Machine Learning Leads As AI Trend
Humans trained the Tesla Model S to drive semi-autonomously, but after the cars learned, they shared the knowledge gained with the other cars. Then, as CEO Elon Musk predicted, they all improved even faster. As Aaron Frank of Singularity University writes about this fascinating trend:
…Fred Lambert with Electrek reported shortly after, Model S owners noticed how quickly the car’s driverless features were improving. In one example, Teslas were taking incorrect early exits along highways, forcing their owners to manually steer the car along the correct route. After just a few weeks, owners noted the cars were no longer taking premature exits.
Ray Kurzweil’s “The Law of Accelerating Returns” theory has become a reality as systems improve at an exponential rate by sharing knowledge. Hod Lipson, professor of mechanical engineering and data science at Columbia University, said the speed of learning is the greatest trend in AI.
“Lipson sees the recent breakthrough from Google’s DeepMind, a project called AlphaGo Zero, as a stunning example of an AI learning without training data. Many are familiar with AlphaGo, the machine learning AI which became the world’s best Go a player after studying a massive training data-set comprised of millions of human Go moves. AlphaGo Zero, however, was able to beat even that Go-playing AI, simply by learning the rules of the game and playing by itself—no training data necessary. Then, just to show off, it beat the world’s best chess playing software after starting from scratch and training for only eight hours.”
GE has developed a “digital twin” technology in which its turbines share data in a digital representation of themselves, also accelerating learning between machines globally. AI improvement could radically evolve as a result of such efforts.