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The AI experts at Monitaur explain the foundations of safe and resilient modeling systems behind the AI that impacts our lives and our businesses in our podcast, The AI Fundamentalists.
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We continue with our series about building agentic AI systems from the ground up and for desired accuracy. In this episode, we explore linear programming and optimization methods that enable reliable decision-making within constraints.
The hosts look at utility functions as the mathematical basis for making AI systems. They use the example of a travel agent that doesn’t get tired and can be increased indefinitely to meet increasing customer demand. They also discuss the difference between this structured, economic-based approach with the problems of using large language models for multi-step tasks.
What if we've been approaching AI agents all wrong? While the tech world obsesses over large language models (LLMs) and prompt engineering, there's a foundational approach that could revolutionize how we build trustworthy AI systems: mechanism design.
Dr. Andrew Clark is Monitaur’s co-founder and Chief Technology Officer. A trusted domain expert on the topic of ML auditing and assurance, Andrew built and deployed ML auditing solutions at Capital One. He has contributed to ML auditing education and standards at organizations including ISACA and ICO in the UK. He currently serves as a key contributor to ISO AI Standards and the NIST AI Risk Management framework. Prior to Monitaur, he also served as an economist and modeling advisor for several very prominent crypto-economic projects while at Block Science.
Andrew received a B.S. in Business Administration with a concentration in Accounting, Summa Cum Laude, from the University of Tennessee at Chattanooga, an M.S. in Data Science from Southern Methodist University, and a Ph.D. in Economics from the University of Reading. He also holds the Certified Analytics Professional and American Statistical Association Graduate Statistician certifications. Andrew is a professionally trained concert trumpeter and Team USA triathlete.
Dr. Sid Mangalik is a Research Scientist at Monitaur, focused on making AI systems accountable and fair through robust model validation and governance. His latest research focused on identifying connections between community-level language and psychological outcomes, for which he received his PhD in Computer Science from Stony Brook University, advised by Dr. H. Andrew Schwartz.
