As artificial intelligence continues its rapid progress, equaling or surpassing human performance on benchmarks in an increasing range of tasks, researchers in the field are directing more effort to the interaction between humans and AI in domains where both are active. Chess stands as a model system for studying how people can collaborate with AI, or learn from AI, just as chess has served as a leading indicator of many central questions in AI throughout the field’s history. AI-powered chess […]

You are here. We see some representation of this every day—a red pin, a pulsating blue dot, a small graphic of an airplane. Without a point of reference on which to anchor it, though, here doesn’t help us make our next move or coordinate with others. But in the context of an office building, street, or U.S. map, “here” becomes a location that we can understand in relation to other points. We’re near the lobby; at the intersection of Broadway […]

At Microsoft, we have been on a quest to advance AI beyond existing techniques, by taking a more holistic, human-centric approach to learning and understanding. As Chief Technology Officer of Azure AI Cognitive Services, I have been working with a team of amazing scientists and engineers to turn this quest into a reality. In my role, I enjoy a unique perspective in viewing the relationship among three attributes of human cognition: monolingual text (X), audio or visual sensory signals, (Y) […]

Consider for a moment what it takes to visually identify and describe something to another person. Now imagine that the other person can’t see the object or image, so every detail matters. How do you decide what information is important and what’s not? You’ll need to know exactly what everything is, where it is, what it’s doing in relation to other objects, and note other attributes like color or position of objects in the foreground or background. This exercise shows […]

The goal of neural architecture search (NAS) is to have computers automatically search for the best-performing neural networks. Recent advances in NAS methods have made it possible to build problem-specific networks that are faster, more compact, and less power hungry than their handcrafted counterparts. Unfortunately, many NAS methods rely on an array of tricks that aren’t always documented in a way that’s easy to discover. While these tricks result in neural networks with greater accuracy, they often cloud the performance […]

Is FashionMNIST, a dataset of images of clothing items labeled by category, more similar to MNIST or to USPS, both of which are classification datasets of handwritten digits? This is a pretty hard question to answer, but the solution could have an impact on various aspects of machine learning. For example, it could change how practitioners augment a particular dataset to improve the transferring of models across domains or how they select a dataset to pretrain on, especially in scenarios […]