Catching up with Stephen DeAngelis, CEO of NJ company Massive Dynamics and Newtown, PA’s Enterra Solutions
Stephen F. DeAngelis, a leading authority on artificial intelligence systems, will lend his expertise to the growing area of cognitive reasoning technology at Princeton University.
DeAngelis was recently appointed as a visiting professional executive at the university’s department of chemistry, where he will work in the laboratory of Professor Herschel A. Rabitz with researchers and other university faculty members to study applications of cognitive computing.
DeAngelis, CEO of Princeton-based Massive Dynamics and Newtown, Pennsylvania-based Enterra Solutions, both specializing in artificial intelligence systems, will also be involved in examining how high dimensional model representation (HDMR) can be used to improve the efficiency of cognitive reasoning platforms. HDMR is comprised of a set of mathematical techniques used for improving the efficiency of deduction and learning involved in the high-dimensional input and output behavior of complex systems.
“I am pleased to have Stephen DeAngelis in this close working relationship with Professor Rabitz,” said Professor Pablo G. Debenedetti, Princeton University Dean for Research, in a press release. “I am also pleased that he will have the opportunity to interact with other faculty in the sciences and engineering to make his presence in the Rabitz Lab most valuable for all parties.”
DeAngelis commented that the technologies at both of his companies, combined with the university’s work in HDMR, “create an ideal testing ground for the advancement of basic computational concepts while also being of intellectual value to laboratory researchers.”
Massive Dynamics is a bespoke applied mathematics company focused on the analysis and control of complex systems through the use of a sophisticated mathematics engine and design-of- analysis approach. Enterra is a cognitive computing company that combines artificial intelligence (semantic reasoning and ontologies), sophisticated mathematics and natural language processing.
Founded in 2014, Massive Dynamics is located in Princeton to benefit from the proximity of Princeton University, especially from research interactions with the university. Most of the employees at Massive Dynamics are Ph.D.s who received their academic degrees from Princeton in applied mathematics or related fields. Enterra is located in Newtown because of the proximity to DeAngelis’ residence.
DeAngelis’ appointment follows a long and illustrious career in the field of cognitive computing.
His idea of launching an artificial intelligence system for companies to provide them with a better understanding of their customers and, hopefully, to improve their bottom-lines can be traced back to one of the darkest and deadliest days in U.S. history.
On September 11, 2001, DeAngelis’ sister was working in a building flanking the World Trade Center complex when planes hijacked by terrorists crashed into the two towers. His sister fortunately escaped unharmed from her office building on that “highly traumatic day,” DeAngelis recalled.
But that tragic event led DeAngelis to wonder if the massive death and destruction that day could have been prevented if government agencies had regularly shared information on potential terrorist plots and other threats to the nation’s security.
At that time, DeAngelis had a technology consulting company called “Enterra Strategies,” but changed that name to the current one shortly after the WTC attack, signaling a switch in its focus to technology designed to improve the government’s ability to analyze and share security-related data.
Back then, the government had a “connect-the-dots problem” when exchanging information on security-related matters, said DeAngelis. “I decided it would be a good thing to embark upon a business used for information-security applications.”
Five years ago, Enterra decided that its advanced cognitive computing system could also help other industry sectors, such as consumer goods, retail, financial services, life sciences and chemicals. Enterra’s specialty of making sense from mountains of disparate data seemed to be needed for these businesses — all ripe for disruption.
Enterra’s cognitive computing and data-driven analytics allows organizations to capture, curate and analyze data, and provides them with the best ways to use this information to create efficiencies in their operations, or to make machines think more like humans.
Enterra’s cognitive computing platform, called the “Enterra Enterprise Cognitive System,” produces insightful analyses of high volumes of data that allow companies to more effectively launch new products or services, improve customer engagement or fine-tune marketing strategies.
The technology uses mathematical and statistical analysis combined with artificial intelligence to create “an efficient and meaningful approach” to analyzing vast amounts of data, DeAngelis said.
One Enterra client, spice-making giant McCormick & Company, is using Enterra’s cognitive computing engine to acquire information on consumers’ tastes. The company’s FlavorPrint system, which analyzes taste preferences and creates a visual image of them, is based on the premise that a person’s taste profile is as unique as his or her fingerprint.
Consumers fill out a survey on the FlavorPrint website about their food preferences, eating habits and additional information, which is then compared with McCormick’s research data on food tastes and other factors. The information is used to increase customer engagement by offering personalized recipes and to help food retailers and suppliers boost sales.
Retailers also are a prime target for Enterra’s technology. Stores are using omni-channel strategies to ensure that both their online and in-store operations are allowing consumers every available item for purchasing. But this also means that retailers need to quickly analyze all of this data in the hope of creating a more favorable customer experience and increase sales.
If the data analysis has to be done manually, however, it could result in lost sales. For example, a retailer offering an in-store coupon to customers requires their information to be quickly analyzed after they walk into the store, in order for the promotion to be successful. It could take hours with humans analyzing the data, whereas machines can easily handle that task in minutes.
DeAngelis said that the healthcare sector is another industry that would greatly benefit from the company’s artificial intelligence platform.
For instance, hospitals using the company’s technology would receive more information about their patients’ medical histories, enabling them to provide better treatment options. “With cognitive computing, we can utilize more specific drugs and other therapies to treat patients,” he said.
Improved analysis of patient data would also minimize the use of trial-and-error treatments, thereby helping to lower healthcare costs and financially reward those healthcare providers who effectively manage patient care.
There is some confusion over Enterra’s technology and other systems that are built to think like humans, DeAngelis noted.
Other systems are designed for “deep learning,” that is, the ability to recognize objects and translate speech in real time, but Enterra’s system goes significantly beyond that.
DeAngelis said that the company’s cognitive computing platform also has “deep understanding,” or the ability to dig deeper into data so as to better enable companies to solve vexing problems.
“With cognitive computing, we can actually deeply understand why things are happening,” he said.
DeAngelis added that the company — which has raised $40 million from investors — is “growing quite rapidly,” with a client roster that includes some of the world’s biggest brands.
Exuding confidence that Enterra will be a leader in the cognitive computing area, an industry expected to reach between $13 billion and $35 billion worldwide by 2020, DeAngelis said that Enterra’s technology is quite unique. “We are the only one in our space doing what we do.”
