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.

Most recent

  1. Hacking the runway with MakeCode with Dr. Thomas Ball and Dr. Teddy Seyed

    Episode 98 | November 13, 2019 - Computer programming has often been perceived as the exclusive domain of computer scientists and software engineers. But that’s changing, thanks to the work of people like Dr. Thomas Ball, a Partner Researcher in the RiSE group at Microsoft Research, and Dr. Teddy Seyed, a post-doctoral researcher in the same group. Their goal is to make programming accessible to non-programmers in places like the classroom, the workshop… and even…

    November 13th, 2019

  2. Optics for the cloud: storage in the zettabyte era with Dr. Ant Rowstron and Mark Russinovich

    Episode 97 | November 6, 2019 - Remember when a hard drive that could hold a terabyte of data was a big deal? Well, we’re now in an era where peta-, exa- and even zetta-bytes are the bytes of the day, and it turns out it’s hard to fit that many zeroes on a hard drive. That’s where Dr. Ant Rowstron, Deputy Lab Director of Microsoft Research Cambridge, and Mark Russinovich, Chief Technical Officer of Azure, come in. Their respective…

    November 6th, 2019

  3. Art + Architecture + AI = Ada with Jenny Sabin and Asta Roseway

    Episode 96 | October 30, 2019 - Jenny Sabin is an architectural designer, a professor, a studio principal and MSR’s current Artist in Residence. Asta Roseway is a principal research designer, a “fusionist” and the co-founder of the Artist in Residence program at Microsoft Research. The two, along with a stellar multi-disciplinary team, recently completed the installation of Ada, the first interactive architectural pavilion powered by AI, in the heart of the Microsoft Research building…

    October 30th, 2019

  4. PipeDream: A more effective way to train deep neural networks using pipeline parallelism

    Deep Neural Networks (DNNs) have facilitated tremendous progress across a range of applications, including image classification, translation, language modeling, and video captioning. DNN training is extremely time-consuming, needing efficient multi-accelerator parallelization. In “PipeDream: Generalized Pipeline Parallelism for DNN Training,” published at the 27th ACM Symposium on Operating Systems Principles (SOSP 2019), Microsoft researchers in the Systems Research Group, along with students and colleagues from Carnegie Mellon University and Stanford University, have proposed a new way…

    October 28th, 2019

  5. From blank canvas unfolds a scene: GAN-based model generates and modifies images based on continual linguistic instruction

    When people create, it’s not very often they achieve what they’re looking for on the first try. Creating—whether it be a painting, a paper, or a machine learning model—is a process that has a starting point from which new elements and ideas are added and old ones are modified and discarded, sometimes again and again, until the work accomplishes its intended purpose: to evoke emotion, to convey a message, to complete a task. Since I began my work as a researcher, machine learning systems have…

    October 23rd, 2019

  6. Machine teaching, LUIS and the democratization of custom AI with Dr. Riham Mansour

    Episode 95 | October 16, 2019 - Machine learning is a powerful tool that enables conversational agents to provide general question-answer services. But in domains with more specific taxonomies – or simply for requests that are longer and more complicated than “Play Baby Shark” – custom conversational AI has long been the province of large enterprises with big budgets. But not for long, thanks to the work of Dr. Riham Mansour, a Principal Software Engineering Manager for…

    October 23rd, 2019

  7. Getting a better visual: RepPoints detect objects with greater accuracy through flexible and adaptive object modeling

    Visual understanding tasks are typically centered on objects, such as human pose tracking in Microsoft Kinect and obstacle avoidance in autonomous driving. In the deep learning era, these tasks follow a paradigm where bounding boxes are localized in an image, features are extracted within the bounding boxes, and object recognition and reasoning are performed based on these features. The use of bounding boxes as the intermediate object representation has long been the convention because of their practical advantages. One advantage is that they are easy for…

    October 22nd, 2019

  8. A new era of spatial computing brings fresh challenges—and solutions—to VR

    Virtual reality (VR) has continually pushed the boundaries of how we perceive, from its early days of Ivan Sutherland’s Sword of Damocles to today. With the technology emerging from its early stages of bulky equipment tethered to one place out of necessity, researchers now are working with increased possibilities derived from hardware and new input sensors. The result is a unique set of challenges requiring innovative approaches to answering some of the most prevalent questions as far as what VR is capable of, where VR can happen, and how humans are able to experience it.

    October 21st, 2019

  9. News from the front in the post-quantum crypto wars with Dr. Craig Costello

    Episode 94, October 16, 2019 - Dr. Craig Costello is in the business of safeguarding your secrets. And he uses math to do it. A researcher in the Security and Cryptography group at Microsoft Research, Dr. Costello is among a formidable group of code makers (aka cryptographers) who make it their life’s work to protect the internet against adversarial code breakers (aka cryptanalysts), both those that exist today in our classical computing world, and those that will exist in…

    October 16th, 2019

  10. The inner magic behind the Z3 theorem prover

    It’s not uncommon for us to hear that the Z3 theorem prover is magical, but the frequency of such complimentary feedback doesn’t make it any less unexpected—or humbling. When we began work on Z3 in 2006, the design was motivated by two emerging use cases: program verification and dynamic symbolic execution. Research projects around program verification and dynamic symbolic execution, such as the verification-oriented programming language Dafny, automatic test generation, and fuzz testing, had created…

    October 16th, 2019

  11. Data science and ML for human well-being with Jina Suh

    Episode 93, October 9, 2019 - Using technology to help us improve our health is nothing new: a quick web search returns hundreds of apps and devices claiming to help us get fit, quit smoking, master anxiety or just “find our center.” What is new is a serious cohort of researchers exploring how artificial emotional intelligence, or AEI, could help us understand ourselves better and, when used in concert with human caregivers, enhance our well-being.…

    October 9th, 2019

  12. Expanding scene and language understanding with large-scale pre-training and a unified architecture

    Making sense of the world around us is a skill we as human beings begin to learn from an early age. Though there is still much to know about the process, we can see that people learn a lot, both directly and indirectly, from observing and interacting with their environments and other people in them: an uncle points to a shiny red piece of fruit and tells his nephew it’s an apple; a teacher reads…

    October 8th, 2019