Alex Philp, Founder/CTO of TerraEchos
MONTANA MAY SEEM AN UNLIKELY place for cutting-edge sensor systems and computational solutions to the big data problem, but there is a cluster of companies with Alex Philp at the helm that are on the forefront of that problem space. Matt Ball spoke with Philp about GCS Research, Adelos and TerraEchos, as well as the trends with systems and sensors that are giving rise to a whole new awareness of our interactions.
BALL I find it inspiring how you’ve made a transition from academic research to an entrepreneur, where you’ve founded several successful companies. What’s the history of how that came about?
PHILP I entered the University of Montana grad school here in Missoula (Montana) in 1992, and my Masters was in geography with an emphasis on GIS (geographic information systems). I started my doctorate in historical landscape ecology using GIS and remote sensing, and halfway through that I had an opportunity to work at the Goddard Space Flight Center on the convergence between remote sensing data types, satellite-derived data products, and GIS, as it was becoming early Web-enabled. We built a great team of people who were active between 1998 and 2002.
As part of that four-year process, my doctorate essentially shifted into telling geographic stories in a meaningful way to support business process or educational experience. I tied that all around the Lewis and Clark Bicentennial and developed that map story with systems within systems within systems that were doing much of what is called the cloud now. We had geospatial distributed analytics, distributed systems, map services, and terabytes of data spread across machines to educate and tell that story. That was all fairly applied GIS research.
I started GCS Research in 2002, and very early on I was able to bring in outstanding business partners. Mike Beltz and John Waterman, two GIS people from the University of Montana, became partners in GCS Research, and we built that company into what it is today.
BALL When did you branch into sensors?
PHILP I started to think about sensors everywhere after working with sensors on satellites and aircraft. It wasn’t news to me that we’d have an explosion in mobile GPS. I became very interested in sensors, and sensored systems, and elements of the sensor Web. I had an opportunity to work with the Navy on a project with a very high-end fiber-optic sensor. Think of it as thousands of microphones buried in the ground, using fiber-optic cable to support those digital sensors.
I describe the opportunity as the '3Vi over network equation' – that is, the convergence of high volume, high velocity, high variety (3V) with the exponent of intelligence, over network.
We licensed that technology from the government and formed a new company called TerraEchos to focus on that activity in 2006. By 2008, we had our first prototype, and then through 2011, we were building and delivering systems to the U.S. government, working with the Navy and the Department of Energy.
We were doing next-generation physical security, the idea being that you need to create a physical perimeter using five or six different types of sensors – cameras, microphones, geophones, magnetometers, biometric arrays, millimeter wave radar, airborne assets... As our work evolved, I realized that it wasn’t enough to focus on just our sensor system, but that we needed to interoperate and interact in real time, both spatially and temporally, in identifying, classifying, tracking and localizing that threat. We started extending and expanding that into Adelos, which is the Greek word for hidden. We proved some phenomenal things with that system, and gained some recognition for it.
BALL Getting recognized by IBM is certainly a validation of a high order in terms of your technical expertise. How did the alliance with IBM come about?
PHILP I became aware of an IBM technology that they referred to as "System S," and if you recall that their original code name for the first relational database management system (RDBMS) was "System R," then it’s pretty significant. The technology is now known as InfoSphere Streams, which is a paradigm shift in how we do computing.
I’m interested in associative memory and analytics that lead to synthetic solutions, theoretically, conceptually or otherwise. You have multiple sources, you do interdisciplinary calculations, you do computationally intensive work in real time, and what comes out are answers that provide automated and semi-automated predictions and decision support. All of that we were doing around Adelos, and we achieved some major success in 2010 and 2011, to the extent that we earned significant industry awards from IBM and others based on the innovation.
BALL How have you capitalized on all the recognition?
PHILP We were interested in going somewhere with this analytical capability, so venture capital investors took a serious look and we created a whole new company just around the central nervous system of Adelos. We literally ripped the cerebral cortex out, and named that product Kairos, the Greek word for right timing. We take data from multiple sources – some of it is big, some is slow, some is small, some is structured, some is unstructured, some is video, some is text, some is audio, etc. – and we bring all that together into an associative and correlative processing engine.
BALL Is geospatial an input to the Kairos "big data in motion" product?
PHILP It is and it isn’t. What we’re trying to figure out right now is where your standard geographic information system begins and ends, and where does Kairos begin and end? As you know, your traditional geographic information systems, with classic database-driven GIS, are not very good at dealing with these kind of compute problems. I’ve been working for years on trying to inject sensor systems into GIS, and to greater and less success. We’ve been doing that over and over again for customers.
The best thing I can say is that we pull data from GIS technology, primarily Esri, whether it is a file, a table or a database as a source, and we write and publish back to the source. We’re pulling what’s meaningful and necessary from GIS as part of our calculation, and then, when we have an answer, we put the answer back into GIS to support those workflows and systems. We’re not trying to make a GIS analytics fusion machine; we’re trying to find the right interoperability at a technical level with reading and writing the right raster, vector and record as part of a service.
BALL There seem to be so many opportunities. How do you go about focusing on specific industries or problems?
PHILP To make sense and to extract meaning today requires the right combination of software, hardware, analytics and network. I describe the opportunity as the "3Vi over network equation" – that is, the convergence of high volume, high velocity, high variety (3V) with the exponent of intelligence, over network. This is the kind of equation that we’re creating with Kairos. What we’re working to identify are specific industries that are hitting the wall on velocity, variety, volume, analytics or network, and we’re trying to bring our solutions to them to achieve 100 to 1,000 to even 10,000-fold improvements on optimization.
Primarily it’s about saving time. If my problem currently takes me 34 seconds, and if I can derive that value in one one-thousandth of a second, now we’re really starting to buy time. We’re starting to manipulate time for existing and past functions, and to do a better job of reacting. But, we don’t just want to react better, we want to be more proactive for our customers.