The Machine Comprehension team at MSR-Montreal recently developed a neural mechanism for metalearning that we call conditionally shifted neurons. Conditionally shifted neurons (CSNs) adapt their activation values rapidly to new data to help neural networks solve new tasks. They do this with task-specific, additive shifts…
Released in preview this week at Build 2018, the new Microsoft Translator custom feature lets users customize neural machine translation systems. These customizations can be applied to both text and speech translation workflows. Microsoft Translator released neural machine translation (NMT) in 2016. NMT provided major…
Over the last five years, deep learning-based methods have revolutionised a wide range of applications, for example those requiring understanding of pictures, speech and natural language. For computer scientists, a naturally arising question is whether computers learn to understand source code? It appears to be…
Generative models are an important subset of machine learning goals and tasks that require realistic and statistically accurate generation of target data. Among all available generative models, generative adversarial networks (GANs) have emerged recently as a leading and state-of-the-art method, particularly in image generation tasks.…
Program synthesis — automatically generating a program that satisfies a given specification — is a major challenge in AI. In addition to changing the way we design software, it has the potential to revolutionize task automation. End users without programming skills can easily provide input-output…
The United States, along with much of the world, is in the midst of an economic transition from manual to intellectual labor. The changing nature of work, including the automation of labor, is an important issue facing society, with implications not only for our standard…
Imagine for a moment that you are blind and are navigating the web using a screen reader to hear websites rather than see them. Imagine that the article you have navigated to includes images. To understand the content and significance, you are relying on your…
Generating realistic images from a text description is a challenging task for a bot. A solution to this task has potential applications in the video game and image editing industries, among many others. Recently, researchers at Microsoft and elsewhere have been exploring ways to enable…
Virtual Reality and Augmented Reality each has distinct advantages when it comes to bringing digital capabilities into our everyday lives. Everything users see, including the environment and every object can be controlled and changed. This also means that what users see doesn’t necessarily mirror the…
The notion of an “uncanny valley” is well known in robotics[1]. This is when increasing the realism of a robot’s human-like appearance can lead to feelings of unease—or even revulsion—as a robot becomes more and more (but never quite fully) human-like[2]. While this uncanny valley…
At RSA Conference 2018, Microsoft announced Azure Sphere, previewing a unique new solution to help connect and secure the most populous category of computing today: the tens of billions of devices powered by microcontrollers (MCUs). Azure Sphere represents an opportunity for Microsoft and our partners…
Over the last decade, advances in machine learning coupled with the availability of large amounts of data have led to significant progress on long-standing AI challenges. In domains like computer vision, speech recognition, machine translation and image captioning, machines have reached and sometimes even exceeded…
