Join us in this thought-provoking episode as we dive deep into the groundbreaking research on AI's capabilities in finance. From crunching numbers in financial statements to uncovering potential pitfalls like look-ahead bias, this conversation peels back the layers of AI's strengths and limitations.

Highlights include:
- Can AI really "understand" financial data?
- Why numerical reasoning is still a challenge for large language models (LLMs).
- The impact of tools like code interpreters on AI's performance.
- Look-ahead bias: How much can we trust AI's predictions?
- Exciting possibilities for using AI to analyze text, images, and audio in finance.

Discover how these insights are shaping the future of financial analysis and decision-making. With a balanced take on the challenges and opportunities, this episode is a must-listen for anyone curious about the intersection of AI and finance.

Find the full research paper here: https://community.quantopian.com/c/community-forums/caution-ahead-numerical-reasoning-and-look-ahead-bias-in-ai-models

For more quant-focused content, join us at ⁠⁠⁠⁠https://community.quantopian.com⁠⁠⁠⁠. There, you can explore a wealth of resources, connect with fellow quants, engage in insightful discussions, and enhance your skills through our extensive range of online courses.

Quant Radio is an AI-generated podcast, intended to help people develop their knowledge and skills in Quant finance. This podcast is not intended to provide investment advice.

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