Guest Mike Conover from Brightwave discusses using large language models in finance, challenges in long context windows, and the evolution of AI research. Topics include implications of polarizing data, value of employee-led datasets, complexities of data temporality in finance, AI in financial services, AI hedge funds, and the evolution of large language models.

Mike Conover, co-founder and CEO of Brightwave, dives into the challenges and capabilities of AI in financial research. He discusses limitations of large language models (LLMs) and the importance of effective information retrieval. Mike shares insights on building strong AI engineering teams and the significance of practical collaboration between analysts and engineers. He emphasizes the need for customized AI solutions to enhance product outcomes, illustrating how Brightwave revolutionizes market analysis.