The state of machine learning in Apache Spark
The O’Reilly Data Show Podcast: Ion Stoica and Matei Zaharia explore the rich ecosystem of analytic tools around Apache Spark.
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).
Finding meaning in generative adversarial networks
Artificial intelligence is emerging as a creative force; in the process, it reveals something of itself.
Solving real-world business problems with computer vision
Applications of CNNs for real-time image classification in the enterprise.
Effective mechanisms for searching the space of machine learning algorithms
The O’Reilly Data Show Podcast: Kenneth Stanley on neuroevolution and other principled ways of exploring the world without an objective.
Bringing gaming to life with AI and deep learning
Machine learning opens the door for the use of training rather than programming in game development.
6 practical guidelines for implementing conversational AI
How organizations can create more fluid interactions between humans and machines.
How Ray makes continuous learning accessible and easy to scale
The O’Reilly Data Show Podcast: Robert Nishihara and Philipp Moritz on a new framework for reinforcement learning and AI applications.
Why continuous learning is key to AI
A look ahead at the tools and methods for learning from sparse feedback.
Why AI and machine learning researchers are beginning to embrace PyTorch
The O’Reilly Data Show Podcast: Soumith Chintala on building a worthy successor to Torch and on deep learning within Facebook.
Reinforcement learning for complex goals, using TensorFlow
How to build a class of RL agents using a TensorFlow notebook.
How big data and AI will reshape the automotive industry
The O’Reilly Data Show Podcast: Evangelos Simoudis on next-generation mobility services.
Neuroevolution: A different kind of deep learning
The quest to evolve neural networks through evolutionary algorithms.
Introduction to reinforcement learning and OpenAI Gym
A demonstration of basic reinforcement learning problems.
A framework for building and evaluating data products
The O’Reilly Data Show Podcast: Pinterest data scientist Grace Huang on lessons learned in the course of machine learning product launches.
Magenta: Machine learning and creativity
Doug Eck discusses Magenta, a Google Brain project aimed at developing new machine learning models for art and sound creation.
Cars that coordinate with people
Anca Dragan introduces a mathematical formulation that accounts for cars responding to people and people responding to cars.
Superhuman AI for strategic reasoning: Beating top pros in heads-up no-limit Texas Hold’em
Tuomas Sandholm explains how domain-independent algorithms are being applied to a variety of imperfect-information games, like poker.
Artificial intelligence in the software engineering workflow
The workflow of the AI researcher has been quite different from the workflow of the software developer. Peter Norvig explores how the two can come together.
Building a next-generation platform for deep learning
The O’Reilly Data Show Podcast: Naveen Rao on emerging hardware and software infrastructure for AI.
Why artificial intelligence is different from previous technology waves
The AI ecosystem just might be resilient enough to live up to the hype.
Highlights from the O’Reilly Artificial Intelligence Conference in New York 2017
Watch highlights covering artificial intelligence, machine learning, applied deep learning, and more. From the O'Reilly Artificial Intelligence Conference in New York 2017.
Tackling the limits of deep learning
Richard Socher explains how Salesforce is doing the heavy lifting to deliver scalable AI to customers.
Can machines spot diseases faster than expert humans?
Suchi Saria discusses the medical applications of artificial intelligence.
Machines as thought partners
David Ferrucci offers an overview of Elemental Cognition, a company focused on creating AI systems that autonomously learn from human language and interaction.