Artificial Intelligence
Pursuing computing advances to create intelligent machines that complement human reasoning to augment and enrich our experience and competencies.
Video
Scalable Systems for Fast and Easy Machine Learning
“Machine learning models trained on massive datasets power a number of applications; from machine translation to detecting supernovae in astrophysics. However the end of Moore’s law and the shift towards distributed computing architectures presents many…
Publication
Neural Program Lattices
Microsoft Research Blog
The next challenges for reinforcement learning
Recent years have seen great progress for AI. In particular, artificial agents have learned to classify images and recognize speech at near-human level. However, for artificial agents to reach their full potential, they should not…
Microsoft Research Blog
Microsoft challenge: Build a collaborative AI in Minecraft
By John Roach, Writer, Microsoft Research A Microsoft Research team has created a competition using Project Malmo, a platform that uses Minecraft as a testing ground for advanced artificial intelligence research. The team is challenging…
Video
Building a Machine that Can Learn to Understand, Reason and Learn
My talk will first briefly review recent advances in memory augmented neural nets and then present my own contribution, Neural Semantic Encoders (NSE). With a special focus on NSE, I show that external memory in…
Video
Democratizing AI to Improve Citizen Health
Healthcare literature has exploded in the past 30 years. Can artificial intelligence help doctors keep up with what works in healthcare? Microsoft Azure and the Cochrane Transform Project, along with more than 5,000 citizen scientists…
Microsoft Research Blog
Democratizing AI to improve citizen health
By Kenji Takeda, Director, Azure for Research Doctors make life-saving — and life-changing — decisions every day. But how do they know that they are making the best decisions? Can artificial intelligence (AI) help? “Before…
Video
Neural Program Learning from Input-Output Examples
Most deep learning research focuses on learning a single task at a time – on a fixed problem, given an input, predict the corresponding output. How should we handle problems where the task is not…
