TinyML: The opportunities of low-power ML apps
In this edition of the Radar column, we look at what’s possible when ML apps can work with minimal or inconsistent power supplies.
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).
Highlights from Strata NY '19
Experts explore new trends, tools, and techniques in data and machine learning.
Delivering the enterprise data cloud
Arun Murthy introduces the open source Cloudera Data Platform (CDP).
Data Science Pioneers: Conquering the next frontier, a documentary investigating the future of data science
Jed Dougherty presents the trailer of the upcoming Data Science Pioneers documentary.
Postrevolutionary big data: Promoting the general welfare
Barbara Eckman shares lessons learned from early big data mistakes and the progress her team at Comcast is making toward a big data vision.
Say what? The ethical challenges of designing for humanlike interaction
Jonathan Foster explains why language reveals ethical challenges we couldn’t encounter with GUI-powered experiences.
RL in real life: Bringing reinforcement learning to the enterprise
Edward Jezierski discusses the ways reinforcement learning is used across Microsoft.
Staying safe in the AI era
Cassie Kozyrkov offers actionable advice for taking advantage of machine learning, navigating the AI era, and staying safe as you innovate.
Strata Data Awards winners 2019
The Strata Data Awards recognize the most innovative startups, leaders, and data science projects from Strata sponsors and exhibitors.
Unlocking the value of your data
Daniel Hernandez looks at how a unified, prescriptive information architecture can help organizations unlock the value of their data.
Data sonification: Making music from the yield curve
Alan Smith says combining visualization and sonification could take the presentation of data into the expanding universe of screenless devices and products.
Machine learning and analytics for time series data
The O’Reilly Data Show Podcast: Arun Kejariwal and Ira Cohen on building large-scale, real-time solutions for anomaly detection and forecasting.
The future of Google Cloud data processing
James Malone introduces new Google Cloud capabilities that help data professionals build scalable and flexible applications faster.
Interactive sports analytics
Patrick Lucey explains methods to find play similarity using multi-agent trajectory data, as well as predicting fine-grain plays.
AI isn’t magic. It’s computer science.
Rob Thomas and Tim O’Reilly discuss the hard work and mass experimentation that will lead to AI breakthroughs.
How disruptive tech is reshaping the financial services industry
Swatee Singh looks at how the financial services industry is using AI, ML, mixed reality and other technologies.
Recent trends in data and ML
Ben Lorica dives into emerging technologies for building data infrastructures and machine learning platforms.
Unleash the power of data at scale
Jeremy Rader explores Intel’s end-to-end data pipeline software strategy.
Everything is connected and the clock is ticking
Sara Menker and Nemo Semret outline the complex and interconnected factors that shape the agriculture industry.
Cisco Data Intelligence Platform
Siva Sivakumar explains how the Cisco Data Intelligence Platform brings together data, AI, compute, and storage.
Safe and smarter driving, powered by AI
Lei Pan explores how Nauto uses AWS to continually evolve smarter data for driver behavior.
On gradient-based methods for finding game-theoretic equilibria
Michael Jordan details several recent results that blend gradient-based methodology with game-theoretic goals.
Accelerate with purpose
Ananth Sankaranarayanan discusses three three key shifts in the AI landscape, how to navigate them, and when to explore hardware acceleration.
Practical insights into deep reinforcement learning
Sahika Genc dives deep into state-of-the-art techniques in deep reinforcement learning for a variety of use cases.