Amazon.com is looking for a Research Scientist, Social Shopping Technology and Machine Learning in Seattle, WA. The post states, “Amazon needs a seasoned research scientist to join customer reviews development team in Seattle, WA. We own Amazon’s famous Customer Reviews – one of the world’s largest community driven products. User contributed reviews are a tremendously visible aspect of Amazon’s brand and a key competitive advantage. Millions of shoppers use customer reviews every day to make buying decisions through our global websites and mobile apps. This translates to a direct impact to Amazon’s core business and customer experience… You’re a scientist looking for a career where you’ll be able to lead, to deliver, and to influence. Read more
Posts Tagged ‘Machine Learning’
Juan Carlos Perez of InfoWorld reports, “Microsoft will add new software, developer tools and capabilities to Office 365 in an attempt to make the cloud applications suite a ‘smarter’ product that is better at helping people interact at work. At its SharePoint Conference, which kicks off in Las Vegas on Monday, Microsoft will demonstrate a new machine learning application code-named Oslo designed to understand how employees work in Office 365 and with whom. Oslo will base its insights on a variety of signals gleaned from how people use Office 365′s components, like Exchange Online for email, OneDrive for Business for storage, Lync Online for IM and video conferencing, SharePoint Online for team collaboration and Yammer for enterprise social networking. Microsoft calls this information the Office Graph.” Read more
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.
John Koetsier of Venture Beat reports, “Some sites are stupid. They don’t know you; they don’t know what you like; and they don’t know what you want. Even if you’re among the tiny six percent of visitors that log in, the site is the site is the site. ‘Unless you put the $4 billion a year that Amazon puts into its technology, you end up with a pretty dumb site,’ Joelle Kaufman, BloomReach’s head of marketing and partnerships, told me yesterday. ‘We use technology to unlock that potential and make every web experience — mobile, tablet, desktop — oriented around the individual and their need at that moment.’” Read more
TORONTO, Feb. 26, 2014 (Menafn – Canada NewsWire via COMTEX) — Sprylogics International Corp. (“Sprylogics”) , a technology provider of local mobile search and messaging solutions for consumers and businesses has signed an agreement with Keek, a mobile video app, to collaborate and explore sharing technology and expertise around a broad segment of cross-platform opportunities, including the deployment of Sprylogics’ semantic processing engine into Keek’s mobile platform. As part of this agreement, Sprylogics will provide semantic content analysis to Keek, including exploring utilizing the indexing and search services in Sprylogics, core infrastructure, and Natural Language Processing capabilities, as well as various machine learning classifiers, semantic and local search technologies available through Sprylogics APIs and distributed content infrastructure. Read more
RT News recently shared the ponderings of artificial intelligence expert Ray Kurzweil. The article begins, “Most people would probably agree that computers are man-made technologies that function inside the strict boundaries of man-made borders. For technologists like Google engineering director Ray Kurzweil, however, the moment when computers liberate themselves from their masters will occur in our lifetime. By the year 2029, computers and robots will not only have surpassed their makers in terms of raw intelligence, they will understand us better than we understand ourselves, the futurist predicts with enthusiasm. Kurzweil, 66, is the closest thing to a pop star in the world of artificial intelligence, the place where self-proclaimed geeks quietly lay the grid work for what could be truly described as a new world order.” Read more
Stephen Wolfram Demos Knowledge-Based Programming Language As It Approaches Official Release (Video)
Stephen Wolfram is talking more publicly about the Wolfram Language, this week releasing a video demo of the knowledge-based programming language. As he describes in the video below, the symbolic language builds in a vast amount of knowledge of how to do computations and about the world itself. “Through symbolic structure of the language,” he says, primitives for everything from processing images to looking up stock prices “are all set up to work together in a wonderfully coherent way.”
The concept of coherence – the idea that everything in the language must fit together – is in fact one of the principles that have guided the development of the language over the past decades, he explains, as is maximum automation – the idea that the language should take care of as much as possible. If you are working in machine learning, for example, and want to build a data classifier, “in the Wolfram Language there’s just one Super Function, Classify, that’s packed with meta-algorithms to automatically figure out what to do,” he says. There are thousands of Super Functions in the language, he says, which “effectively give you the highest possible level of building blocks for programs.”
These building blocks contain not only algorithms but knowledge and data, too, including knowledge about how to import and export formats and interact with external APIs and huge amounts of curated computable data – the same data that powers Wolfram Alpha, completely programmatically accessible, he says. Ask it when the sun will set today, and you’ll get the answer for your current location, for instance.
Machine learning is playing a role in fraud prevention: This week Versium launched its Predictive FraudScore solution to help companies weed out fraudsters from signing up for their services or conducting ecommerce transactions with them. All the organization needs is an email address.
The solution is based on Versium’s LifeData predictive analytics platform that also is behind the company’s churn, social influencer, shopper and custom scoring products. “There are three fundamental areas we bring to fraud scoring: unique data, powerful matching technology to identify and associate that data to accounts or consumers as they sign up, and applying machine learning to that unique data set to predict whether that account is likely to be associated with fraud or not,” says Versium’s CEO Chris Matty.
The FraudScore service provides an enterprise a very strong indication of whether a person is legitimately interfacing with it at the point in time that that entity registers with the company. “That’s quite upstream from where normal fraud prediction takes place,” Matty says.
Deborah Todd of the Pittsburgh Post-Gazette reports, “An initiative to use Yahoo’s data and Carnegie Mellon University’s brain trust to build the smartphone apps of the future has launched with a multimillion-dollar jump start. Project InMind — a five-year, $10 million partnership between CMU and multinational Internet corporation Yahoo Inc. — gives university researchers access to a “mobile toolkit” of Yahoo’s real-time data services and its infrastructure in order to advance machine learning and personalization of smartphone apps. Once new experimental mobile products are created, students and faculty on campus will be able to opt in as alpha testers. The goal is to create customized services able to anticipate users’ needs and interests on an ongoing basis, whether a user is at home playing video games or navigating the streets of a foreign country.” Read more
Greg Jarboe of Search Engine Watch reports, “The top four U.S. online video content properties in comScore’s December 2013 U.S. online video rankings are well-known brand names: Google sites, driven primarily by video viewing at YouTube; Facebook; AOL; and Yahoo sites. But digital marketers can be forgiven if they aren’t as familiar with the fifth largest property, NDN. NDN ranks ahead of Amazon sites, VEVO, Microsoft sites, Vimeo, and Turner Digital in the latest online video rankings. So, it’s worth knowing more about an online video platform that says it ‘is disrupting the digital media industry in all the right ways.’ Search Engine Watch (SEW) interviewed Stephen Bach (SB), the head of Business Development at NDN.” Read more
NEXT PAGE >>