A Vision for the Future of Systems
When you surf the Internet with your favorite search engine, when you play with Xiaoice or Siri to see if they are smart or dumb, or when you experience the adventure and convenience of autonomous driving, that smooth user experience…
Soundscaping the world with Amos Miller
Episode 54, December 12, 2018 - Amos Miller is a product strategist on the Microsoft Research NeXT Enable team, and he’s played a pivotal role in bringing some of MSR’s most innovative research to users with disabilities. He also happens…
First TextWorld Problems—Microsoft Research Montreal’s latest AI competition is really cooking
| Wendy Tay and Adam Trischler
This week, Microsoft Research threw down the gauntlet with the launch of a competition challenging researchers around the world to develop AI agents that can solve text-based games. Conceived by the Machine Reading Comprehension team at Microsoft Research Montreal, the…
A Deep Learning Theory: Global minima and over-parameterization
| Zeyuan Allen-Zhu, Yuanzhi Li, and Zhao Song
One empirical finding in deep learning is that simple methods such as stochastic gradient descent (SGD) have a remarkable ability to fit training data. From a capacity perspective, this may not be surprising— modern neural networks are heavily over-parameterized, with…
Fast, accurate, stable and tiny – Breathing life into IoT devices with an innovative algorithmic approach
In the larger quest to make the Internet of Things (IoT) a reality for people everywhere, building devices that can be both ultrafunctional and beneficent isn’t a simple matter. Particularly in the arena of resource-constrained, real-time scenarios, the hurdles are…
Learning to teach: Mutually enhanced learning and teaching for artificial intelligence
| Fei Tian
Teaching is super important. From an individual perspective, a student learning on his or her own is never ideal; a student needs a teacher's guidance and perspective to be more effectively educated. Taking the societal perspective, teaching enables civilization to…
Chasing convex bodies and other random topics with Dr. Sébastien Bubeck
Episode 53, December 5, 2018 - Dr. Sébastien Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to…
In the news | Forbes
Microsoft Puts More Brain-Power Into Machine Learning For Azure Cloud
The advancements that now come forward in this part of Microsoft's ML brain play result in part from experimentation carried out by Nicolo Fusi, who works in the automated machine learning research team at Microsoft Research.