Burrowed in the alleys of Hongik-dong, a hushed residential neighborhood in eastern Seoul, is a faded stone-tiled building stamped “Korea Baduk Association,” the governing body for professional Go. The game is an ancient one, with sacred stature in South Korea.  But inside the building, rooms once filled with the soft clatter of hands dipping into wooden bowls of stones now echo with mouse clicks. Players hunch over their monitors and replay their matches in an AI program. Others huddle around a Go board and debate the best next move, while coaches report how their choices stack up against the AI’s. […]

For years, Industry 4.0 transformation has centered on the convergence of intelligent technologies like AI, cloud, the internet of things, robotics, and digital twins. Industry 5.0 marks a pivotal shift from integrating emerging technologies to orchestrating them at scale. With Industry 5.0, the purpose of this interconnected web of technologies is more nuanced: to augment human potential, not just automate work, and enhance environmental sustainability. Industry 5.0 has ushered in a radically new level of collaboration between humans and machines, one that removes data silos and optimizes infrastructure, operations, and resource use to disrupt business models and create new forms […]

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller steps. These powerful models are particularly good at challenging tasks like advanced programming and multistep planning. But developing reasoning models demands an enormous amount of computation and energy due to inefficiencies in the training process. While a few of the high-power processors continuously work through complicated queries, others in the group sit idle. Researchers from MIT and elsewhere found a way to use this computational downtime to efficiently accelerate reasoning-model training. Their new method automatically trains a smaller, faster model […]