The O’Reilly Data Show Podcast: Andrew Burt and Steven Touw on how companies can manage models they cannot fully explain.
Chinese Internet, Booting Linux, Pull Requests, and Commercialized Commons
We need to build organizations that are self-critical and avoid corporate self-deception.
Open Source, Milspec Origami, Machine Says No, and Golang
Product Feedback, Medical AI, DensePose, and Automating Debugging
Innovation Stack, Fundraising, Diversity and Fans, and APIs to MySQL Data
Pose Estimation, Data Ethics, Interactive Explanation, and Serverless Tool
Dave Andrews explains how to wield the power of a global 50 Tbps application delivery network to ensure maximum availability during and after a change.
David Hayes explains why adding a manageable dose of actionable intelligence to your operations management workflow can save you time and aggravation.
Focusing on a mix of artificial, scientific, and environmental sensing data, Aurelia Moser explores fantasy and farcical mapping.
Julia Grace shares how she learned to rapidly scale herself and her leadership team during a period of hypergrowth at Slack.
Kyle Kingsbury explores anomalies in three distributed systems and shares strategies for correctness testing using Jepsen.
Nicole Forsgren shares results and stories behind high-performing technology-driven teams and organizations.
Tracy Lee helps you think differently about how to increase diversity in technology with open source.
Bryan Liles explains how to evaluate and integrate new declarative application management practices into continuous integration pipelines.
Oracle's Kyle York and Netra's Richard Lee discuss Netra’s high-performance computing environment.
Brendan Eich asks what it would mean to the web if we start building products, apps, and systems that are private by default.
Historic Handwriting Recognition, Proving Security, Formal Methods, and Dank Memes
Tamar Bercovici details how the team at Box has constructed its database stack to handle an ever-growing query load and data set.
Renee Orser explains how to monitor the human networks within your engineering teams using models similar to your distributed technology systems.
Watch highlights covering infrastructure, DevOps, security, and more. From the O'Reilly Velocity Conference in San Jose 2018.
Cherie Wong shares common developer pain points and recipes to solve them using AWS.
Cory Doctorow fields questions on the future of the web, privacy, and net neutrality.
Martin Woodward shares key data points from Microsoft's journey to DevOps.
Kyle York explores the scale, complexity, and volatility of the internet and the risk it poses to your applications and infrastructure.
Natalie Silvanovich discusses the link between feature complexity, developer error, and security vulnerabilities.
Lin Clark explains what browser vendors need to do over the next few years to ensure their browsers, and the web itself, meet upcoming demands.
Javier Garza details the ingredients you need to build and deliver an app your users will love.
Kris Nova looks at the four metrics that help you decide if running stateful applications in Kubernetes is worth the risk.
Scott Davis explains why accessibility should be just as important to you as a mobile design strategy was 10 years ago.
Astrid Atkinson discusses techniques for building systems that are resilient by design.
Cory Doctorow says the right to configure technology is the signature right of the 21st century.
Security Papers, Science AI, Deliberation, and Doing Science
A look at a few ways to evaluate whether or not a design achieves what it set out to do.
Practical advice for software engineers and security consultants.
The benefits of modeling data as events as a mechanism to evolve our software systems.
Taking blockchain technology private for the enterprise.
How to identify when a fit has been achieved, and how to exit the explore stage and start exploiting a product with its identified market.
Text2Binary, GraphQL, USB, and Debugging
An overview of common design patterns for navigation that will ensure users can find and use features in an application.
An overview and framework, including tools that can be used to enable automation.
Tiny Machine Learning, Deep Video, Software 2.0, and Smart Camera
Representative Recognition, Cyberwar, Data Science Projects, and Conversational Failure
The O’Reilly Data Show Podcast: Ashok Srivastava on the emergence of machine learning and AI for enterprise applications.
Algorithmic Accountability, Killing Project Maven, AI Scares Past, and Submarine Data Center
Find new ways to gain insight into how your users interact.
Cast your vote for the top open source projects and communities through June 29.
Use cases of AI and ML to help businesses build better defenses today and in the near future.
Future Analytics, Personal Data, Wireless Power, Counterintuitive Probability
Get hands-on training in machine learning, Python, Java, Kubernetes, product management, and many other topics.
This collection of AI resources will get you up to speed on the basics, best practices, and latest techniques.
The O’Reilly Podcast: Tammy Butow and Annie Lau on the importance of creating a culture of learning.
Reinforcement Learning Notebooks, Music Translation, Service Fabric, and Nat Friedman
Why model development does not equal software development.
Considerations based on experience with Fortune 500 clients.
Infinite Walking, Security Class, Collaborative Data Structures, and Brain Class