Microsoft Research Blog

The Microsoft Research blog provides in-depth views and perspectives from our researchers, scientists and engineers, plus information about noteworthy events and conferences, scholarships, and fellowships designed for academic and scientific communities.

Autonomous soaring – AI on the fly

The past few years have seen tremendous progress in reinforcement learning (RL). From complex games to robotic object manipulation, RL has qualitatively advanced the state of the art. However, modern RL techniques require a lot for success: a largely deterministic stationary environment, an accurate resettable simulator in which mistakes – and especially their consequences – are limited to the virtual sphere, powerful computers, and a lot of energy to run them. At Microsoft Research, we…

May 2019

Microsoft Research Blog

Minimizing gaps in information access on social networks while maximizing the spread

Lots of important information, including job openings and other kinds of advertising, are often transmitted by word-of-mouth in online settings. For example, social networks like LinkedIn are increasingly used as a way of spreading information about job opportunities, which can greatly affect people’s career development. The goal of social influence maximization, a well-studied problem, is to maximize the number of people in a social network that receive specific information, given a limited budget with which…

May 2019

Microsoft Research Blog

Launching a new round of projects in the Swiss JRC – Research with impact

January 31, 2019 marked the start of the sixth workshop for the Swiss Joint Research Center (Swiss JRC), an innovative and successful collaborative research engagement between Microsoft Research and the two universities that make up the Swiss Federal Institutes of Technology—ETH Zurich (ETH) and EPFL. The Swiss JRC is a continuation of an outstanding collaborative engagement that began back in 2008, with these two world-class institutions. Microsoft recently further committed to this engagement by ensuring…

February 2019

Microsoft Research Blog

Getting efficient with “What-happens-if …”

Causal inference studies the relationship between causes and effects. For example, one kind of question that causal inference can answer is the “What-happens-if …” question. What happens if I take a specific medication? What happens if I raise the price of a product? What happens if I go to the ER? What happens if I change a public policy? Often, the answers to these questions vary based on context—different patients might be more or less…

February 2019

Microsoft Research Blog

Traffic updates: Saying a lot while revealing a little

The idea of crowdsourcing traffic data has been around for a while: If we can get vehicles on the roads to upload their current speeds, then we can get instant, up-to-date data on how fast traffic is moving for well-traveled segments. This is useful for finding the fastest route to a destination, avoiding slowdowns. There are problems with this idea, though. The main one is that drivers need to upload their location along with their…

January 2019

Microsoft Research Blog

Creating better AI partners: A case for backward compatibility

Artificial intelligence technologies hold great promise as partners in the real world. They’re in the early stages of helping doctors administer care to their patients and lenders determine the risk associated with loan applications, among other examples. But what happens when these systems that users have come to understand and employ in ways that will enhance their work are updated? Sure, we can assume an improvement in accuracy or speed on the part of the…

January 2019

Microsoft Research Blog

Project Sonoma Greenhouse

Competition win a steppingstone in the greater journey to create sustainable farming

The cucumber plants, their leaves wide and green and veiny, stood tall in neat rows, basking in the Netherland sunlight shining through the glass panes of their greenhouses. Hopes were high for the plants—a bountiful crop in just four months using as few resources as possible. With the right amount and type of care, they’d produce vegetables for consumers to enjoy. To the casual observer, though, it might have seemed like the plants had been…

December 2018

Microsoft Research Blog

textworld at neurips 2018

First TextWorld Problems—Microsoft Research Montreal’s latest AI competition is really cooking

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 competition—First TextWorld Problems: A Reinforcement and Language Learning Challenge—runs from December 8, 2018 through May 31, 2019. First TextWorld Problems is built on the TextWorld framework. TextWorld was released to the public in July 2018…

December 2018

Microsoft Research Blog

A Deep Learning Theory: Global minima and over-parameterization

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 the number of parameters much larger than the number of training samples. In principle, there exist parameters to achieve 100% accuracy. Yet, from a theory perspective, why and how SGD finds global minima over the…

December 2018

Microsoft Research Blog

Learning to teach: Mutually enhanced learning and teaching for artificial intelligence

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 be passed on to the next generation. Human teachers have three concrete responsibilities: providing students with qualified teaching material (for example, textbooks); defining the appropriate skill set to be mastered by the students (for example,…

December 2018

Microsoft Research Blog

Getting into a conversational groove: New approach encourages risk-taking in data-driven neural modeling

Microsoft Research’s Natural Language Processing group has set an ambitious goal for itself: to create a neural model that can engage in the full scope of conversational capabilities, providing answers to requests while also bringing the value of additional information relevant to the exchange and—in doing so—sustaining and encouraging further conversation. Take the act of renting a car at the airport, for example. Across from you at the counter is the company representative, entering your…

December 2018

Microsoft Research Blog

redial

ReDial: Recommendation dialogs for bridging the gap between chit-chat and goal-oriented chatbots

Chatbots come in many flavors, but most can be placed in one of two categories: goal-oriented chatbots and chit-chat chatbots. Goal-oriented chatbots behave like a natural language interface for function calls, where the chatbot asks for and confirms all required parameter values and then executes a function. The Cortana chat interface is a classic example of a goal-directed chatbot. For example, you can ask about the weather for a specific location or let Cortana walk…

November 2018

Microsoft Research Blog