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When it comes to chess, computers seem to have nothing left to prove. Since IBM’s Deep Blue defeated world chess champion Garry Kasparov in 1997, advances in artificial intelligence have made chess-playing computers more and more formidable. No human has beaten a computer in a chess tournament in 15 years. In new research, a team including Jon Kleinberg, the Tisch University Professor of Computer Science, developed an artificially intelligent chess engine that doesn’t necessarily seek to beat humans – it’s trained to play like a human. This not only creates a more enjoyable chess-play...

Maia Chess Capturing human style in chess Maia’s goal is to play the human move — not necessarily the best move. As a result, Maia has a more human-like style than previous engines, matching moves played by human players in online games over 50% of the time. During training, Maia is given a position that occurred in a real human game and tries to predict which move was made. After seeing hundreds of millions of positions, Maia accurately captures how people at different levels play chess. Maia is an AlphaZero/Leela-like deep learning framework that learns from online ...

Published January 9, 2021, 4:45 PM Four data science projects under the Good Governance through Data Science and Decision Support System (GODDESS) Program of the  Department of Science and Technology-Philippine Council for Industry, Energy,  and Emerging Technology Research and Development (DoST-PCIEERD) have been approved. DoST-PCIEERD said that the program aims to address the gap in the country’s workforce for data scientists and support research and development  that will enable the government to adapt to data-driven governance and evidence-based management. The approved projects wer...

PNNL TranSEC tool uses UBER data to track and potentially alleviate urban traffic congestion Researchers at Pacific Northwest National Laboratory (PNNL) have developed a new machine-learning-based tool to help urban transportation analysts relieve bottlenecks and chokepoints that routinely snarl city traffic. The tool—Transportation State Estimation Capability (TranSEC)—was developed to help urban traffic engineers get access to actionable information about traffic patterns in their cities. Currently, publicly available traffic information at the street level is sparse and incomplete. Tr...