Jeffrey Schwartz of Redmond Magazine recently wrote, “Nearly a year after launching its Hadoop-based Azure HDInsight cloud analytics service, Microsoft believes it’s a better and broader solution for real-time analytics and predictive analysis than IBM’s widely touted Watson. Big Blue this year has begun commercializing its Watson technology, made famous in 2011 when it came out of the research labs to appear and win on the television game show Jeopardy. Both companies had a large presence at this year’s Strata + Hadoop World Conference in New York, attended by 5,000 Big Data geeks. At the Microsoft booth, Eron Kelly, general manager for SQL Server product marketing, highlighted some key improvements to Microsoft’s overall Big Data portfolio since last year’s release of Azure HDInsight including SQL Server 2014 with support for in-memory processing, PowerBI and the launch in June of Azure Machine Learning.” Read more
Predixion Software Removes Barriers to Deployment of Predictive Analytics With Release of Predixion Insight 4.0
NEW YORK, NY–(Marketwired – Oct 15, 2014) – Strata + Hadoop World, Booth #103 -Predixion Software, a developer of cloud-based predictive analytics software, today released Predixion Insight 4.0, the latest version of its powerful predictive analytics platform. The new release expedites the deployment of predictive analytics directly to the point of front-line decisions, and expands predictive capabilities across a wider variety of production environments, such as applications, databases, data stores, real-time engines, devices and machines. By removing barriers to deploying predictive analytics, Predixion Insight 4.0 enables companies to achieve the full potential of their data investments. Read more
Jordan Novet of Venture Beat reports, “Many people know Google first and foremost as a search engine company. But really it’s a machine-learning company, using data to make predictions that get incorporated into applications like search and advertising without people even realizing it. Today Google is announcing in a blog post that people can now choose to apply its machine-learning savvy to Google Sheets, the company’s spreadsheet app, to make educated guesses and fill in blank cells. This applied use of machine learning follows Microsoft’s recent announcement of a cloud-based service for that purpose, Azure Machine Learning.” Read more
Serdar Yegulalp of InfoWorld reports, “Those who have been chomping at the bit to use IBM’s Watson machine-intelligence service with their apps need gnaw no longer. Watson APIs are now available for public use, albeit only through IBM’s Bluemix cloud services platform. IBM’s Watson Developer Cloud now offers eight services for building what IBM describes as cognitive apps, with more services promised later on.” Read more
NEW YORK – 07 Oct 2014: IBM is announcing significant milestones fueling adoption of Watson and cognitive computing cloud capabilities on a global scale. Watson is a groundbreaking platform that represents a new era of computing based on its ability to interact in natural language, process vast amounts of Big Data to uncover patterns and insights, and learn from each interaction.
On Tuesday, October 7, IBM Watson Group Senior Vice President Mike Rhodin demonstrates Watson at work in its Client Experience Center at its new global headquarters at 51 Astor Place in New York City’s Silicon Alley. Read more
Sophie Curtis of The Telegraph reports, “Today a new artificial intelligence computing system has been unveiled, which promises to transform the global workforce. Named ‘Amelia’ after American aviator and pioneer Amelia Earhart, the system is able to shoulder the burden of often tedious and laborious tasks, allowing human co-workers to take on more creative roles. ‘Watson is perhaps the best data analytics engine that exists on the planet; it is the best search engine that exists on the planet; but IBM did not set out to create a cognitive agent. Read more
Cade Metz of Wired reports, “When Google used 16,000 machines to build a simulated brain that could correctly identify cats in YouTube videos, it signaled a turning point in the art of artificial intelligence. Applying its massive cluster of computers to an emerging breed of AI algorithm known as ‘deep learning,’ the so-called Google brain was twice as accurate as any previous system in recognizing objects pictured in digital images, and it was hailed as another triumph for the mega data centers erected by the kings of the web.” Read more
John Boyd of IEEE Spectrum reports, “With satellite, cable, and terrestrial TV stations broadcasting in the hundreds and Internet-based entertainment content companies also competing for viewers’ attention, finding something to watch is, strangely, a growing challenge. To help simplify the task, researchers at Japan’s public TV and radio broadcaster Nippon Hoso Kyokai, better known as NHK, plan to begin testing technology to automatically assess in real time a viewer’s interest in a TV program or video and then suggest other programs to watch based on the results.” Read more
A recent announcement on EurekAlert! states: “Researchers from North Carolina State University have developed artificial intelligence (AI) software that is significantly better than any previous technology at predicting what goal a player is trying to achieve in a video game. The advance holds promise for helping game developers design new ways of improving the gameplay experience for players.”We developed this software for use in educational gaming, but it has applications for all video game developers,” says Dr. James Lester, a professor of computer science at NC State and senior author of a paper on the work. “This is a key step in developing player-adaptive games that can respond to player actions to improve the gaming experience, either for entertainment or – in our case – for education.” The researchers used “deep learning” to develop the AI software. Deep learning describes a family of machine learning techniques that can extrapolate patterns from large collections of data and make predictions. Deep learning has been actively investigated in various research domains such as computer vision and natural language processing in both academia and industry.”
Apigee wants the development community to be able to seamlessly take advantage of predictive analytics in their applications.
“One of the biggest things we want to ensure is that the development community gets comfortable with powering their apps with data and insights,” says Anant Jhingran, Apigee’s VP of products and formerly CTO for IBM’s information management and data division. “That is the next wave that we see.”
Apigee wants to help them ride that wave, enabling their business to better deal with customer issues, from engagement to churn, in more personal and contextual ways. “We are in the business of helping customers take their digital assets and expose them through clean APIs so that these APIs can power the next generation of applications,” says Jhingran. But in thinking through that core business, “we realized the interactions happening through the APIs represent very powerful signals. Those signals, when combined with other contextual data that may be in the enterprise, enable some very deep insights into what is really happening in these channels.”
With today’s announcement of a new version of its Apigee Insights big data platform, all those signals generated – through API and web channels, call centers, and more – can come together in the service of predictive analytics for developers to leverage.
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