Raffaello D’Andrea presents his vision of how autonomous indoor drones will drive the next wave of robotics development.
Zhe Zhang provides an architectural overview of LinkedIn’s machine learning pipelines.
Walter Riviera discusses three key shifts in the AI landscape.
Ihab Ilyas describes the HoloClean framework, a prediction engine for structured data with direct applications in detecting and repairing data errors.
Jeff Jonas details how you can use a purpose-built real-time AI to gain new insights and make better decisions faster.
Alexis Crowell Helzer outlines a practical approach to implementing machine learning.
Ben Lorica and Roger Chen review how companies are building AI applications today.
Kim Hazelwood and Mohamed Fawzy look at how applied ML has changed the platforms and infrastructure at Facebook.
The O’Reilly Data Show Podcast: Peter Bailis on data management, ML benchmarks, and building next-gen tools for analysts.
In this edition of the Radar column, we look at what’s possible when ML apps can work with minimal or inconsistent power supplies.
Experts explore new trends, tools, and techniques in data and machine learning.
Arun Murthy introduces the open source Cloudera Data Platform (CDP).
Jed Dougherty presents the trailer of the upcoming Data Science Pioneers documentary.
Barbara Eckman shares lessons learned from early big data mistakes and the progress her team at Comcast is making toward a big data vision.
Jonathan Foster explains why language reveals ethical challenges we couldn’t encounter with GUI-powered experiences.
Edward Jezierski discusses the ways reinforcement learning is used across Microsoft.
The Strata Data Awards recognize the most innovative startups, leaders, and data science projects from Strata sponsors and exhibitors.
Cassie Kozyrkov offers actionable advice for taking advantage of machine learning, navigating the AI era, and staying safe as you innovate.
Alan Smith says combining visualization and sonification could take the presentation of data into the expanding universe of screenless devices and products.
Daniel Hernandez looks at how a unified, prescriptive information architecture can help organizations unlock the value of their data.
The O’Reilly Data Show Podcast: Arun Kejariwal and Ira Cohen on building large-scale, real-time solutions for anomaly detection and forecasting.
James Malone introduces new Google Cloud capabilities that help data professionals build scalable and flexible applications faster.
Patrick Lucey explains methods to find play similarity using multi-agent trajectory data, as well as predicting fine-grain plays.
Rob Thomas and Tim O’Reilly discuss the hard work and mass experimentation that will lead to AI breakthroughs.