Elon Musk, Bill Gates and Stephen Hawking are among those that have raised concerns regarding our pursuit of artificial intelligence, while Musk has recently gone so far to suggest that AI presents “more risk than North Korea” and should be regulated, like “everything (cars, planes, food, drugs, etc.) that’s a danger to the public.” Our colleague Yves Bergquist, director of ETC’s Data & Analytics Project, published a compelling rebuttal on Medium this week, in which he clearly defines “narrow AI” and “artificial general intelligence” in order to provide additional context regarding the evolution of AI applications and their numerous possibilities. Continue reading In Response to Elon Musk and His Concerns About AI Safety

As predicted, artificial intelligence has been one of the most repeated phrases of CES 2017. It seems every other vendor here is slapping the “AI” label on its technology. So much so that it inspired us to take a (short) step back and look at what AI is in relation to machine learning. The reality is: there are still very few applications that can be legitimately labeled as artificial intelligence. Self-driving cars, DeepMind’s AlphaGo, Hanson Robotics’ Sophia robot, and to a lesser extent Alexa, Siri and the Google Assistant, are all AI applications. Most of the rest, and certainly most of what we’ve seen here at CES, are robust, well productized machine learning applications (usually built on neural network architectures), often marketed as AI. Continue reading CES 2017: Distinguishing Between Machine Learning and AI