When it comes to automation of existing tasks and workflows, you need not adopt an “all or nothing” attitude.
The O’Reilly Data Show Podcast: Alex Wong on building human-in-the-loop automation solutions for enterprise machine learning.
Can We Stop?, Everything Breaks, Edge Cloud, and Molly Guard
Get a basic understanding of distributed systems and then go deeper with recommended resources.
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The O’Reilly Data Show Podcast: Vitaly Gordon on the rise of automation tools in data science.
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Considerations for a world where ML models are becoming mission critical.
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Understanding how the Kubernetes scheduler makes scheduling decisions is critical to ensure consistent performance and optimal resource utilization.
Claire Janisch looks at some of the best biomimicry opportunities inspired by nature’s software and wetware.
Jane Adams examines the ways data-driven recruiting fails to achieve intended results and perpetuates discriminatory hiring practices.
Kris Nova looks at the new era of the cloud native space and the kernel that has made it all possible: Kubernetes.
Martin Kleppmann shows how recent computer science research is helping develop the abstractions and APIs for the next generation of applications.
Katrina Owen says the valuable skills that experienced professionals lack are at the vital margins of their careers.
Omoju Miller outlines a vision where we harness human action for a better future.
Crystal Hirschorn discusses how organizations can benefit from combining established tech practices with incident planning, post-mortem-driven development, chaos engineering, and observability.
Watch highlights from expert talks covering Kubernetes, chaos engineering, deep learning, and more.
Anne Currie says excessive and dirty energy use in data centers is one of the biggest ethical issues facing the tech industry.
Mike Roberts explores ideas for trying serverless as well as a framework for evaluating its effectiveness within your organization.
Trisha Gee shares advice and lessons she learned the hard way while managing her career as a developer, lead, and technical advocate.
Stefan Tilkov looks at common software architecture pitfalls and explains how they can be avoided.
Sarah Wells explains how the Financial Times migrated microservices between container stacks without affecting production users.
Liz Rice outlines the security implications of microservices, containers, and serverless.
Chris Richardson describes microservices anti-patterns he’s observed while working with clients around the world.
Watch highlights from expert talks covering microservices, Kubernetes, serverless, and more.
The O’Reilly Data Show Podcast: Alon Kaufman on the interplay between machine learning, encryption, and security.
As lists are the raw material of strategy and technology architecture, MECE list-making is one of the most useful tools you can have in your tool box.
A look at the roles of architect and strategist, and how they help develop successful technology strategies for business.
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O’Reilly’s new survey reveals the latest operations salary trends, and the skill sets that will keep your operations career on track.
Create a coherent BI strategy that aligns data collection and analytics with the general business strategy.
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Supasorn Suwajanakorn discusses the possibilities and the dark side of building artificial people.
Kristian Hammond maps out simple rules, useful metrics, and where AI should live in the org chart.
Cassie Kozyrkov shares machine learning lessons learned at Google and explains what they mean for applied data science.
Marc Warner and Louis Barson discuss the internal and external uses of AI in the UK government.
Drawing on the McKinsey Global Institute’s research, Michael Chui explores commonly asked questions about AI and its impact on work.
Jason Knight offers an overview of the state of the field for scaling training and inference across distributed systems.
The O’Reilly Data Show Podcast: Jacob Ward on the interplay between psychology, decision-making, and AI systems.
Watch highlights from expert talks covering artificial intelligence, machine learning, automation, and more.
Jonathan Ballon explains why Intel’s AI and computer vision edge technology will drive advances in machine learning and natural language processing.
Ian Massingham discusses the application of ML and AI within Amazon, from retail product recommendations to the latest in natural language understanding.
Ben Lorica and Roger Chen highlight recent trends in data, compute, and machine learning.
Ashok Srivastava draws upon his cross-industry experience to paint an encouraging picture of how AI can solve big problems.
Ruchir Puri explains why trust and transparency are essential to AI adoption.
Yangqing Jia talks about what makes AI software unique and its connections to conventional computer science wisdom.
Amy Heineike explains how Primer created a self-updating knowledge base that can track factual claims in unstructured text.
Our bad AI could be the best tool we have for understanding how to be better people.
A new report examines the state of infrastructure and anticipated near-term developments through the eyes of infrastructure experts.
Roger Magoulas shares insights from O'Reilly's online learning platform that point toward shifts in the systems engineering ecosystem.
Jaana Dogan explains why Google teaches its tracing tools to new employees and how it helps them learn about Google-scale systems end to end.
Laura Thomson shares Mozilla’s approach to data ethics, review, and stewardship.
Michael Bernstein offers an unflinching look at some of the fallacies that developers believe about marketing.
Tammy Butow explains how companies can use Chaos Days to focus on controlled chaos engineering.
Practical techniques to ensure developers can actually do the things you want them to do using your API.
Kris Beevers examines the trade-offs between risk and velocity faced by any high-growth, critical path technology business.
Dave Rensin explains why DevOps and SRE make each other better.
Francesc Campoy Flores explores ways machine learning can help developers be more efficient.
Laurent Gil shares the latest cybersecurity research findings based on real-world security operations.
Kavya Joshi says performance theory offers a rigorous and practical approach to performance tuning and capacity planning.
Anil Dash asks: How could our processes and tools be designed to undo the biggest bugs and biases of today’s tech?