Machine Learning Changes the Way We Learn from Data
October 26, 2016
The technology blog post from Danial Miessler titled Machine Learning is the New Statistics strives to convey a sense of how crucial Machine Learning has become in terms of how we gather information about the world around us. Rather than dismissing Machine Learning as a buzzword, the author heralds Machine Learning as an advancement in our ability to engage with the world around us. The article states,
So Machine Learning is not merely a new trick, a trend, or even a milestone. It’s not like the next gadget, instant messaging, or smartphones, or even the move to mobile. It’s nothing less than a foundational upgrade to our ability to learn about the world, which applies to nearly everything else we care about. Statistics greatly magnified our ability to do that, and Machine Learning will take us even further.
The article breaks down the steps of our ability to analyze our own reality, moving from randomly explaining events, to explanations based on the past, to explanations based on comparisons with numerous trends and metadata. The article positions Machine Learning as the next step, involving an explanation that compares events but simultaneously progresses the comparison by coming up with new models. The difference is of course that Machine Learning offers the ability of continuous model improvement. If you are interested, the blog also offers a Machine Learning Primer.
Chelsea Kerwin, October 26, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Search Vendor RAVN Systems Embraces Buzzwords
February 19, 2016
The article titled RAVN Systems Releases RAVN ACE for Automated Data Extraction of ISDA Documents Using Artificial Intelligence on BobsGuide details the needs of banks and other members of the derivatives market. Risk mitigation leads to ongoing negotiations that result in major documentation issues to keep up with the changes. The article explains how RAVN has met these challenges,
“RAVN ACE can extract the structure of the agreement, the clauses and sub-clauses, which can be very useful for subsequent re-negotiation purposes. It then further extracts the key definitions from the contract, including collateral data from tabular formats within the credit support annexes. All this data is made available for input to contract or collateral management and margining systems or can simply be provided as an Excel or XML output for analysis.”
Not only does RAVN ACE do the work in a fraction of the amount of time it would take a person, the output is also far more accurate, always good news when handling legal documents. The service also includes an audit service that compares terms from the documents with the manual abstraction. By doing so, RAVN ACE is able to analyze the risks and even estimate the amount of negotiating necessary to complete the contract.
Chelsea Kerwin, February 19, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Hello, Big Algorithms
January 15, 2016
The year had barely started and it looks lime we already have a new buzzword to nestle into our ears: big algorithms. The term algorithm has been tossed around with big data as one of the driving forces behind powerful analytics. Big data is an encompassing term that refers to privacy, security, search, analytics, organization, and more. The real power, however, lies in the algorithms. Benchtec posted the article, “Forget Big Data-It’s Time For Big Algorithms” to explain how algorithms are stealing the scene.
Data is useless unless you are able to are pull something out of it. The only way get the meat off the bone is to use algorithms. Algorithms might be the powerhouses behind big data, but they are not unique. The individual data belonging to different companies.
“However, not everyone agrees that we’ve entered some kind of age of the algorithm. Today competitive advantage is built on data, not algorithms or technology. The same ideas and tools that are available to, say, Google are freely available to everyone via open source projects like Hadoop or Google’s own TensorFlow…infrastructure can be rented by the minute, and rather inexpensively, by any company in the world. But there is one difference. Google’s data is theirs alone.”
Algorithms are ingrained in our daily lives from the apps run on smartphones to how retailers gather consumer detail. Algorithms are a massive untapped market the article says. One algorithm can be manipulated and implemented for different fields. The article, however, ends on some socially conscious message about using algorithms for good not evil. It is a good sentiment, but kind of forced here, but it does spur some thoughts about how algorithms can be used to study issues related to global epidemics, war, disease, food shortages, and the environment.
Whitney Grace, January 15, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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