Daniel Hernandez looks at how a unified, prescriptive information architecture can help organizations unlock the value of their data.
Barbara Eckman shares lessons learned from early big data mistakes and the progress her team at Comcast is making toward a big data vision.
Edward Jezierski discusses the ways reinforcement learning is used across Microsoft.
Jed Dougherty presents the trailer of the upcoming Data Science Pioneers documentary.
The Strata Data Awards recognize the most innovative startups, leaders, and data science projects from Strata sponsors and exhibitors.
Siva Sivakumar explains how the Cisco Data Intelligence Platform brings together data, AI, compute, and storage.
Swatee Singh looks at how the financial services industry is using AI, ML, mixed reality and other technologies.
Jeremy Rader explores Intel’s end-to-end data pipeline software strategy.
James Malone introduces new Google Cloud capabilities that help data professionals build scalable and flexible applications faster.
Machine learning, artificial intelligence, data engineering, and architecture are driving the data space.
Experts discuss new trends, tools, and issues in artificial intelligence and machine learning.
Lei Pan explores how Nauto uses AWS to continually evolve smarter data for driver behavior.
Kenneth Stanley discusses how open-ended algorithms can offer an entirely different level of automated creation.
Sahika Genc dives deep into state-of-the-art techniques in deep reinforcement learning for a variety of use cases.
Ananth Sankaranarayanan discusses three three key shifts in the AI landscape, how to navigate them, and when to explore hardware acceleration.
Michael Jordan details several recent results that blend gradient-based methodology with game-theoretic goals.
Adversarial images aren’t a problem—they’re an opportunity to explore new ways of interacting with AI.
Speech adds another level of complexity to AI applications—today’s voice applications provide a very early glimpse of what is to come.