rich on Building a Customer-Driven Culture at Microsoft

In this episode of the Data Show, I spoke with Jeremy Stanley, VP of data science at Instacart, a popular grocery delivery service that is expanding rapidly. As Stanley describes it, Instacart operates a four-sided marketplace comprised of retail stores, products within the stores, shoppers assigned to the stores, and customers who order from Instacart. The objective is to get fresh groceries from popular retailers delivered to customers in a timely fashion. Instacart’s goals land them in the center of the many opportunities and challenges involved in building high-impact data products.

Data Science and Deep Learning in Retail

This week, I sit down with Cynthia Savard Saucier, director of design at Shopify and author of Tragic Design. Saucier also is keynoting at Velocity in New York, October 1-4, 2017. We talk about moving from working in design to leading designers, the real and sometimes negative impact that design decisions can have on users, and how design is organized at Shopify.

Cynthia Savard Saucier on Design at Shopify

In this episode of the O’Reilly Programming Podcast, I talk all things Python with Aaron Maxwell, presenter of the live online training courses "Python: Beyond The Basics, and Python: The Next Level." He is also the author of the book "Powerful Python: The Most Impactful Patterns, Features and Development Strategies Modern Python Provides."

Aaron Maxwell on the Power of Python

In this week’s Design Podcast, I sit down with Cheryl Platz, senior designer at Microsoft for the Azure Portal and Marketplaces. We talk about the challenges of working on a top-secret design project, the research behind Amazon's Echo Look, the skills you need to start designing for voice, and how studying improv can make you a better designer.

Cheryl Platz on Designing the Amazon Echo Look

In this week’s Design Podcast, I sit down with John Whalen, chief experience officer at 10 Pearls, a digital development company focused on mobile and web apps, enterprise solutions, cyber security, big data, IoT,  and cloud and dev ops. We talk about the “six minds” that underlie each human experience, why it’s important for designers to understand brain science, and what people really look for in a voice assistant.

John Whalen on Using Brain Science in Design

In this episode of the O’Reilly Programming Podcast, I talk with Eric Freeman and Elisabeth Robson, presenters of the live online training course "Design Patterns Boot Camp," and co-authors (with Bert Bates and Kathy Sierra) of "Head First Design Patterns," among other books. They are also co-founders of WickedlySmart, an online learning company for software developers.

Eric Freeman and Elisabeth Robson on Design Patterns

In this podcast episode, I speak with Eliot Knudsen, data science lead at Tamr, a company that uses AI to integrate data across silos. Data integration is often a painstaking, highly manual process of matching fields and resolving entities, but new tools can work alongside human experts to discover patterns in data and make recommendations for automatically merging it.

Integrating Data with AI

In this week’s Design Podcast, I sit down with Julie Stanford, founder and principal of user experience agency Sliced Bread Design. We talk about how to get in the rapid experimentation mindset, the design thinking process, and how to get started with rapid experimentation at your company. Hint: start small.

Julie Stanford on Vetting Designs Through Rapid Experimentation

In this episode of the O’Reilly Programming Podcast, I talk with Jim Blandy and Jason Orendorff, both of Mozilla, where Blandy works on Firefox’s web developer tools and Orendorff is the module owner of Firefox’s JavaScript engine. They are the authors of the new O’Reilly book "Progamming Rust."

Jim Blandy and Jason Orendorff on Rust

In this episode of the Security Podcast, I talk with Andrea Limbago, chief social scientist at Endgame. We discuss how the misperception of security as a computer science skillset ultimately restricts innovation, the need to make security easier and accessible for everyone, and how current branding of security can discourage newcomers.

Andrea Limbago on the Effects of Security's Branding Problem

In this episode of the Security Podcast, I talk with Charles Givre, senior lead data scientist at Orbital Insight. We discuss how data science skills are increasingly important for security professionals, the critical role of data scientists in making the results of their work accessible to even nontechnical stakeholders, and using machine learning as a dynamic filter for vast amounts of data.

Charles Givre on the Impetus for Training All Security Teams in Basic Data Science

In this episode of the Security Podcast, O’Reilly’s Mac Slocum talks with Susan Sons, senior systems analyst for the Center for Applied Cybersecurity Research (CACR) at Indiana University. They discuss how she initially got involved with fixing the open source Network Time Protocol (NTP) project, recruiting and training new people to help maintain open source projects like NTP, and how security needn’t be an impediment to organizations moving quickly.

Susan Sons on Building Security from First Principles

In this episode of the Security Podcast, I talk with Christie Terrill, partner at Bishop Fox. We discuss the importance of educating businesses on the complexities of “being secure,” how to approach building a strong security program, and aligning security goals with the larger processes and goals of the business.

Christie Terrill on Building a High-Caliber Security Program in 90 Days

In this episode of the Security Podcast, I talk with Rich Smith, director of labs at Duo Labs, the research arm of Duo Security. We discuss the goals of agile application security, how to reframe success for security teams, and the short- and long-term implications of your security culture.

Rich Smith on Redefining Success for Security Teams and Managing Security Culture

In this episode of the O’Reilly Programming Podcast, I talk with Paul Bakker, senior software engineer on the edge developer experience team at Netflix, and Sander Mak, a fellow at Luminis Technologies. They are the authors of the O’Reilly book "Java 9 Modularity," in which they call the introduction of the module system to the platform “the start of a new era.”

Paul Bakker and Sander Mak on Java 9 Modularity

In this episode of the O’Reilly Programming Podcast, I talk with Richard Warburton and Raoul-Gabriel Urma of Iteratr Learning. They are the presenters of a series of O’Reilly Learning Paths, including "Getting Started with Reactive Programming" and "Build Reactive Applications in Java 8." Warburton is the author of "Java 8 Lambdas," and Urma is the author of "Java 8 in Action."

Richard Warburton and Raoul-Gabriel Urma on Java 8 and Reactive Programming

In this episode of the O’Reilly Programming Podcast, I talk about Jenkins 2 and Git with Brent Laster, who presents a number of live online training courses on these topics (including "Building a deployment pipeline with Jenkins 2," and "Next level Git"). Laster will also present the workshop "Power Git" at the O’Reilly Open Source Convention, July 16-19, 2018, in Portland, Oregon, and he is the author of the forthcoming O’Reilly book "Jenkins 2: Up and Running."

Brent Laster on Jenkins 2 and Git

In this episode of the O’Reilly Programming Podcast, I talk about Kubernetes, containers, and more with Bridget Kromhout, a principal cloud developer advocate at Microsoft, and a frequent speaker at tech conferences. She will be leading the workshop "Kubernetes 101" at the O’Reilly Velocity Conference in San Jose, June 11-14, 2018, and at the O’Reilly Open Source Convention (OSCON), July 16-19, 2018.

Bridget Kromhout on Kubernetes

In this episode of the O’Reilly Programming Podcast, I talk with two of the program chairs for the upcoming O’Reilly Fluent Conference (July 11-14 in San Jose), Kyle Simpson and Tammy Everts. Simpson is co-author of the "HTML 5 Cookbook," and the author of the "You Don’t Know JS" series of books. Everts is the chief experience officer at SpeedCurve and the author of "Time is Money: The Business Value of Web Performance."

Kyle Simpson and Tammy Everts on the Challenges of the Modern Web

In this episode of the O’Reilly Media Podcast, I talk with JP Phillips, platform engineer at IBM Cloud. IBM is driving development in the container space, as shown through last year’s launch of Istio, an open cloud service that allows developers to connect, manage, and secure networks of different microservices. Istio, a joint collaboration between IBM, Google, and Lyft, (in conjunction with the Cloud Native Computing Foundation), is platform agnostic and runs on Kubernetes platforms, such as IBM’s Cloud Container Service. Interest in the platform is growing. IBM's Daniel Berg, who is giving a talk on Istio at the upcoming OSCON conference in Portland, recently led a hands-on workshop at KubeCon in Copenhagen to help developers learn how Istio can solve common challenges with microservices deployed within Kubernetes.

Kubernetes and Containers for Enterprise Developers

In a recent episode of the O’Reilly Media Podcast, we spoke with George Miranda about the importance of service mesh technology in creating reliable distributed systems. As discussed in the new report The Service Mesh: Resilient Service-to-Service Communication for Cloud Applications, service mesh technology has emerged as a popular tool for companies looking to build cloud-native applications that are reliable and secure.

During the podcast, we discussed the problems a service mesh infrastructure solves and the service mesh features you’ll find most valuable. We also talked about how to choose the right service mesh for your organization, the challenges involved in getting it deployed to production, and the best ways for getting started with a service mesh.

How to Choose and Deploy a Service Mesh

In this episode of the O’Reilly Media Podcast, Rachel Roumeliotis, VP of content strategy at O’Reilly, sat down with Daniel Krook, IBM developer advocate. They discussed how developers across industries can participate in the Call for Code initiative, the benefits of the program, support from its charitable partners—United Nations Human Rights and the American Red Cross—and the positive impacts IBM hopes to achieve by investing in Call for Code.

Developers Worldwide Will Collaborate on Solutions to Save Lives in Call For Code

This episode of the O’Reilly Podcast, features a conversation on serverless and Kubernetes, with Kelsey Hightower, developer advocate for Google Cloud Platform at Google (and co-author of "Kubernetes: Up and Running"), and Chris Gaun, Kubernetes product marketing manager at Mesosphere.

Kelsey Hightower and Chris Gaun on Serverless and Kubernetes

At Google’s 2019 Cloud Next conference, I sat down with Stephen Thorne, site reliability engineer on Google’s customer reliability engineering team and co-author of "The Site Reliability Workbook," to talk about how organizations, both large and small, can use SRE to reduce operational costs, improve reliability, and create productive cross-functional teams.

How to Get Started With Site Reliability Engineering (SRE)

In this episode of the Data Show, I spoke with Nick Pentreath, principal engineer at IBM. Pentreath was an early and avid user of Apache Spark, and he subsequently became a Spark committer and PMC member. Most recently his focus has been on machine learning, particularly deep learning, and he is part of a group within IBM focused on building open source tools that enable end-to-end machine learning pipelines.

Enabling End-to-End Machine Learning Pipelines in Real-World Applications

In this week's episode of the Data Show, we're featuring an interview Data Show host Ben Lorica participated in for the Software Engineering Daily Podcast, where he was interviewed by Jeff Meyerson. Their conversation mainly centered around data engineering, data architecture and infrastructure, and machine learning (ML).

Tools for Machine Learning Development

In this episode of the Data Show, I spoke with Roger Chen, co-founder and CEO of Computable Labs, a startup focused on building tools for the creation of data networks and data exchanges. Chen has also served as co-chair of O'Reilly's Artificial Intelligence Conference since its inception in 2016. This conversation took place the day after Chen and his collaborators released an interesting new white paper, "Fair value and decentralized governance of data." Current-generation AI and machine learning technologies rely on large amounts of data, and to the extent they can use their large user bases to create “data silos,” large companies in large countries (like the U.S. and China) enjoy a competitive advantage. With that said, we are awash in articles about the dangers posed by these data silos. Privacy and security, disinformation, bias, and a lack of transparency and control are just some of the issues that have plagued the perceived owners of “data monopolies.”

Acquiring and Sharing High-Quality Data

In this episode of the Data Show, I speak with Cassie Kozyrkov, technical director and chief decision scientist at Google Cloud. She describes "decision intelligence" as an interdisciplinary field concerned with all aspects of decision-making, and which combines data science with the behavioral sciences. Most recently she has been focused on developing best practices that can help practitioners make safe, effective use of AI and data. Kozyrkov uses her platform to help data scientists develop skills that will enable them to connect data and AI with their organizations' core businesses.

We had a great conversation spanning many topics, including:

How data science can be more useful

The importance of the human side of data

The leadership talent shortage in data science

Is data science a bubble?

Make Data Science More Useful

In this interview, Tim Craig and fellow Googler Gustavo Franco, a site reliability engineer (SRE), discuss the wide range of events that qualify as “incidents;” the need for a conscious, robust, and well-defined process for understanding them; the role of training; and how to get buy-in from management so you can spread incident response training throughout an organization.

Taming Chaos: Preparing for Your Next Incident

In this episode of the Data Show, I speak with Alex Ratner, project lead for Stanford’s Snorkel open source project; Ratner also recently garnered a faculty position at the University of Washington and is currently working on a company supporting and extending the Snorkel project. Snorkel is a framework for building and managing training data. Based on our survey from earlier this year, labeled data remains a key bottleneck for organizations building machine learning applications and services.

Ratner was a guest on the podcast a little over two years ago when Snorkel was a relatively new project. Since then, Snorkel has added more features, expanded into computer vision use cases, and now boasts many users, including Google, Intel, IBM, and other organizations. Along with his thesis advisor professor Chris Ré of Stanford, Ratner and his collaborators have long championed the importance of building tools aimed squarely at helping teams build and manage training data. With today’s release of Snorkel version 0.9, we are a step closer to having a framework that enables the programmatic creation of training data sets.

Labeling, Transforming, and Structuring Training Data Sets for Machine Learning

In this episode of the Data Show, I speak with Kesha Williams, technical instructor at A Cloud Guru, a training company focused on cloud computing. As a full stack web developer, Williams became intrigued by machine learning and started teaching herself the ML tools on Amazon Web Services. Fast forward to today, Williams has built some well-regarded Alexa skills, mastered ML services on AWS, and has now firmly added machine learning to her developer toolkit.

Becoming a Machine Learning Practitioner

In this episode of the Data Show, I speak with Michael Mahoney, a member of RISELab, the International Computer Science Institute, and the Department of Statistics at UC Berkeley. A physicist by training, Mahoney has been at the forefront of many important problems in large-scale data analysis. On the theoretical side, his works spans algorithmic and statistical methods for matrices, graphs, regression, optimization, and related problems. On the applications side, he has contributed to systems used for internet and social media analysis, social network analysis, as well as for a host of applications in the physical and life sciences. Most recently, he has been working on deep neural networks, specifically developing theoretical methods and practical diagnostic tools that should be helpful to practitioners who use deep learning.

Understanding Deep Neural Networks

In this episode of the Data Show, I speak with Arun Kejariwal of Facebook and Ira Cohen of Anodot (full disclosure: I’m an advisor to Anodot). This conversation stemmed from a recent online panel discussion we did, where we discussed time series data, and, specifically, anomaly detection and forecasting. Both Kejariwal (at Machine Zone, Twitter, and Facebook) and Cohen (at HP and Anodot) have extensive experience building analytic and machine learning solutions at large scale, and both have worked extensively with time-series data. The growing interest in AI and machine learning has not been confined to computer vision, speech technologies, or text. In the enterprise, there is strong interest in using similar automation tools for temporal data and time series.

Machine Learning and Analytics for Time Series Data

In this episode of the Data Show, I speak with Peter Bailis, founder and CEO of Sisu, a startup that is using machine learning to improve operational analytics. Bailis is also an assistant professor of computer science at Stanford University, where he conducts research into data-intensive systems and where he is co-founder of the DAWN Lab.

Machine Learning for Operational Analytics and Business Intelligence

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.

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