Microsoft AI News

Microsoft Build 2017: Microsoft AI – Amplify human ingenuity

A few years ago, it was hard to think of a commonly used technology tool that used AI.

In a few years, it will be hard to imagine any technology that doesn’t tap into the power of AI.

Thanks to the convergence of three major forces — increased computing power in the cloud, powerful algorithms that run on deep neural networks and access to massive amounts of data — we’re finally able to realize the dream of AI.

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Microsoft is teaching systems to read, answer and even ask questions

Microsoft researchers have already created technology that can do two difficult tasks about as well as a person: identify images and recognize words in a conversation.

Now, the company’s leading AI experts are working on systems that can do something even more complex: Read passages of text and answer questions about them.

“We’re trying to develop what we call a literate machine: A machine that can read text, understand text and then learn how to communicate, whether it’s written or orally,” said Kaheer Suleman, the co-founder of Maluuba, a Quebec-based deep learning startup that Microsoft acquired earlier this year.

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Explanimators: Animated Adventures in Technology

AI has gone from science fiction to part of our daily lives. But what is it? How does it work? And why now?

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A conversation with AI pioneer Yoshua Bengio

When Microsoft acquired deep learning startup Maluuba in January, Maluuba’s highly respected advisor, the deep learning pioneer Yoshua Bengio, agreed to continue advising Microsoft on its artificial intelligence efforts. Bengio, head of the Montreal Institute for Learning Algorithms, recently visited Microsoft’s Redmond, Washington, campus, and took some time for a chat.

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Microsoft shares open source system for training drones, other gadgets to move safely on their own

When most people with normal vision walk down the street, they can easily differentiate the things they must avoid – like trees, curbs and glass doors — from the things they don’t, such as shadows, reflections and clouds.

Chances are, most people also can anticipate what obstacles they should expect to encounter next — knowing, for example, that at a street corner they should watch out for cars and prepare to step down off the curb.

The ability to differentiate and anticipate comes easily to humans but it’s still very difficult for artificial intelligence-based systems. That’s one big reason why self-driving cars or autonomous delivery drones are still emerging technologies.

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Microsoft Cognitive Services push gains momentum

The machine-learned smarts that enable Microsoft’s Skype Translator, Bing and Cortana to accomplish tasks such as translating conversations, compiling knowledge and understanding the intent of spoken words are increasingly finding their way into third-party applications that people use every day.

These advances in the democratization of artificial intelligence are coming in part from Microsoft Cognitive Services, a collection of 25 tools that allow developers to add features such as emotion and sentiment detection, vision and speech recognition, and language understanding to their applications with zero expertise in machine learning.

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AI is getting smarter; researchers want to ensure it’s also getting more accurate

Just a decade ago, the idea of using technology to do things like automatically translate conversations, identify objects in pictures — or even write a sentence describing those pictures — seemed like interesting research projects, but not practical for real-world use.

The recent improvements in artificial intelligence have changed that. These days more and more people are starting to rely on systems built with technologies such as machine learning. That’s raising new questions among artificial intelligence researchers about how to ensure that the basis for many of these systems — the algorithms, the training data and even the systems for testing the tools — are accurate and as unbiased as possible.

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AI in the News