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  <title>Ep. 365: Stefan Jansen on Agentic AI, ML Workflows, and the Evolution of Machine Learning for Trading</title>
  <description> Stefan Jansen is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups across industries on data &amp;amp;amp; AI strategy, building data science teams, and developing end-to-end machine learning solutions.&amp;amp;nbsp;   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 &amp;quot;Fat Tail&amp;quot; Challenge Shapley Values: Turning Black Boxes Grey Agentic AI and Unstructured Data RAG, Provenance, and the Context Window Debate The &amp;quot;Alpha Factory&amp;quot; Workflow Reinforcement Learning (RL) for Execution, Not Prediction The Critical Role of Human Context Advice for the AI-Native Job Market&amp;amp;nbsp;   </description>
  <author_name>Macro Hive Conversations With Bilal Hafeez</author_name>
  <author_url>https://macrohive.com/</author_url>
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