The state of automation technologies
Ben Lorica and Roger Chen highlight recent trends in data, compute, and machine learning.
AI & ML
Few technologies have the potential to change the nature of work and how we live as artificial intelligence (AI) and machine learning (ML).
Why we built a self-writing Wikipedia
Amy Heineike explains how Primer created a self-updating knowledge base that can track factual claims in unstructured text.
AI for a better world
Ashok Srivastava draws upon his cross-industry experience to paint an encouraging picture of how AI can solve big problems.
What we learn from AI’s biases
Our bad AI could be the best tool we have for understanding how to be better people.
ML on code: Machine learning will change programming
Francesc Campoy Flores explores ways machine learning can help developers be more efficient.
Why it’s hard to design fair machine learning models
The O’Reilly Data Show Podcast: Sharad Goel and Sam Corbett-Davies on the limitations of popular mathematical formalizations of fairness.
Practical ML today and tomorrow
Hilary Mason explores the current state of AI and ML and what’s coming next in applied ML.
Black box: How AI will amplify the best and worst of humanity
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.
Using machine learning to improve dialog flow in conversational applications
The O’Reilly Data Show Podcast: Alan Nichol on building a suite of open source tools for chatbot developers.
Highlights from the Strata Data Conference in New York 2018
Watch highlights from expert talks covering data science, machine learning, algorithmic accountability, and more.
Preserving privacy and security in machine learning
Ben Lorica offers an overview of recent tools for building privacy-preserving and secure machine learning products and services.
The ethics of data flow
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.
Machine learning in the cloud
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.
Accelerating AI on Xeon through SW optimization
Huma Abidi discusses the importance of optimization to deep learning frameworks.
AI and security: Lessons, challenges, and future directions
Dawn Song explains how AI and deep learning can enable better security and how security can enable better AI.
The breadth of AI applications: The ongoing expansion
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.
A new golden age for computer architecture
David Patterson explains why he expects an outpouring of co-designed ML-specific chips and supercomputers.
Beyond hype: AI in the real world
Julie Shin Choi reviews real-world customer use cases that take AI from theory to reality.
AI foundations: What shapes the AI that’s shaping our world?
Meredith Whittaker says the benefits of AI will only come if we have a clear-eyed perspective on its dark side.
OpenAI and the path toward safe AGI
Greg Brockman discusses OpenAI's recent advancements and their implications for how we should plan for creating safe artificial general intelligence (AGI).
China: AI superpower
Kai-Fu Lee outlines the factors that enabled China's rapid ascension in AI.
Fireside chat with Tim O’Reilly and Kai-Fu Lee
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.
Highlights from the Artificial Intelligence Conference in San Francisco 2018
Watch highlights from expert talks covering artificial intelligence, machine learning, security, and more.
Unlocking innovation in AI
Ben Lorica and Roger Chen provide a glimpse into tools and trends poised to accelerate AI innovation.