Big Data
How Big Data Helped Chicago Improve Its Food Safety
July 17, 2019Using big data, the city of Chicago deploys its health inspectors to the establishments at highest risk first and allows inspectors to discover violations 25 percent faster.
Luminaries
Episode 38: Enhancing Human Performance…Using Motorsport Technology
Duration 27:18
McLaren Applied Technologies works at applying the principles of Formula 1 technology to deliver quantifiable deliver quantifiable performance advantage to four key sectors including Motorsport, Automotive, Public Transport and Health. The latter aims to enhance human performance in high intensity professions, elite athletes and racing drivers. Duncan Bradley, Health & Human Performance Business Unit Director, outlines how the digital transformation of motorsport has allowed them to develop transformative solutions.
Data Analytics
Reexamining the Data Money Tree
July 10, 2019When done right, data monetization can be an untapped source of third-party revenue. Learn why companies should consider leveraging data insights to achieve these tangible results.
Dell Technologies
Welcome to the Data Era
June 17, 2019How one technology leader describes the importance of data to predict the future, understand the past and succeed in a smart world. John Roese, President and CTO, Dell EMC, welcomes us to the data era.
Artificial Intelligence
Pentagon Projects Move Military into AI Arena
April 25, 2019Artificial intelligence is changing the way the United States Department of Defense and the Pentagon does business. The recently created Joint Artificial Intelligence Center (JAIC) will focus on a wide variety of projects, such as using machine learning to label thousands of drone video images in its counterterrorism efforts.
Machine Learning
Labels Before Drones: The Painstaking Machine Learning Process Behind Stopping Poachers
March 25, 2019AirShepherd and University of Southern California doctoral student Elizabeth Bondi is helping wildlife rangers stop poaching. But her team is faced with a challenge common in the data science and machine learning space: accurate labeling.
