Highlights from the Strata Data Conference in London 2019
Watch highlights from expert talks covering machine learning, predictive analytics, data regulation, and more.
O’Reilly Radar Analysis
Looking Back on the O’Reilly Artificial Intelligence Conference
More than anything else, O'Reilly's AI Conference was about making the leap to AI 2.0.
How companies adopt and apply cloud native infrastructure
Survey results reveal the path organizations face as they integrate cloud native infrastructure and harness the full power of the cloud.
Why companies are in need of data lineage solutions
The O’Reilly Data Show Podcast: Neelesh Salian on data lineage, data governance, and evolving data platforms.
Decoding the human genome with deep learning
How can machine learning decode the mysteries of life? Olga Troyanskaya explores this and other big questions through the prism of deep learning.
Applied machine learning at Facebook
Kim Hazelwood discusses the hardware and software Facebook has designed to meet its scale needs.
Making real-world distributed deep learning easy with Nauta
Carlos Humberto Morales offers an overview of Nauta, an open source multiuser platform that lets data scientists run complex deep learning models on shared hardware.
Simple, scalable, and sustainable: A methodical approach to AI adoption
Rajendra Prasad explains how leaders in large enterprises can make AI adoption successful.
Software 2.0 and Snorkel
Christopher Ré discusses Snorkel, a system for fast training data creation.
Computational propaganda
Sean Gourley considers the repercussions of AI-generated content that blurs the line between what's real and what's fake.
Artificial intelligence: The “refinery” for data
Nick Curcuru explains how Mastercard is using AI to improve security without sacrificing the customer experience.
Data fueling AI of the future
Thomas Henson considers how AI will shape the experiences of future generations.
Toward ethical AI: Inclusivity as a messy, difficult, but promising answer
Kurt Muehmel explores AI within a broader discussion of the ethics of technology, arguing that inclusivity and collaboration are necessary.
Automated ML: A journey from CRISPR.ML to Azure ML
Danielle Dean explains how cloud, data, and AI came together to help build Automated ML.
Fast, flexible, and functional: 4 real-world AI deployments at enterprise scale
Gadi Singer discusses the major questions organizations confront as they integrate deep learning.
Machine learning for personalization
Tony Jebara explains how Netflix is personalizing and optimizing the images shown to subscribers.
Highlights from the O’Reilly Artificial Intelligence Conference in New York 2019
Watch highlights from expert talks covering AI, machine learning, deep learning, ethics, and more.
Checking in on AI tools
Ben Lorica and Roger Chen assess the state of AI technologies and adoption in 2019.