Ep. 365: Stefan Jansen on Agentic AI, ML Workflows, and the Evolution of Machine Learning for Trading
About this episode
Stefan Jansen discusses the evolution of machine learning for trading and the implications of AI in various sectors.
Stefan Jansen is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups across industries on data & AI strategy, building data science teams, and developing end-to-end machine learning solutions. Before his current venture, he was a partner and managing director at an international investment firm, where he built the predictive analytics and investment research practice. He was also a senior executive at a global fintech company with operations in 15 markets, advised Central Banks in emerging markets, and consulted for the World Bank. In this podcast, we discuss: Defining AI as a Moving Target The Trading vs. Business Data Science Divide Synthetic Data and the "Fat Tail" Challenge Shapley Values: Turning Black Boxes Grey Agentic AI and Unstructured Data RAG, Provenance, and the Context Window Debate The "Alpha Factory" Workflow Reinforcement Learning (RL) for Execution, Not Prediction The Critical Role of Human Context Advice for the AI-Native Job Market
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