If you happen to have a free 30 hours or so, I would highly recommend watching Google's AlphaGo program take on one of the best players in the world at the ancient Chinese board game Go. If you don't have that much time, you could instead just watch the 6-hour third match, where the program wrapped up the best of five series. It's literally history being made. Some news outlets have covered this feat, but I don't think many people understand how monumental this actually is. Back in 1997, when Garry Kasparov was beaten by IBM's Deep Blue in chess, people were more excited about the future of computing.
Since the dawn of machinery and the first flickerings of computer technology, humanity has been obsessed with the idea of artificial intelligence - the concept that machines could one day interact, respond and think for themselves as if they were truly alive. Every year, the possibility of an "intelligent technology" future becomes more and more of a reality - as algorithms and machine learning improve at a lightning-fast rate. According to experts across the globe, machines will soon be capable of replacing a variety of jobs - from writing bestsellers, to composing Top 40 pop songs and even performing your open-heart surgery! However, the biggest questions remain: how long until that point, and how did we get to here? When attempting to chart the future, it's always essential to know the past.
Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.
It feels like this man needs no introduction, but for anyone who doesn't know who Demis Hassabis is, here's the lowdown. He's the cofounder and chief executive of the London-headquartered DeepMind AI lab, which was acquired by Google in 2014 for £400m. Prior to DeepMind, Hassabis had his own computer games company called Elixir Studios, but his passion for games goes way back. He was a chess master at the age of 13 and the second-highest-rated under 14 player in the world at one time. Catherine Breslin is a machine learning scientist and consultant based in Cambridge.