We are thrilled to have mastered Go and thus achieved one of the grand challenges of AI. However, the most significant aspect of all this for us is that AlphaGo isn’t just an “expert” system built with hand-crafted rules; instead it uses general machine learning techniques to figure out for itself how to win at Go. While games are the perfect platform for developing and testing AI algorithms quickly and efficiently, ultimately we want to apply these techniques to important real-world problems. Because the methods we’ve used are general-purpose, our hope is that one day they could be extended to help us address some of society’s toughest and most pressing problems, from climate modeling to complex disease analysis. We believe these techniques can accelerate scientific research. Scientists working alongside AI systems that can home in on areas of research are very likely to be fruitful. The same techniques could even suggest a way forward that might point the human expert to a breakthrough. We’re excited to see what we can use this technology to tackle next!