Prof. Geoffrey Hinton Awarded IEEE Medal For His Work In Artificial Intelligence


2014 in Computing: Breakthroughs in Artificial Intelligence

The past year saw progress in developing hardware and software capable of human feats of intelligence.

By Tom Simonite on December 29, 2014

The holy grail of artificial intelligence—creating software that comes close to mimicking human intelligence—remains far off. But 2014 saw major strides in machine learning software that can gain abilities from experience. Companies in sectors from biotech to computing turned to these new techniques to solve tough problems or develop new products.

The most striking research results in AI came from the field of deep learning, which involves using crude simulated neurons to process data.

Work in deep learning often focuses on images, which are easy for humans to understand but very difficult for software to decipher. Researchers at Facebook used that approach to make a system that can tell almost as well as a human whether two different photos depict the same person. Google showed off a system that can describe scenes using short sentences.

Results like these have led leading computing companies to compete fiercely for AI researchers. Google paid more than $600 million for a machine learning startup called DeepMind at the start of the year. When MIT Technology Review caught up with the company’s founder, Demis Hassabis, later in the year, he explained how DeepMind’s work was shaped by groundbreaking research into the human brain.

The search company Baidu, nicknamed “China’s Google,” also spent big on artificial intelligence. It set up a lab in Silicon Valley to expand its existing research into deep learning, and to compete with Google and others for talent. Stanford AI researcher and onetime Google collaborator Andrew Ng was hired to lead that effort. In our feature-length profile, he explained how artificial intelligence could turn people who have never been on the Web into users of Baidu’s Web search and other services.

Machine learning was also a source of new products this year from computing giants, small startups, and companies outside the computer industry.

Microsoft drew on its research into speech recognition and language comprehension to create its virtual assistant Cortana, which is built into the mobile version of Windows. The app tries to enter a back-and-forth dialogue with people. That’s intended both to make it more endearing and to help it learn what went wrong when it makes a mistake.

Startups launched products that used machine learning for tasks as varied as helping you get pregnant, letting you control home appliances with your voice, and making plans via text message .

Some of the most interesting applications of artificial intelligence came in health care. IBM is now close to seeing a version of its Jeopardy!-winning Watson software help cancer doctors use genomic data to choose personalized treatment plans for patients . Applying machine learning to a genetic database enabled one biotech company to invent a noninvasive test that prevents unnecessary surgery.

Using artificial intelligence techniques on genetic data is likely to get a lot more common now that Google, Amazon, and other large computing companies are getting into the business of storing digitized genomes.

However, the most advanced machine learning software must be trained with large data sets, something that is very energy intensive, even for companies with sophisticated infrastructure. That’s motivating work on a new type of “neuromorphic” chips modeled loosely on ideas from neuroscience. Those chips can run machine learning algorithms more efficiently.

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Skype can translate spoken Spanish to English in near real-time

Kif Leswing  Dec. 15, 2014 – 9:17 AM PST

Microsoft started rolling out a new feature for Skype on Monday: Skype Translator will translate communications from users using different languages in near real-time — that is, as you’re chatting. At first, Skype Translator will work with spoken English and Spanish, as well as forty written languages over instant messaging.

To try it out, you’ll need a computer running Windows 8.1 or a current Windows Phone. You can sign up for the preview here. Users of Skype Translator will need to manually activate the feature for each person they speak to in order to hear their conversation automatically translated. The software will also provide an on-screen transcript of the call.

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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.” Read more of this post

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

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. Read more of this post