IBM Watson Runs a Food Truck?!

What to do after winning Jeopardy against the world’s best players?  Open a food truck, of course!  Yes, that Watson is now running a food truck, and apparently it creates some truly delicious dishes!  Confused?  Don’t be.  The intelligence behind the Watson engine that successfully answered hundreds of randomized Jeopardy questions is now the creative engine behind a gourmet food truck.  IBM is endeavoring to show that predictive analytics have uses in the most unusual of places!

As with most predictive analytics, there is still an important role for humans to play in providing balance, judgment and expertise.  Watson does  the data-crunching heavy lifting to find interesting and appealing flavor combinations, faster (better?) than human beings can do on their own, and then trained chefs implement the Watson directions.

This hybrid approach should have a familiar ring to it.  Let the software do the hard, data-intensive number-crunching and then marry that output with human skill and finesse.  It’s a winning combination and one that we employ here at Valora every day.  We utilize our analytics, indexing, and rules platform, PowerHouse, to organize, catalog and find relationships in content for us and then we add the human skill, the expertise, to refine the output and do custom things for specific projects.  

Here’s an example:  We run 50,000 emails and attachments through PowerHouse, which quickly finds well over 150 attributes about each item.  Then we ask PH to find important relationships and insights, such as trend data or topic clusters.  From there, we adapt the rules programming to customize the output so it yields middle initials, or zip + 4, or the top 3 issues per document, or whatever it is that any particular customer needs.  Load it up to BlackCat for easy, online review (often by the client’s workforce) and we’re done.  Predictive analytics mastery!

Now, if you’ll excuse me, I think pork belly moussaka sounds amazing!

Statistical Pattern Matching Accurately Predicts Presidential Winners and Electoral College Counts, Why Not Privilege and Responsiveness in Litigation?

The technology utilized by political statisticians is finally getting the attention it deserves.  Not because it is partisan, but because it is accurate.  The excellent article in today’s LA Times explains how mathematical models predicted the election outcome well before the first polls had opened. How? By taking the information from numerous sample sets and re-modeling over and over again with different assumptions and weightings. If this sounds a lot like statistical sampling and pattern-matching, then you have been paying attention! The techniques used by the Nate Silvers of the world to classify and label voting patterns are being used right now in litigation to “predict” (or diagnose, if you prefer) for privilege, responsiveness and issues.

At Valora, we call this technique Probabilistic Hierarchical Context-Free Grammars, but others have shortened it to Statistical Pattern Matching, which works just fine. The point is that information about documents (or voter behavior or music choices) has been available for a long time. The only missing piece is the human comfort level with statistics and probabilistic systems.

If the statisticians can call elections, baseball winners and consumer preferences, isn’t it time we let them loose onto document analysis and review? If you’d like a primer on or a demonstration of Probabilistic Hierarchical Context-Free Grammars in litigation, contact us at valoratech.com.