AI Odyssey

By: Anlie Arnaudy Daniel Herbera and Guillaume Fournier
  • Summary

  • AI Odyssey is your journey through the vast and evolving world of artificial intelligence. Powered by AI, this podcast breaks down both the foundational concepts and the cutting-edge developments in the field. Whether you're just starting to explore the role of AI in our world or you're a seasoned expert looking for deeper insights, AI Odyssey offers something for everyone. From AI ethics to machine learning intricacies, each episode is crafted to inspire curiosity and spark discussion on how artificial intelligence is shaping our future.
    Anlie Arnaudy, Daniel Herbera and Guillaume Fournier
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Episodes
  • AI vs. Wall Street – The Rise of Multi-Agent Trading
    Mar 15 2025

    How can AI revolutionize financial trading? The TradingAgents framework introduces a multi-agent system where AI-powered analysts, researchers, and traders collaborate to make more informed investment decisions. Inspired by real-world trading firms, this innovative approach leverages specialized agents—fundamental analysts, sentiment analysts, technical analysts, and traders with diverse risk profiles—to optimize trading strategies.

    Unlike traditional models, TradingAgents enhances explainability, risk management, and market adaptability through agentic debates and structured decision-making. Extensive backtesting reveals significant performance improvements over standard trading strategies.

    Discover the future of AI-driven finance and explore the full research paper here: https://arxiv.org/abs/2412.20138.

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    10 mins
  • Agentic AI in Finance: Smarter Models, Safer Decisions
    Mar 8 2025

    Can AI-powered teams replace traditional financial modeling workflows? This episode explores how agentic AI systems—where multiple specialized AI agents work together—are transforming financial services. Based on recent research, we break down how these AI "crews" tackle complex tasks like credit risk modeling, fraud detection, and regulatory compliance.

    We dive into the structure of these AI-driven teams, from model selection and hyperparameter tuning to risk assessment and bias detection. How do they compare to human-led processes? What challenges remain in ensuring fairness, transparency, and robustness in financial AI applications? Join us as we unpack the future of autonomous decision-making in finance.

    Source paper: https://arxiv.org/abs/2502.05439


    Original analysis by Hanane Dupouy on LinkedIn:

    https://www.linkedin.com/posts/hanane-d-algo-trader_curious-about-how-agentic-systems-are-transforming-activity-7303759019653943296-SD7p?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAC-sCIBdYWLepIkTB7ZdnxPNfvEfrLi2z0


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    16 mins
  • The Future of Prompting: Can AI Optimize Its Own Instructions?
    Mar 2 2025

    Crafting the perfect prompt for large language models (LLMs) is an art—but what if AI could master it for us? This episode explores Automatic Prompt Optimization (APO), a rapidly evolving field that seeks to automate and enhance how we interact with AI. Based on a comprehensive survey, we dive into the key APO techniques, their ability to refine prompts without direct model access, and the potential for AI to fine-tune its own instructions. Could this be the key to unlocking even more powerful AI capabilities? Join us as we break down the latest research, challenges, and the future of APO.

    📄 Read the full paper here: https://arxiv.org/abs/2502.16923

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    17 mins

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