Y2K and other disappointing disasters
How risk reduction makes sure bad things happen as rarely as possible.
What's on our radar.
How risk reduction makes sure bad things happen as rarely as possible.
The O’Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness.
Apple MDM, Source Explorer, Verification-Aware Programming, and Superstar Economics
The World Economic Forum’s 2018 jobs report limits research to a narrow range of the workforce.
Getting DataOps right is crucial to your late-stage big data projects.
How we can put privacy at the heart of our design processes.
Using advanced Docker Compose features to solve problems in larger projects and teams.
The economy we want to build must recognize increasing the value to and for humans as the goal.
Exploring use cases for the two tools.
Asking good design questions will elucidate problems and opportunities.
Ziya Ma discusses how recent innovations from Intel in high-capacity persistent memory and open source software are accelerating production-scale deployments.
Amanda Pustilnik highlights potential applications of data from new technologies that capture brain-based processes.
Jacob Ward reveals the relationship between the unconscious habits of our minds and the way that AI is poised to amplify them, alter them, maybe even reprogram them.
Chad Jennings explains how Geotab's smart city application helps city planners understand traffic and predict locations of unsafe driving.
Julia Angwin discusses what she's learned about forgiveness from her series of articles on algorithmic accountability and the lessons we all need to learn for the coming AI future.
Hilary Mason explores the current state of AI and ML and what’s coming next in applied ML.
Amber Case covers methods product designers and managers can use to improve interactions through an understanding of sound design.
Ben Sharma shares how the best organizations immunize themselves against the plague of static data and rigid process
Dinesh Nirmal explains how AI is helping supply school lunch and keep ahead of regulations.
We should invest at least as much time in understanding our customers as we do in optimizing our product development process.
The O’Reilly Data Show Podcast: Alan Nichol on building a suite of open source tools for chatbot developers.
Ted Dunning discusses how new tools can change the way production systems work.
Cassie Kozyrkov explores why businesses fail at machine learning despite its tremendous potential and excitement.
DD Dasgupta explores the edge-cloud continuum, explaining how the roles of data centers and cloud infrastructure are redefined through the mainstream adoption of AI, ML, and IoT technologies.
Ben Lorica offers an overview of recent tools for building privacy-preserving and secure machine learning products and services.
Drew Paroski and Aatif Din share how to develop modern database applications without sacrificing cost savings, data familiarity, and flexibility.
Executives from Cloudera and PNC Bank look at the challenges posed by data-hungry organizations.
Watch highlights from expert talks covering data science, machine learning, algorithmic accountability, and more.
Joseph Lubin explains how Ethereum can help with new innovations like cryptocurrencies, automated and self-executing legal agreements, and self-sovereign identity.
Poll results reveal where and why organizations choose to use containers, cloud platforms, and data pipelines.
It has become much more feasible to run high-performance data platforms directly inside Kubernetes.
If we’re going to think about the ethics of data and how it’s used, then we have to take into account how data flows.
Dawn Song explains how AI and deep learning can enable better security and how security can enable better AI.
Manish Goyal shows you how to best unlock the value of enterprise AI.
Huma Abidi discusses the importance of optimization to deep learning frameworks.
David Patterson explains why he expects an outpouring of co-designed ML-specific chips and supercomputers.
Joseph Sirosh tells an intriguing story about AI-infused prosthetics that are able to see, grip, and feel.
Peter Norvig says one of the most exciting aspects of AI is the diversity of applications in fields far astray from the original breakthrough areas.
Hagay Lupesko explores key trends in machine learning, the importance of designing models for scale, and the impact that machine learning innovation has had on startups and enterprises alike.
Levent Besik explains how enterprises can stay ahead of the game with customized machine learning.
From chaos architecture to event streaming to leading teams, the O'Reilly Software Architecture Conference offers a unique depth and breadth of content.
Akhilesh Tripathi shows you how to use machine learning to identify root causes of problems in minutes instead of hours or days.
Julie Shin Choi reviews real-world customer use cases that take AI from theory to reality.
Kishore Durg explains why deploying AI requires raising it to act as a responsible representative of the business and a contributing member of society.
Tim O'Reilly and Kai-Fu Lee discuss differences in how China and the U.S. approach AI and why AI might give humanity larger purpose.
Kai-Fu Lee outlines the factors that enabled China's rapid ascension in AI.
Meredith Whittaker says the benefits of AI will only come if we have a clear-eyed perspective on its dark side.
Watch highlights from expert talks covering artificial intelligence, machine learning, security, and more.
Soups Ranjan describes the machine learning system that Coinbase built to detect potential fraud and fake identities.
A new survey highlights concerns from network and cloud administrators, and reveals their coping strategies.
This collection of data governance resources will get you up to speed on the basics and best practices.
Get hands-on training in machine learning, blockchain, Java, software architecture, leadership, and many other topics.
Data can help inform design choices at every step in the process.
The O’Reilly Data Show Podcast: Eric Jonas on Pywren, scientific computation, and machine learning.
The O’Reilly Media Podcast: Daniel Krook, IBM developer advocate, on the Call for Code Global Initiative at IBM.
Tools and techniques for recruiting UX research participants.
How the UK's NHS uses prototyping to explore and illustrate new technological possibilities.
Fernando Perez talks about UC Berkeley's transition into an environment where many undergraduates use Jupyter and the open data ecosystem as naturally as they use email.
Michelle Ufford shares how Netflix leverages notebooks today and describes a brief vision for the future.
Michelle Gill discusses how data science methods and tools can link information from different scientific fields and accelerate discovery.
Tracy Teal explains how to bring people to data and empower them to address their questions.
Cristian Capdevila explains how Prognos is predicting disease.
David Schaaf explains how data science and data engineering can work together to deliver results to decision makers.