Here’s another topic we have been hearing a lot about and it will continue to grow “machine learning”. There have been many articles about the topic and you might be familiar with IBM Watson servers as that is exactly what you have there.
We are talking about processing terabytes here to run algorithms to extract patterns, clusters and to build training models to classify data based on data that has already been captured as a result of prior queries, etc. The program is called Daytona and updated will be scheduled monthly and it is free. The runtime for Windows Azure is free to download.
The applications will be built on Azure, Microsoft’s cloud technology. Groups both inside and outside of Microsoft will have the ability to use.
“Microsoft has developed an iterative MapReduce runtime for Windows Azure, code-named "Daytona." Project Daytona is designed to support a wide class of data analytics and machine learning algorithms. It can scale out to hundreds of server cores for analysis of distributed data.”
“There are a number of use cases for Project Daytona, such as for data analysis, machine learning, financial analysis, text processing, indexing, and search. Almost any application that involves data manipulation and analysis can take advantage of Project Daytona to scale out processing on Windows Azure.”
Additional information can be found here and this is “hard hat” area that mostly developers will understand. Basically this is the Microsoft Cloud technology to be used for handling huge data sets with building on memory with queries and algorithms already used in the system so everyone can benefit from the “machine learning” portions for faster and more concise information. BD
Two years ago, during a cyber infrastructure meeting convened by the U.S. National Science Foundation, principal investigators from across the country found their scientific concerns begin to converge.
“All around the table,” recalls Roger Barga, an architect in Microsoft Research’s eXtreme Computing Group (XCG), “people were saying, ‘I need the means to analyze data,’ or ‘I need a library of analytics that scale out over large data.’”
Barga and his colleagues took note, and in Redmond, Wash., on July 18, the opening day of the 12th annual Microsoft Research Faculty Summit, they provided their response to the scientists’ plea: a platform code-named “Daytona,” designed to expand the tool set for scientists who require large-scale data computation.
“‘Daytona’ has a very simple, easy-to-use programming interface for developers to write machine-learning and data-analytics algorithms,” he says. “They don’t have to know too much about distributed computing or how they’re going to spread the computation out, and they don’t need to know the specifics of Windows Azure.”