Posts Tagged ‘neural networks’

How Andrew Ng is Monetizing Deep Learning at Baidu

Baidu logoCade Metz of Wired recently wrote, “Deep learning can do many things. Tapping the power of hundreds or even thousands of computers, this new breed of artificial intelligence can help Facebook recognize people, words, and objects that appear in digital photos. It can help Google understand what you’re saying when you bark commands into an Android phone. And it can help Baidu boost the bottom line. The Chinese web giant now uses deep learning to target ads on its online services, and according to Andrew Ng—who helped launch the deep learning operation at Google and now oversees research and development at Baidu—the company has seen a notable increase in revenue as a result. ‘It’s used very successfully in advertising,’ he says, sitting inside the company’s U.S. R&D center in Sunnyvale, California. ‘We have not released revenue numbers on the specific impact, but it is significant’.” Read more

Red Lamba’s AI-Enabled Security Solution Stands Up To Operational Data Volume And Velocity Challenge

RLRed Lambda, a company spun out of the University of Florida, late last month was recognized by The Software & Information Industry Association (SIIA)’s NextGen program for providing the most innovative security solution. SIIA cited its advances in supercomputing, relational stream processing and artificial intelligence as part of its integrated MetaGrid platform and analytics capabilities as highlights for protecting enterprise data.

The rules approach taken by many antivirus and security information management solutions to root out threats based on what was learned in past breaches has its place. But “Red Lambda wants to identify activity and patterns of activity that can be seen as a breach or potential breach,” says company CTO Dan Nieten.

“One of the things neural networking is very useful for is for deep learning and also dealing with unknowns, and cyber-security world is a world where you have to deal with a lot of unknowns.” To battle threats that get past the first lines of defense, more attention is starting to be paid “to use AI, to apply statistical and machine learning methods in the area of security, to identify breaches,” says Nieten, whose own background is in NLP and machine learning. Read more

Nervana Systems Raises $3.3M for Deep Learning

nervanaDerrick Harris of GigaOM reports, “Nervana Systems, a San Diego-based startup building a specialized system for deep learning applications, has raised a $3.3 million series A round of venture capital. Draper Fisher Jurvetson led the round, which also included Allen & Co., AME Ventures and Fuel Capital. Nervana launched in April with a $600,00 seed round. The idea behind the company is that deep learning — the advanced type of machine learning that is presently revolutionizing fields such as computer vision and text analysis — could really benefit from hardware designed specifically for the types of neural networks on which it’s based and the amount of data they often need to crunch.” Read more

Smarter Enterprise Data with Machine Learning and Cognitive Computing

Watson

Jorge Garcia of Wired recently wrote, “IBM’s recent announcements of three new services based in Watson technology make it clear that there is pressure in the enterprise software space to incorporate new technologies, both in hardware and software, in order to keep pace with modern business. It seems we are approaching another turning point in technology where many concepts that were previously limited to academic research or very narrow industry niches are now being considered for mainstream enterprise software applications. Machine learning, along with many other disciplines within the field of artificial intelligence and cognitive systems, is gaining popularity, and it may in the not so distant future have a colossal impact on the software industry. This first part of my series on machine learning explores some basic concepts of the discipline and its potential for transforming the business intelligence and analytics space.” Read more

Deep Neural Networks Could Help Discover Unique Particles Like Higgs Boson

ucirvine

Derrick Harris of GigaOM reports, “Researchers from the University of California, Irvine, have published a paper demonstrating the effectiveness of deep learning in helping discover exotic particles such as Higgs bosons and supersymmetric particles. The research, which was published in Nature Communications, found that modern approaches to deep neural networks might be significantly more accurate than the types of machine learning scientists traditionally use for particle discovery and might also save scientists a lot of work. To get a sense of how challenging particle discovery is, consider that a collider can produce 100 billion collisions per hour and only about 300 will produce a Higgs boson. Because the particles decay almost immediately, scientists can’t expressly identify them, but instead must analyze (and sometimes infer) the products of their decay.” Read more

Ersatz Labs Hopes to Answer Your Questions with Deep Learning

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Jordan Novet of Venture Beat recently wrote, “A startup called Ersatz Labs wants to help lots of companies intelligently answer lots of questions after reviewing lots of data, just as big tech companies like Google and Netflix do. Toward that end, today Ersatz is launching a cloud service for deep learning, as well as a hardware-software package to run inside companies’ existing facilities. While deep learning services are often geared toward specific uses, like text processing and image recognition, Ersatz makes deep learning available for any type of use.” Read more

New Startup Skymind Offers Support for Open Source Deep Learning

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New Startup Skymind Offers Support for Open Source Deep Learning

 

Derrick Harris of GigaOM reports, “A San Francisco-based startup called Skymind launched on Monday to offer support and services for deeplearning4j, an open source deep learning project it has created. It’s early to tell how much traction deep learning will gain among mainstream companies or even web companies, but the technology does hold a lot of promise. The existence of open source libraries backed by professional services could certainly help spur adoption – especially for a field of data analysis previously relegated to top universities and research labs at companies such as Google, Microsoft, Facebook and Baidu.” Read more

The Strongest Social Assistant in History Microsoft Xiaobing Apprenticed Herself to a Master Crossover

Microsoft strongest social assistant

BEIJING, May 29, 2014 /PRNewswire/ — As one of the most famous crosstalk groups in China, DeYunShe has been renowned for its stringency in accepting apprentices. But on May 29, 2014, crosstalk master Yu Qian unprecedentedly accepted an artificial intelligence (AI) female apprentice social assistant – Microsoft Xiaobing, a 16-year-old girl with an independent manner raised carefully by Microsoft Search Technology Center Asia (STCA). Read more

AlchemyAPI Launches Deep Learning API-Based Service, AlchemyVision

Alchemy API

Derrick Harris of GigaOM reports, “Denver-based startup AlchemyAPI is keeping proactive in the world of artificial intelligence, launching on Monday night a new service that lets users perform computer vision tasks such as image-tagging and photo search via API. The product, called AlchemyVision, is the company’s first foray outside the natural-language processing space where it has focused since 2011. It also probably foreshadows a spate of computer vision services yet to come. AlchemyAPI first demonstrated its object recognition service in September but Turner said the company has done a lot of work in the meantime to get it ready for commercial use. Among the big differences is the sheer scale of the new system, which is running unsupervised across millions of online images and using context from the pages they’re housed on in order to determine what they are.” 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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