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Stephen DeAngelis, Founder & CEO of Enterra Solutions – Interview Series

September 11, 2023
in AI & Technology
Reading Time: 6 mins read
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Stephen DeAngelis, Founder & CEO of Enterra Solutions – Interview Series
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Stephen DeAngelis is founder and CEO of Enterra Solutions, the first company to apply Autonomous Decision ScienceTM (ADS®) technology to perform end-to-end value chain optimization, decision-making, and complex research & development for enterprises.

Stephen F. DeAngelis is an internationally recognized expert on artificial intelligence and advanced analytics and their applications to the competitiveness, resiliency, and security of commercial entities and governmental agencies. Mr. DeAngelis is a patent holder, technology pioneer, and entrepreneur. His career is in the intersection of international relations, business, government, and academia. He brings a unique perspective and deep experience to his companies.

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Could you share the genesis story behind Enterra Solutions?

Enterra has its origins as a U.S. government contractor. Enterra developed and executed enterprise resiliency (systemic data-driven competitiveness, risk, and performance) models for U.S. governmental agencies. In performing this work, Enterra developed its best practices Enterprise Resilience Management Methodology and Maturity model under collaborative research and development agreements with federally funded US research and development agencies.

To advance competitiveness and resiliency technology, Enterra began work in artificial intelligence and applied mathematics in the early 2000s. By the mid-2000s, the company began to combine its work in the government sector with cutting-edge theoretical and experimental academic research – this work continues today. Enterra academic research is a bi-directional cooperation that exposes our company and employees to some of the most advanced and sophisticated AI and mathematical techniques and practices, while establishing a deep network and set of connections to some of the leading individuals and seminal thinkers in cognitive science and resiliency applications.

Enterra leveraged the scientific and technical learnings from its work in government and academia to reimagine big data analytics in the commercial sector – the result was the creation of Enterra’s Autonomous Decision Science® (ADS®) & Generative AI platform and set of value-chain expansive business applications that come together to create a first of its kind System of Intelligence. Enterra’s System of Intelligence performs autonomous end-to-end optimization, planning, and execution by sitting atop an organization’s multiple transactional systems of record/engagement across Marketing, Sales, Supply Chain, and Corporate Strategy, and orchestrating decisions and actions that help the company build competitiveness and resiliency and reach their business goals.

By combining Enterra’s proprietary technology with organizational knowledge and practices, Enterra anticipates market changes systematically and at market speed—transforming businesses into Autonomous Intelligent Enterprises.

Enterra Solutions offers autonomous decision science, what is this specifically and how does it optimize business decisions?

Enterra’s Autonomous Decision Science® (ADS®) is the technology platform that powers the Enterra System of Intelligence™. Enterra’s ADS technology platform brings together three previously siloed technologies:

  1. A Semantic Reasoning and Vector Symbolic Logic-based Artificial Intelligence that enables human-like reasoning, decision-making and learning. This unique capability combines common-sense and industry knowledge with inference reasoning to create a system that can make decisions with subtle, human-like reasoning and then learn from the outcomes.
  2. Glass-Box, explanatory, transparent machine learning in the form of the proprietary Representation Learning Machine™ (RLM). The basis of the RLM is high dimensional mathematics and functional analysis. RLM uniquely identifies a function that describes the combination and contribution of variables in the data set that describe the observable effects through multiple layers of interaction with a high degree of precision. This is classified as a “glass-box”, explanatory algorithm that generates a function, whose output is visible as opposed to “black-box” algorithms that merely generate patterns, but do not offer any explanatory description of the dynamics of system/data set, nor have any substantive “Understanding” of what the pattern means.
  3. Constraint-based, non-linear optimization capability that incorporates the RLM derived formula, along with semantic reasoning constraints and logic, to perform fast optimization that reflect the complex multi-dimensional real-world considerations to derive highly actionable recommendations. This capability breaks the dimensionality barrier that is associated with linear models.

The unique combination of these techniques has enabled Enterra to provide clients with significantly differentiated capabilities and created a highly defensible chasm in the competitive landscape – with both large AI technology platforms and point solution players.

Approximately a year ago, on the “Eye on AI podcast”, you discussed how old-fashioned AI continues to be a powerful tool. Have your views shifted on this, and what are some of the traditional machine learning algorithms that are still used at Enterra Solutions?

Science is generationally additive, meaning that one generation of capability layers on top the previous generation’s innovations to create new capabilities. Enterra continually innovates and creatively evolves its technology. As mentioned above, Enterra has created an Enterra Autonomous Decision Science® (ADS®) & Generative AI platform that is an ensemble of human-like reasoning and GenAI capabilities, super advanced high-dimensional, glass-box, explanatory machine learning with non-linear, constraint-based optimization engines. We have brought together these previously siloed technologies under one platform and in doing so have been able to unlock previously unrealizable analytical capabilities and mitigated the shortfalls of any one individual technology.

How has Enterra Solutions integrated Generative AI into their solutions?

While many organizations are still in a discovery and trial period with generative AI, Enterra Solutions and our clients have benefited from its powerful capabilities for over a decade. The AI component of Enterra’s platform will uniquely learn the environmental reasons that recommendations are successful or not and persist that learning in their Ontologies and Generative AI knowledge bases. Enterra, when requested by a client, will develop a specific GenAI knowledge base representing their clients’ strategies, tactics, business logic, and ways of working and winning; while providing updated logic and constraint setting to the optimization functions within the functional components of Enterra’s System of Intelligence.

Hallucinations is one of the primary issues with Generative AI, how does Enterra Solutions overcome these limitations?

Generative AI can automate most workflows, but being unvalidated, its credibility is questionable. This can be addressed by leveraging ADS technology that can plug into large language models (LLMs), reason and triangulate knowledge mathematically to validate its efficacy. By leveraging ADS to deliver trusted explainability and actionability of insights and recommendations, trust can be built.

From 2015 to 2019, you were an Advisory Board Member at the Dalai Lama Center for Ethics and Transformative Values at MIT, how has this molded your values on business and AI?

Well, if one is involved with the Dalai Lama Center you can’t help but think about leadership and ethics as one in the same. When you run a business, you learn very quickly that you make thousands of decisions a year. Some are small, some are ordinary or procedural, and some are significant or consequential decisions. I hope that I have learned to make decisions with ethical considerations natively embedded in my logic – truly a north star and the parameters for enlightened decision-making. This concept is also reflected in the way we construct algorithms and software, and it is ultimately reflected in the way that we run our organization.

Often business and AI leaders such as Geoffrey Hinton are concerned about the future potential problems of AI, and specifically AGI, what are your views on this?

Some of Geoffrey Hinton’s concerns are with potential misuse and the speed at which AI is being deployed. Those are fair points as many companies are trying to fit AI into their business practices without first understanding what problems they are trying to solve. AI doesn’t solve every problem and should not be thought of as a blanket solution to all business challenges. It is paramount that companies start with a business-led problem statement, before searching for viable solutions. Once you understand the problem you are trying to solve, you can understand the strategic fit and technical feasibility of using advanced technologies, like AI.

You’re a serial entrepreneur and have successfully launched multiple businesses in various domains, what drives you to innovate?

At the end of the day, I am more of a creative lifelong learner and intellectually curious businessperson than an administrator. The combination of lifelong learning and intellectual curiosity, when combined with an entrepreneur’s zeal for creating new business, drives innovation and the creation of products and services to fill identified market gaps. The desire to work with great teams of people and to “compete and win” by creating shareholder value are what drives me to innovate.

What is your vision for the future of AI?

Though the lens of AI’s use in near-future B2B applications – I believe that AI will enable practical autonomous decision-making in the near future in at-scale business applications. These capabilities will be driven by human-like Intelligent Agents that augment human-decision making with an artificial intelligence or artificial super intelligence that are focused on large and disruptive use cases. Applications such as, end-to-end value chain optimization and decision-making for global corporations across industry sectors and disruptions in drug discovery and formulations, and clinical trials, are transformative and touch the lives of most people across the planet.

Thank you for the great interview, readers who wish to learn more should visit Enterra Solutions.

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