Liz Fong-Jones says management of complex distributed systems requires changing who's involved in production, how they collaborate, and how success is measured.
Drawing from technology, finance, sports, social psychology, and complexity theory, Everett Harper looks at the key practices that are crucial for solving our most critical challenges.
Experts explore software architecture security, design heuristics, Next Architecture, and more.
Chris Guzikowski discusses the convergence of microservices, cloud, containers, and orchestration that points toward the rise of a Next Architecture.
Michael Carducci takes an entertaining look at why humans are so easy to fool, and he explores what we can do to overcome our weaknesses and build more secure software.
Rebecca Wirfs-Brock explores how you can grow as a designer by becoming conscious of your heuristics.
Nathaniel Schutta explains why an architect’s job is to be a storyteller.
Experts explore cloud native infrastructure, SRE, distributed systems, and more.
Modern distributed systems are immensely different from distributed systems of just a decade ago. Lena Hall looks at how our approaches and practices progress with time.
Jessica Kerr argues that most programming careers aren’t about writing software, they’re about changing it.
Lachlan Evenson and Bridget Kromhout discuss the journey to build Gatekeeper, a community-driven approach for enforcing policy on any Kubernetes cluster.
Chen Goldberg shares how Kubernetes, Istio, GKE, and Anthos can help build distributed systems and happy teams.
Yaniv Aknin dives into the secret sauce for a successful SRE organization: high-quality measurements of reliability.
We now are in the implementation phase for AI technologies.
Google SRE Stephen Thorne shares best practices for starting an SRE team at your company.
We won’t get the chance to worry about artificial general intelligence if we don’t deal with the problems we have in the present.
The O’Reilly Data Show Podcast: Dhruba Borthakur and Shruti Bhat on enabling interactive analytics and data applications against live data.
Cloud native, AI/ML, and data tools and topics are areas of emphasis for the O’Reilly Open Source Software Conference.
How SREs can use a hierarchy for mature alerts.
The O’Reilly Data Show Podcast: Jike Chong on the many exciting opportunities for data professionals in the U.S. and China.
Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms.
Microservices, serverless, AI, ML, and Kubernetes are among the most notable topics in our analysis of proposals from the O’Reilly Software Architecture Conference.
From data quality to personalization, to customer acquisition and retention, and beyond, AI and ML will shape the customer experience of the future.
Breaking up Facebook won't solve the disinformation or privacy problems. It might well make it harder for Facebook to work on those problems.
Programmers have built great tools for others. It’s time they built some for themselves.
The O’Reilly Data Show Podcast: Jeff Jonas on the evolution of entity resolution technologies.
David Boyle shares lessons on how analysts can harness data and creativity to build partnerships.
Mike Tidmarsh looks at how data and AI are radically reshaping the world of marketing communications.
Sandra Wachter argues that a right to reasonable inferences could protect against new forms of discrimination.
Shingai Manjengwa shares insights from teaching data science to 300,000 online learners.
Chris Taggart explains the benefits of “white box data” and outlines the structural shifts that are moving the data world toward this model.
Watch highlights from expert talks covering machine learning, predictive analytics, data regulation, and more.
Cassie Kozyrkov explains how organizations can extract more value from their data.
Cait O’Riordan discusses the North Star metric the Financial Times uses across the organization to drive subscriber growth.
James Burke asks if we can use data and predictive analytics to take the guesswork out of prediction.
Mick Hollison describes why hybrid and multi-cloud is the future for organizations that want to capitalize on machine learning and AI.
Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning.
More than anything else, O'Reilly's AI Conference was about making the leap to AI 2.0.
Survey results reveal the path organizations face as they integrate cloud native infrastructure and harness the full power of the cloud.
The O’Reilly Data Show Podcast: Neelesh Salian on data lineage, data governance, and evolving data platforms.
Resolving the volatility problem will unlock the groundwork needed for blockchain-based global payment systems.
Ruchir Puri discusses the next revolution in automating AI, which strives to deploy AI to automate the task of building, deploying, and managing AI tasks.
Sean Gourley considers the repercussions of AI-generated content that blurs the line between what's real and what's fake.
Christopher Ré discusses Snorkel, a system for fast training data creation.
How can machine learning decode the mysteries of life? Olga Troyanskaya explores this and other big questions through the prism of deep learning.
Kim Hazelwood discusses the hardware and software Facebook has designed to meet its scale needs.
Rajendra Prasad explains how leaders in large enterprises can make AI adoption successful.
Nick Curcuru explains how Mastercard is using AI to improve security without sacrificing the customer experience.
Carlos Humberto Morales offers an overview of Nauta, an open source multiuser platform that lets data scientists run complex deep learning models on shared hardware.
Thomas Henson considers how AI will shape the experiences of future generations.
Ben Lorica and Roger Chen assess the state of AI technologies and adoption in 2019.
Kurt Muehmel explores AI within a broader discussion of the ethics of technology, arguing that inclusivity and collaboration are necessary.
Gadi Singer discusses the major questions organizations confront as they integrate deep learning.
Watch highlights from expert talks covering AI, machine learning, deep learning, ethics, and more.
Tony Jebara explains how Netflix is personalizing and optimizing the images shown to subscribers.
Aleksander Madry discusses roadblocks preventing AI from having a broad impact and approaches for addressing these issues.
Danielle Dean explains how cloud, data, and AI came together to help build Automated ML.
Martial Hebert offers an overview of challenges in AI for robotics and a glimpse at the exciting developments emerging from current research.
Joleen Liang explains how AI and precise knowledge points can help students learn.
Balancing risk and reward is a necessary tension we'll need to understand as we continue our journey into the age of data.