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Interset UTM Brings Machine Learning to Network Security Policy Best Practices


Unified threat management (UTM) is a critical component of modern network security policy best practices, and those in the market for a new UTM would do well to check out Interset, a threat management platform that combines Machine Learning (ML) with a Big Data architecture to identify potential threats that would otherwise go undetected. Interset uses extensive data ingestion capabilities that correlate events/activities with entities to determine the level of risk that is being encountered at any given time. Modern network security policy best practices include the use of Big Data analytics to harvest and examine ostensibly unrelated bits of data to find relationships and expose trends that lead to predictions of risky or bad behaviors. Interset does so in a different fashion than most threat mitigation products. Interset ingests multiple data sources related to the movement of data across (or inside) of the network, while also gathering information about the entities involved.

News: ONR Researchers Create 'Human User Manual' for Robots - Office of Naval Research


ARLINGTON, Va.--With support from the Office of Naval Research (ONR), researchers at the Georgia Institute of Technology have created an artificial intelligence software program named Quixote to teach robots to read stories, learn acceptable behavior and understand successful ways to conduct themselves in diverse social situations. "For years, researchers have debated how to teach robots to act in ways that are appropriate, non-intrusive and trustworthy," said Marc Steinberg, an ONR program manager who oversees the research. "One important question is how to explain complex concepts such as policies, values or ethics to robots. Humans are really good at using narrative stories to make sense of the world and communicate to other people. This could one day be an effective way to interact with robots."

ND4J User Guide N-Dimensional Scientific Computing for Java


This user guide is designed to explain (and provide examples for) the main functionality in ND4J. It is still a work in progress. An NDArray is in essence n-dimensional array: i.e., a rectangular array of numbers, with some number of dimensions. In terms of indexing there are a few things to know. First, rows are dimension 0, and columns are dimension 1: thus INDArray.size(0) is the number of rows, and INDArray.size(1) is the number of columns. Like normal arrays in most programming languages, indexing is zero-based: thus rows have indexes 0 to INDArray.size(0)-1, Throughout this document, we'll use the term NDArray to refer to the general concept of an n-dimensional array; the term INDArray refers specifically to the Java interface that ND4J defines.

Shifting from Big Data to Machine Learning: Lessons Learned


Arvid Tchivzhel, Director of Product Development, Mather Economics, Arvid Tchivzhel, a director with Mather Economics oversees the delivery and operations for all Mather Economics consulting engagements, along wit... The old adage is as true as ever in the world of open source technology: "Those who do not learn history are doomed to repeat it." Numerous surveys, articles, listicles and case studies address best practices for companies wishing to implement a Big Data project and make a return on their investment. Machine learning is the new buzzword to take hold among executives (and in the marketing materials of enterprise consultants). Before plunging into the world of machine learning, firms should pause and learn from the mistakes made in the implementation of Big Data projects over the last five years.

Talking To Our Computers Is Changing Who We Are

Huffington Post - Tech news and opinion

On Wednesday, Google introduced its new personal assistant, Google Home, which will listen to your voice and provide information on demand, much like the popular Amazon Echo. Apple's Siri and Microsoft's Cortana have been chatting with people for years -- and one expert predicts that voice-driven technology will have startling effects on our social interactions moving forward. "There used to be a disconnect between how we interacted with, say, our desktop computers and our family," Illah Nourbakhsh, a professor of robotics at Carnegie Mellon University, told The Huffington Post. "We interacted with that computer only when we wanted to. Now technology is pervading the home environment.