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.

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  1. Deliberation Network: Pushing the frontiers of neural machine translation

    During the Tang dynasty of China, which lasted from 618 to 907, the poet Jia Dao was known for polishing his poems over and over to make them better and better. One famous story describes how he deliberated over two lines of a poem that read, “Birds nestle in the trees by the pond. A monk pushes the door in the moonlight.” Dao concentrated on the word “pushes.” He considered using “knocks” instead. After a…

    December 6th, 2017

  2. Hybrid Reward Architecture and the Fall of Ms. Pac-Man with Dr. Harm van Seijen

    Episode 3, December 6, 2017 - If you’ve ever watched King of Kong: Fistful of Quarters, you know what a big deal it is to beat a video arcade game that was designed not to lose. Most humans can’t even come close. Enter Harm van Seijen, and a team of machine learning researchers from Microsoft Research Montreal. They took on Ms. Pac-man. And won. Today we’ll talk to Harm about his work in reinforcement learning,…

    December 6th, 2017

  3. ‘Contextual bandit’ breakthrough enables deeper personalization

    News portals that simultaneously personalize every part of the landing page for every visitor and mobile health apps that adaptively tweak every part of an exercise regimen to maximize the benefit of every user are becoming plausible due to an advance in a type of interactive machine learning that my team will describe at the Annual Conference on Neural Information Processing Systems running December 4-9 in Long Beach, California. Our research falls in an important…

    December 5th, 2017

  4. Will machines one day be as creative as humans?

    Recent methods in artificial intelligence enable AI software to produce rich and creative digital artifacts such as text and images painted from scratch. One technique used in creating these artifacts are generative adversarial networks (GANs). Today at NIPS 2017, researchers from Microsoft Research and ETH Zurich present their work on making GAN models more robust and practically useful. Generative adversarial networks are a recent breakthrough in machine learning. Initially proposed by Ian Goodfellow and colleagues…

    December 4th, 2017

  5. New Microsoft Research Podcast invites you to log on, tune in and geek out

    Microsoft Research Podcast Subscribe and listen on iTunes, android or email I’ve spent the better part of the last decade investigating the impact of digital media and technology on culture from an academic perspective. I have conducted my own qualitative research and devoured nearly every book, article, tweet, post or link I could find on the subject. I’m as interested as any person who can’t do the math could possibly be in what’s going on…

    December 4th, 2017

  6. AI and Our Future With Machines with Dr. Eric Horvitz

    Episode 2, December 4, 2017 - When it comes to artificial intelligence, Dr. Eric Horvitz is as passionate as he is accomplished. His contributions to the field, and service on the boards of nearly every technical academy and association in the country, have earned him the respect – and awe – of his colleagues, along with the position of Technical Fellow and Managing Director of Microsoft Research. Dr. Horvitz talks about the goal of artificial…

    December 4th, 2017

  7. Snippets from the Revolution – An Interview with Dr. Jaime Teevan

    Episode 1, November 28, 2017 - Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counterintuitive. Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of 4 young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us…

    December 4th, 2017

  8. Microsoft Research and Microsoft Azure improve the efficiency and capacity of cloud-scale optical networks

    Today, at HotNets 2017, the Sixteenth ACM Workshop on Hot Topics in Networks, we shared with you some important research results from Microsoft Research and Microsoft Azure that show how we can increase the capacity of optical networks without purchasing new fibers. Data, data, data – it’s all about the data Our journey to understand and improve optical networks began several years ago. To innovate we first needed to measure the operational efficiency of our optical…

    December 1st, 2017

  9. FigureQA: an annotated figure dataset for visual reasoning

    Reasoning about figures Almost every scientific publication is accompanied by data visualizations in the form of graphs and charts. Figures are an intuitive aid for understanding the content of documents, so naturally, it is useful to leverage this visual information for machine reading comprehension. To enable research in this domain we built FigureQA, a new dataset composed of figure images – like bar graphs, line plots, and pie charts – and question and answer pairs about them. We…

    November 17th, 2017

  10. Microsoft extends AirSim to include autonomous car research

    Earlier this year, we open-sourced a research project called AirSim, a high-fidelity system for testing the safety of artificial intelligence systems. AirSim provides realistic environments, vehicle dynamics and sensing for research into how autonomous vehicles that use AI that can operate safely in the open world. Today, we are sharing an update to AirSim: We have extended the system to include car simulation, which will help advance the research and development of self-driving vehicles. The…

    November 13th, 2017

  11. Neural fuzzing: applying DNN to software security testing

    Microsoft researchers have developed a new method for discovering software security vulnerabilities that uses machine learning and deep neural networks to help the system root out bugs better by learning from past experience. This new research project, called neural fuzzing, is designed to augment traditional fuzzing techniques, and early experiments have demonstrated promising results. Software security testing is a hard task that is traditionally done by security experts through costly and targeted code audits, or…

    November 13th, 2017

  12. Scientists use machine learning to predict DNA binding rates from sequence

    By Microsoft Research Lab - Cambridge and Department of Bioengineering, Rice University The binding of DNA strands by Watson-Crick base pairing is a fundamental process in biotechnology, which is used around the world for reading and writing DNA sequences and for assembling DNA nanostructures. Yet this process remains poorly understood, and there is still no way to accurately predict how quickly two DNA strands will bind. The binding rate of two complementary DNA strands can…

    November 8th, 2017