This second machine age has seen the rise of artificial intelligence (AI), or “intelligence” that is not the result of human cogitation. It is now ubiquitous in many commercial products, from search engines to virtual assistants. AI is the result of exponential growth in computing power, memory capacity, cloud computing, distributed and parallel processing, open-source solutions, and global connectivity of both people and machines.
Researchers are working on a new version of an algorithm that will power better search, autonomous cars, smarter smartphones and the Internet of Things.Deep-learning algorithms, which are based on loose simulations of the brain, have been used to advance technologies like speech recognition, natural language processing and robotic autonomy.
As a relatively new – but already highly sought after – position, it can be hard to know where Data Analytics ends and Data Science begins. Is it science? Statistics? Programming? Analytics? Black magic? Or some strange and wonderful combination? Making the most of this digital goldmine to optimize outcomes and meet business goals requires some very advanced skills that many organizations don’t yet have within their ranks.
As with many industries, data science is transforming the energy vertical, providing insights into cost reductions in down markets and allowing oil producers to adjust to market demands in boom times.
When General Motors was looking for someone to lead its global talent and organizational capability group, the $152 billion carmaker clearly wasn’t looking for a paper-pushing administrator. Michael Arena, who took the position 18 months ago, is an engineer by training. He was a visiting scientist at MIT Media Lab. He’s a Six Sigma black belt. He’s got a Ph.D.