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Microsoft unveils de-cluttering option for Office 365 mailboxes

Microsoft today launched Clutter, an email filtering option for Office 365 business customers.

The tool, which Microsoft debuted earlier this year in Outlook Web App (OWA), the browser-based mail client for Exchange, will roll out to Office 365 commercial customers starting today.

Similar to an anti-spam filter, Clutter shunts messages into a segregated folder where they can be ignored or reviewed later. Microsoft defines “clutter” as “lower priority messages” that, while not strictly spam, are either unimportant or useless.

“Clutter removes distractions so you can focus on what matters most,” claimed Brian Shiers, a senior product marketing manager, and Kumar Venkateswar, a senior program manager, in a blog post Tuesday. Shiers and Venkateswar work on the Exchange team.

In practice, Clutter works similarly to a spam filter: Users can drag messages they deem suitable to a same-named folder to “train” the tool to spot like email in the future. “It gets smarter over time, learning from your prior actions with similar messages, and assessing things like the type of content and even how you are addressed in the message,” said Shiers and Venkateswar.

Once enabled in OWA, Clutter appears in other clients linked to that Exchange account, including Outlook on both Windows and OS X desktops and notebooks, and the iPhone and Android OWA apps.

Microsoft powered Clutter with Office Graph, the machine learning engine that also drives Delve, an Office 365 application that attempts to automatically connect users to the most relevant colleagues, files and data.

Employees whose workplaces have adopted Office 365 subscription plans — including Business Premium (12.50peruserpermonth)andEnterpriseE3(20 per user per month) — will be able to call on Clutter; consumers who subscribe to Office 365 Home or Personal will not.

Companies that have opted into Microsoft’s First Release program — corporate early adopters, in other words — will see Clutter today in English-speaking locales; others will be able to access the tool starting later this month, or in the case of non-English languages, once Microsoft wraps up localization.

Computerworld enabled Clutter on an Office 365 Enterprise account through OWA’s Options menu — Microsoft’s recommended method — and a new folder labeled “Clutter” appeared moments later in the desktop Outlook client tied to the account.

There was no immediate evidence that Clutter was doing its job — even though several eligible messages had been dragged to the folder — but Shiers and Venkateswar warned that it would take several days to begin sweeping aside messages. They added that “the more [messages] you move [to the Clutter folder], the faster it will learn.”

Enlitic picks up $2M to help diagnose diseases with deep learning

Image Credit: Tom Page/Flickr

In the near future, machines might help you improve your health.

Enlitic, a young startup that has committed to using a kind of artificial intelligence to assist doctors in the diagnosis and prognosis of diseases, is announcing a $2 million seed round at VentureBeat’sHealthBeat conference today.

Enlitic aims to process huge heaps of CT scans, x-rays, and other kinds of images and then unearth latent patterns in new images. It will do that using a trendy computational technique called deep learning, which entails training systems called artificial neural networks on lots of information derived from audio, images, and other inputs, and then presenting the systems with new information and receiving inferences about it in response.

Google does deep learning for all sorts of purposes. Netflix does it. Even Facebook does it. But when it comes to applying deep learning — a type of artificial intelligence — Enlitic is one of the first companies, if not the first, to do so.

Enlitic’s team has spent the past few months speaking with pathologists, radiologists, physicians, and hospital administrators, with an eye toward making applications that could be useful in all sorts of situations. They’ve come away with partnerships with hospitals in Brazil, China, India, and the U.S., and the company has been developing alliances with hardware makers and teleradiology clinics as well, Howard said. Enlitic has come across enormous archives of radiology images that can serve as a starting point.

Google, Spotify, & Pandora bet a computer could generate a better playlist than you can

Image Credit: Peter Durben/Flickr

Google, Pandora, and Spotify haven’t exactly advertised it, but they are all working on using a type of artificial intelligence called “deep learning” to make a better music playlist for you.

All three have recently hired deep learning experts. This branch of A.I. involves training systems called “artificial neural networks” with terabytes of information derived from images, text, and other inputs. It then presents the systems with new information and receives inferences about it in response. Companies including Google, Baidu, and others have put deep learning to work for all sorts of purposes — advertising, speech recognition, image recognition, even data center optimization. A startup even intends to use deep learning to recognize patterns in medical images.

Now these companies are turning to music. A neural network for a music-streaming service could recognize patterns like chord progressions in music without needing music experts to direct machines to look for them. Then it could introduce a listener to a song, album, or artist in accord with their preferences.

Putting these complex systems into production won’t necessarily happen overnight. But look out: Once in place, deep learning could be the kind of technology that inspires listeners to stick around music-streaming services for years to come.

“It’s a really exciting area, and certainly, it’s of high interest to Pandora,” Pandora senior scientist Erik Schmidt told VentureBeat in an interview.

Send in the interns

The new wave of attention leads back to an academic paper that came out of Belgium’s Ghent University last year.

In the obscure “reservoir computing” section of the university’s electronics and information systems department, Ph.D. students Sander Dieleman and Aäron van den Oord collaborated with professor Benjamin Schrauwen to make convolutional neural networks (CNNs) pick up attributes of songs, rather than using them to observe features in images, as engineers have done for years.

This Device Diagnoses Hundreds of Diseases Using a Single Drop of Blood

rHEALTH X1. XPRIZE Foundation

The digital health revolution is still stuck.

Tech giants are jumping into the fray with fitness offerings like Apple Health and Google Fit, but there’s still not much in the way of, well, actual medicine. The Fitbits and Jawbones of the world measure users’ steps and heart rate, but they don’t get into the deep diagnostics of, say, biomarkers, the internal indicators that can serve as an early warning sign of a serious ailment. For now, those who want to screen for a disease or measure a medical condition with clinical accuracy still need to go to the doctor.