Earlier this year, an amateur Go player decisively defeated one of the game's top-ranked AI systems. They did so using a strategy developed with the help of a program researchers designed to probe systems like KataGo for weaknesses. It turns out that victory is just one part of a broader Go renaissance that is seeing human players become more creative since AlphaGO's milestone victory in 2016 In a recent study published in the journal PNAS, researchers from the City University of Hong Kong and Yale found that human Go players have become less predictable in recent years. As the New Scientist explains, the researchers came to that conclusion by analyzing a dataset of more than 5.8 million Go moves made during professional play between 1950 and 2021. With the help of a "superhuman" Go AI, a program that can play the game and grade the quality of any single move, they created a statistic called a "decision quality index," or DQI for short.

Our societies and economies are in transition to a future shaped by artificial intelligence (AI). To thrive in this coming era companies are transforming themselves by using machine learning, a type of AI that that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. This article investigates the role IT professionals play in enabling the AI-driven enterprise through machine learning model deployment. Imagine your company as an AI-driven enterprise. Embedded in core business processes, hundreds of machine learning models ingest streams of data as the company interacts with customers and suppliers.