Lessons on building data products at Google
Aparna Chennapragada discusses Google's process for developing data products.
Aparna Chennapragada discusses Google's process for developing data products.
Naveen Rao outlines deep learning challenges and explores how changes to the organization of computation and communication can lead to advances in capabilities.
Rana El Kaliouby explores why emotion in AI is critical to accelerating adoption of AI systems.
Microsoft's Fuzzer, Fed Game, MadLibs Machine, and Secure Time
Tim O’Reilly explains why we can’t just use technology to replace people; we must use it to augment them so they can do things that were previously impossible.
Building reliable, robust software is hard. It is even harder when we move from deterministic domains, such as balancing a checkbook, to uncertain domains, such as recognizing speech or objects in an image.
Lili Cheng discusses the human aspects of artificial intelligence.
Shahin Farshchi examines role artificial intelligence will play in driverless cars.
Genevieve Bell explores the meaning of “intelligence” within the context of machines and its cultural impact on humans and their relationships.
Linking Records, Encrypted Editing, Neural Photo Editing, and Self-Care Resources
Use smart pointers and move semantics to supercharge your C++ code base.
On Reproducibility, Robot Monkey Startup, Stealing Predictive Models, and GPU Equivalence
The anatomy of an architecture to bring data science into production.
The O’Reilly Bots Podcast: A look at some of the technologies behind the chatbot boom.
Ops Papers, Moral Tests, Self-Powered Computing Materials, and Self-Driving Regulation
Simple Text Processing, Future Work Strategies, Chatbot Errors, and Formal Verification
Aligning Incentives, Git Recovery, Google's Public Service, and Quadruped Robots
Visualizing Circuits, Working on Climate Change, Cashless Challenges, Architecture & Politics