MSU paper analyzing complexity of genetic algorithms used to train Expert Systems (fuzzy logic) and Neural Networks (NEAT).
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LLMZ+: Contextual Prompt Whitelist
MSU research paper to be presented at a ICMLA ’25 conference in Boca Raton, FL. It describes the principles of contextual whitelisting for agentic LLMs. It significantly increases deployment security without additional cost and resources associated with traditional threat mitigation systems.
Continue reading “LLMZ+: Contextual Prompt Whitelist”Fintech Use of Genetic Algorithms
MSU Seminar paper describing fintech adoption of Genetic-assisted AI. From ledger forecasting to anti-fraud and forensic audits, I provide a brief overview of evolutionary algorithms improving well-established artificial intelligence tools.
Continue reading “Fintech Use of Genetic Algorithms”Genetic Evolution of Expert AI Systems
MSU paper describing a real-life use of an expert system paired with an evolutionary training algorithm in the realm of US credit underwriting.
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