Artificial Intelligence
Building intelligent machines that complement human reasoning and extend what people can do.
Microsoft Research Blog
Project Rocket platform—designed for easy, customizable live video analytics—is open source
Thanks to advances in computer vision and deep neural networks (DNNs) in what can arguably be described as the golden age of vision, AI, and machine learning, video analytics systems—systems performing analytics on live camera…
Video
Transparency and Intelligibility Throughout the Machine Learning Life Cycle
People play a central role in the machine learning life cycle. Consequently, building machine learning systems that are reliable, trustworthy, and fair requires that relevant stakeholders—including developers, users, and anybody affected by these systems—have at…
Podcast
Innovating in India with Dr. Sriram Rajamani
Dr. Sriram Rajamani is a Distinguished Scientist and the Managing Director of the Microsoft Research lab in Bangalore. He’s dedicated his career to advancing globally applicable science in the testbed that is India. He is,…
Webinar
Transparency and intelligibility throughout the machine learning life cycle webinar
In this webinar led by Microsoft researcher Jenn Wortman Vaughan, explore how to best incorporate transparency into the machine learning life cycle. Here, we will explore these three components of transparency (with examples): traceability, communication,…
Microsoft Research Blog
When bias begets bias: A source of negative feedback loops in AI systems
Is bias in AI self-reinforcing? Decision-making systems that impact criminal justice, financial institutions, human resources, and many other areas often have bias. This is especially true of algorithmic systems that learn from historical data, which…
Video
Perspectives on Cross-Validation
Cross-validation is probably the most widely used method for risk estimation in machine learning and statistics. However, analyzing it and comparing it to the data splitting estimator has proved difficult. In the first part of…
Microsoft Research Blog
By making text-based games more accessible to RL agents, Jericho framework opens up exciting natural language challenges
You’re in a field. In front of you, there’s a white house. The door is boarded shut. The immediate challenge—investigate the house. The game—Zork I: The Great Underground Empire, a treasure-seeking adventure in which you’ll…
Video
Exploring Reinforcement Learning Methods from Algorithm to Application
Reinforcement learning (RL) is a systematic approach to learning and decision making under uncertainty. Developed and studied for decades, recent combinations of RL with modern deep learning have led to impressive demonstrations of the capabilities…
