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A chess program that learns from human error might be better at working with people or negotiating with them. It took about 50 years for computers to eviscerate humans in the venerable game of chess. A standard smartphone can now…

In the news | The Economist

But as the software improves, access to material gets harder.

An visual comparing public image classification APIs to the proposed denoised smoothing framework applied to a public image classification API. In the first sequence, an image of an elephant is input into a public image classification API, represented by an arrow leading to a gray square labeled as such. An arrow from the square points to a correct prediction of elephant, enclosed in a green square, with the words “no robustness guaranteed” under it. In the second sequence, an arrow points from an image of an elephant to six noisy copies of the image. An arrow then points from the copies to a square labeled “Custom-trained Denoiser,” which outputs six clean versions of the images. An arrow points from the clean copies to a square labeled “Public Image Classification API.” The classifier provides predictions for each copy, of which four correctly identify their respective images as elephant. Adjacent to the predictions is a pie chart labeled “Majority Rules!” with one-third of the pie in red and two-thirds in green. Arrows point to the output of the process: a final prediction of elephant, enclosed in a green square, and a strong robustness guarantee, denoted by the words “certified radius” enclosed in a green square.
Microsoft Research Blog

| Hadi Salman

Editor’s note: This post and its research are the result of the collaborative efforts of a team of researchers comprising former Microsoft Research Engineer Hadi Salman (opens in new tab), CMU PhD student Mingjie Sun (opens in new tab), Researcher…

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One fantastic feature in search engines is that they can understand when you misspell a word and correct it. This seemingly simple feature saves a lot of time in an average internet user’s life, but we haven’t quite known how…

In the news | OnMSFT

The Microsoft Research Team has developed a new AI that will automatically analyze people’s expressions during video meetings (via Windows Central). Indeed, the Microsoft Teams bot reads the non-verbal cues of the meeting participants and dynamically spotlights the most expressive…

In the news | OnMSFT

Microsoft has launched a new language system that should help to improve the search experience in Bing. The tool is called Speller100, and it leverages several AI models to correct spelling in over 100 languages to make the search engine…

In the news | ZDNet

As computational science and data science are becoming closer than ever, a deal with Microsoft could see Verily and Broad Institute's open-source cloud platform hit new users.

Articles

Research teams across Microsoft have conducted studies to better understand how those changes impacted our customers, ranging from consumers, to students and teachers, to Information Workers (IWs). This global effort now belongs to a larger body of research, known as…

In the news | ZDNet

Microsoft has explained how it is using a variety of technologies and techniques to fix bad spellings that can mean queries addressed to its Bing search engine would otherwise deliver the wrong results. The software giant is getting back to…