If A.I. isn’t counterintuitive, why should we pay for it?
The pandemic has driven many companies to accelerate digital transformation. This is particularly true in manufacturing, where the pandemic has forced businesses think about how to operate with fewer workers on machine shop floors and assembly lines.
Automation is the order of the day. And, increasingly, artificial intelligence is playing a role in these efforts—predicting when machines will need maintenance, directing growing armies of factory robots on their daily rounds, and optimizing workflows throughout the entire manufacturing process.
In the coming weeks, I will be writing more about this trend. But today, I want to talk about the way in which industry's turn to A.I. is accelerating a particular type of machine learning: deep reinforcement learning (or deep RL). This combines deep neural networks, the kind of machine learning software very loosely based on the wiring of the human brain, with reinforcement learning, which involves learning from experience rather than historical data. Deep RL is behind most of the big breakthroughs in computers that can play various kinds of games better than top humans, including DeepMind’s achievements in Atari, the strategy game Go, and most recently, with Starcraft II, as well as OpenAI’s work on the video game Dota 2 and Facebook’s and Carnegie Mellon University’s poker-playing software.