Drawing on 13 years spent building the Chef community, Adam Jacob takes a deep dive into the soul of open source.
Pete Skomoroch covers what you need to know as we shift from a world of deterministic programs to systems that give unpredictable results on ever-changing training data.
The O’Reilly Data Show Podcast: Roger Chen on the fair value and decentralized governance of data.
Weird Algorithms, Open Syllabi, Conversational AI, and Quantum Computing
Kay Williams explores key lessons for building strong open source communities based on Microsoft’s real-world experience with Kubernetes and VSCode.
Tiffani Bell shares three lessons she's learned exploring how technology can help the less fortunate.
Experts explore the role open source software plays in fields as varied as machine learning, blockchain, disaster response, and more.
Arun Gupta discusses the reasons why AWS is committed to open projects and communities.
Pedro Cruz and Brad Topol discuss Call for Code, a global developer competition that uses open source technologies to address natural disasters.
Alison McCauley looks at how blockchain technology offers new tools that can help extend the ethos of open innovation into new areas.
Margaret Hamilton, WeChat Censorship, Refactoring, and Ancient Games
Quantum TiqTaqToe, Social Media and Depression, Incidents, and Unity ML
A look at how guidelines from regulated industries can help shape your ML strategy.
Climbing Robot, Programming and Programming Languages, Media Player, and Burnout Shops
Hosting Hate, Releasing, Government Innovation, and Voice Cloning
Museum Copyright, Twitter Apprenticeship, AI Regulation, and Computational Biology
Optimizations and Security, 512 Byte Pac-Man, Cell Security, and Meme AI
Future of Work, GRANDstack, Hilarious Law Review Article, and The Platform Excuse
We shouldn't ask our AI tools to be fair; instead, we should ask them to be less unfair and be willing to iterate until we see improvement.
Experts explore the future of hiring, AI breakthroughs, embedded machine learning, and more.
Abigail Hing Wen discusses some of the most exciting recent breakthroughs in AI and robotics.
Pete Warden digs into why embedded machine learning is so important, how to implement it on existing chips, and shares new use cases it will unlock.
Ion Stoica outlines a few projects at the intersection of AI and systems that UC Berkeley's RISELab is developing.
Tim Kraska outlines ways to build learned algorithms and data structures to achieve “instance optimality” and unprecedented performance for a wide range of applications.
Michael James examines the fundamental drivers of computer technology and surveys the landscape of AI hardware solutions.
Haoyuan Li offers an overview of a data orchestration layer that provides a unified data access and caching layer for single cloud, hybrid, and multicloud deployments.
Maria Zheng examines AI and its impact on people’s jobs, quality of work, and overall business outcomes.
Mikio Braun takes a look at Zalando and the retail industry to explore how AI is redefining the way ecommerce sites interact with customers.
Algorithmic Governance, DevOps Assessment, Retro Language, and Open Source Satellite
Online Not All Bad, Emotional Space, Ted Chiang, Thread Summaries
Debugging AI, Serverless Foundations, YouTube Bans, and Pathological UI
The O'Reilly Data Show: Ben Lorica chats with Jeff Meyerson of Software Engineering Daily about data engineering, data architecture and infrastructure, and machine learning.
Models, More Models, Robots.txt, and Event Sourcing
Lock Convoys, AI Hardware, Lambda Observability, and AI for Science
General-Purpose Probabilistic Programming, Microsoft's Linux, Decolonizing Data, Testing Statistical Softwares
Neural-backed generators are a promising step toward practical program synthesis.
Heartbeat Identity, Seam Carving, Q&A Facilitation, and Secure Data in Distributed Systems
As we close in on its two-year anniversary, Spark NLP is proving itself a viable option for enterprise use.
Security Mnemonics, Evidence Might Work, Misinformation Inoculation, and Spoofing Presidential Alerts
Ethics and OKRs, Rewriting Binaries, Diversity of Implementation, and Uber's Metrics Systems
To successfully integrate AI and machine learning technologies, companies need to take a more holistic approach toward training their workforce.
Analog Deep Learning, Low-Trust Internet, Media Literacy, and Psych Experiments
Wacky Timestamps, Computers and Spies, Surveillance Capitalism, and Twitter Adventures
Private Computation, Robot Framework, 3D Objects, and Self-Supervised Learning
Model Governance, Content Moderators, Interactive Fiction, and End-User Probabilistic Programming
The O’Reilly Data Show Podcast: Nick Pentreath on overcoming challenges in productionizing machine learning models.
Voice2Face, DIY Minivac, Cloud Metrics, and Envoy for Mobile
A look at the landscape of tools for building and deploying robust, production-ready machine learning models.
Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge.
Multiverse Databases, Detecting Photoshopping, Simulation Platform, and Tail-Call Optimization: The Musical
Michael Feathers explores various scaling strategies in light of research about human cognition and systems cohesion.
Rebecca Parsons shares the story of her career path and her work as an architect.
Adam Tornhill offers a new perspective on software development that will change how you view code.
Information Operations, Game Creator, History Lessons, and Physical Pen Testing
Bob Quillin outlines how the cloud native community can reduce complexity, be more inclusive to all teams, and create a more open, multicloud future.
Drawing inspiration from restorative justice practices and her own journey of healing, Alex Qin offers a hopeful vision for how we can come together and co-create the world we yearn for.
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.
Liz Fong-Jones says management of complex distributed systems requires changing who's involved in production, how they collaborate, and how success is measured.
Bridget Kromhout looks over the cloud native landscape and talks about what’s new, what’s next, and what you need to get started with Kubernetes right now.