I t was March 2016, and at the Four Seasons Hotel in Seoul, the world was gathered to watch the culmination of a battle 2,500 years in the making. On one side was the South Korean Lee Se-dol, the second-highest ranking Go player in the world. On the other was AlphaGo - a computer program developed by London-based artificial intelligence research company DeepMind. "Chess is the greatest game mankind has invented," game designer Alex Randolph once said. "Go is the greatest game mankind has discovered."

Chris Maddison was just an intern when he started working on the Go-playing AI that would eventually become AlphaGo. In March 2016, Google DeepMind's artificial intelligence system AlphaGo shocked the world. In a stunning five-match series of Go, the ancient Chinese board game, the AI beat the world's best player, Lee Sedol - a moment that was televised in front of millions and hailed by many as a historic moment in the development of artificial intelligence. Chris Maddison, now a professor of artificial intelligence at the University of Toronto, was then a master's student and helped get the project off the ground. Alex Wilkins: How did the idea for AlphaGo first come about?

He Did PR for Zuckerberg, Musk, and Google. Now He Says He'Only Told Half the Story' Thirty thousand feet in the air, Mark Zuckerberg turned to his speechwriter. The duo were flying in Zuckerberg's jet to the United Nations General Assembly in New York, where the Facebook boss was scheduled to address world leaders. Zuckerberg had a question for his companion. "Wait, what exactly is the UN?" Dex Hunter-Torricke had to hide his surprise. Zuckerberg was, by this point in 2015, the head of a company that was reshaping politics and societies around the world, with 1.5 billion users and counting.

A recently proposed class of models attempts to learn latent dynamics from high-dimensionalobservations,likeimages,usingpriorsinformedbyHamiltonian mechanics.

Instead, wesuggest that foragivenCMP,it is natural to be interested in Markov rewards, but acknowledge the importance of going beyond such functions.

Entertainment about or made with artificial intelligence has been missing the mark with viewers over the past year. Acclaimed director Darren Aronofsky is the executive producer of a new web series that matches human voice actors with video images generated in part by Google DeepMind. An insurrectionist robot unleashed by a mad inventor in Fritz Lang's . HAL 9000 sabotaging a manned mission to Jupiter in . Skynet, the self-aware global defense network that seeks to exterminate humanity throughout the franchise.

Do You Feel the AGI Yet? According to some predictions, 2026 is the year that an all-powerful AI will arrive. H undreds of billions of dollars have been poured into the AI industry in pursuit of a loosely defined goal: artificial general intelligence, a system powerful enough to perform at least as well as a human at any task that involves thinking. Will this be the year it finally arrives? Anthropic CEO Dario Amodei and xAI CEO Elon Musk think so.

Google's Project Genie lets you generate your own interactive worlds You'll need a Google AI Ultra subscription to try the showcase. Project Genie allows people outside of Google to try the company's Genie 3 world model. This past summer, Google DeepMind debuted Genie 3 . It's what's known as a world world, an AI system capable of generating images and reacting as the user moves through the environment the software is simulating. At the time, DeepMind positioned Genie 3 as a tool for training AI agents.

AI model from Google's DeepMind reads recipe for life in DNA An AI model developed by Google's DeepMind could transform our understanding of DNA - the complete recipe for building and running the human body - and its impact on disease and medicine discovery, according to researchers. Called AlphaGenome, the model could help scientists discover why subtle differences in our DNA put us at risk of conditions such as high blood pressure, dementia and obesity. It could also dramatically accelerate our understanding of genetic diseases and cancer. The developers of the model acknowledge it's not perfect, but experts have described it as an incredible feat and a major milestone. We see AlphaGenome as a tool for understanding what the functional elements in the genome do, which we hope will accelerate our fundamental understanding of the code of life, says Natasha Latysheva, research engineer at DeepMind.