Posts Tagged ‘deep learning’

Machine Learning’s Future: Fortune 500 Buys In, Manufacturing Sees The Light

STServerMartin Hack, CEO and co-founder of machine learning company Skytree, has a prediction to make: “In the next three to five years we will see a machine learning system in every Fortune 500 company.” In fact, he says, it’s already happening, and not just among the high-tech companies in that ranking but also among the “bread and butter” enterprises.

“They know they need advanced analytics to get ahead in the game or stay competitive,” Hack says. For that, he says, they need machine learning algorithms for analyzing their Big Data sets, and they need to be able to deploy them quickly and easily — even if those who will be doing the deployments are coming from at best a background of basic analytics and business intelligence.

“There just aren’t enough data scientists to go around,” he says. It’s very tough to fill those roles in most companies, he says, “so like it or not, we have to make it much, much easier for people to digest and use this.”

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Facebook’s DeepFace Matches Faces Almost as Well as Humans

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Tom Simonite of the MIT Technology Review reports, “Asked whether two unfamiliar photos of faces show the same person, a human being will get it right 97.53 percent of the time. New software developed by researchers at Facebook can score 97.25 percent on the same challenge, regardless of variations in lighting or whether the person in the picture is directly facing the camera. That’s a significant advance over previous face-matching software, and it demonstrates the power of a new approach to artificial intelligence known as deep learning, which Facebook and its competitors have bet heavily on in the past year.” Read more

Plumbing The Depths Of Deep Learning

Image Courtesy: Flickr/ Hey Paul Studios

Image Courtesy: Flickr/ Hey Paul Studios

Will deep learning take us where we want to go? It’s one of the questions that Oxford University professor of Computational Linguistics Stephen Pulman will be delving into at this week’s Sentiment Analysis Symposium. There, he’ll be participating in a workshop session today on compositional sentiment analysis and giving a presentation tomorrow on bleeding-edge natural language processing.

“There is a lot of hype about deep learning, but it’s not a magic solution,” says Pulman. “I worry whenever there is hype about some technologies like this that it raises expectations to the point where people are bound to be disappointed.”

That’s not to imply, however, that important progress isn’t taking place when it comes to deep learning, which leverages machine learning methods based on learning representations with applications to everything from NLP to computer vision to speech recognition.

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Google Buys DeepMind Technologies, Growing Its Deep Learning Portfolio And Expertise

deepmindGoogle’s letting the cash flow. Fresh off its $3.2 billion acquisition of “conscious home” company Nest, which makes the Nest Learning Thermostat and Protect smoke and carbon monoxide detector, it’s spending some comparative pocket change — $400 million – on artificial intelligence startup DeepMind Technologies.

The news was first reported at re/code here, where one source describes DeepMind as “the last large independent company with a strong focus on artificial intelligence.” The London startup, funded by Founders Fund, was founded by Demis Hassabis, Shane Legg and Mustafa Suleyman, with the stated goal of combining machine learning techniques and neuroscience to build powerful general purpose learning algorithms.

Its web page notes that its first commercial applications are in simulations, e-commerce and games, and this posting for a part-time paid computer science internship from this past summer casts it as “a world-class machine learning research company that specializes in developing cutting edge algorithms to power massively disruptive new consumer products.”

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Hello 2014 (Part 2)

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Courtesy: Flickr/faul

Picking up from where we left off yesterday, we continue exploring where 2014 may take us in the world of semantics, Linked and Smart Data, content analytics, and so much more.

Marco Neumann, CEO and co-founder, KONA and director, Lotico: On the technology side I am personally looking forward to make use of the new RDF1.1 implementations and the new SPARQL end-point deployment solutions in 2014 The Semantic Web idea is here to stay, though you might call it by a different name (again) in 2014.

Bill Roberts, CEO, Swirrl:   Looking forward to 2014, I see a growing use of Linked Data in open data ‘production’ systems, as opposed to proofs of concept, pilots and test systems.  I expect good progress on taking Linked Data out of the hands of specialists to be used by a broader group of data users.

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Hello 2014

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Courtesy: Flickr/Wonderlane

Yesterday we said a fond farewell to 2013. Today, we look ahead to the New Year, with the help, once again, of our panel of experts:

Phil Archer, Data Activity Lead, W3C:

For me the new Working Groups (WG) are the focus. I think the CSV on the Web WG is going to be an important step in making more data interoperable with Sem Web.

I’d also like to draw attention to the upcoming Linking Geospatial Data workshop in London in March. There have been lots of attempts to use Geospatial data with Linked Data, notably GeoSPARQL of course. But it’s not always easy. We need to make it easier to publish and use data that includes geocoding in some fashion along with the power and functionality of Geospatial Information systems. The workshop brings together W3C, OGC, the UK government [Linked Data Working Group], Ordnance Survey and the geospatial department at Google. It’s going to be big!

[And about] JSON-LD: It’s JSON so Web developers love it, and it’s RDF. I am hopeful that more and more JSON will actually be JSON-LD. Then everyone should be happy.

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IBM Checks off Its 2014 Big Data in Education Prediction

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Barb Darrow of GigaOM reports, “On Monday, IBM, as part of its annual 5 in 5  extravaganza, predicted that cloud-based cognitive technology would personalize education for students within five years. Fast forward three days, and voila! IBM unveiled a research project to bring machine learning, predictive modeling and deep content analytics to deliver on that promise. Talk about gaming the system. IBM is working with Georgia’s Gwinnett County Public Schools (GCPS) system to test out the technology and its thesis that the application of big data analytics and deep learning — which looks at connections and context in different types of data- – can help students learn better. The 12-month project kicked off in September and focuses on 5th and 6th grade math students, said an IBM spokesman.” Read more

Bing Turns to Deep Learning to Improve Image Search

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Zach Walton of Web Pro News recently wrote, “Image search is a cornerstone of any search engine. That’s why both Google and Bing are doing everything they can to improve image search to bring up the most relevant images for any search imaginable. While some may argue that recent changes made to Google image search make it worse, Bing is moving ahead with a new strategy that involves deep learning. So, what is deep learning? In short, it’s a type of machine learning that uses artificial neural networks to learn about and understand multiple concepts, including the abstract. In the past, computer systems had to be manually ‘trained’ to recognize patterns or specific images. With machine learning, these systems can now learn to recognize these patterns on their own. When it comes to image search quality, Bing found that integrating deep learning into its systems greatly increased the quality.” Read more

Facebook is Getting Serious About Semantic Technologies

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Bianca Bosker of the Huffington Post reports, “Facebook’s new AI team made 1.2 trillion comments and status updates searchable. Our more than 1 trillion social connections can now also be mined with queries like, ‘friends of friends who are single in San Francisco.’ On Wednesday, Zuckerberg made clear these kinds of cute searches are just the appetizer. He wants people to be able to ‘easily ask any question to Facebook and get it answered.’ (Emphasis added.) This first requires getting to know us better. Read more

Facebook Launches AI Effort to Find Meaning in Posts

Facebook

Tom Simonite of the MIT Technology Review reports, “Facebook is set to get an even better understanding of the 700 million people who use the social network to share details of their personal lives each day. A new research group within the company is working on an emerging and powerful approach to artificial intelligence known as deep learning, which uses simulated networks of brain cells to process data. Applying this method to data shared on Facebook could allow for novel features and perhaps boost the company’s ad targeting. Deep learning has shown potential as the basis for software that could work out the emotions or events described in text even if they aren’t explicitly referenced, recognize objects in photos, and make sophisticated predictions about people’s likely future behavior.” Read more

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