Exploring the trajectory and potential of machine learning in incentive-based insurance at Discovery Ltd.
Telehealth has recently emerged as a convenient alternative to the traditional in-person health care appointment. Teladoc, the oldest and largest telehealth company, provides 24/7 access to physicians worldwide via audio or video consultations. Patients use the Teladoc website or mobile […]
“Imagine a world in which every single human being can freely share in the sum of all knowledge.”
In a war between Amazon and Walmart for the e-commerce crown, who will ultimately win?
This piece briefly examines the adoption of various open innovation practices by Mondelez International to better react to competitive pressures and position itself for long-term sustainable growth
In the competitive world of professional basketball, organizations such as the Toronto Raptors are turning to AI to improve the roster decision process in order to gain a competitive advantage in the race for a championship team.
Given the importance of addressing climate change and adding renewable generation to the energy grid, Xcel Energy is using machine learning to overcome the challenges of the intermittent nature of wind power.
How Google is using Machine Learning to keep Gmail (and other core products) ahead of the rest.
Deutsche Bahn is investing heavily in additive manufacturing. How can they best incorporate this technology into their future supply chain?
From startups to Big Tech, everyone loves to tout their strategy for leveraging machine learning (ML). These companies promise ML is our 21st century savior; it will not only liberate us from the tedious drudgery of administrative tasks but will arm us with near-perfect predictions. But the technology has a dark side, one that few companies adequately acknowledge and even fewer are equipped to handle.