FINTECH FOCUS TV: The science behind custom LLMs and Alpha discovery
From the limitations of static models to the need for custom, continuously learning systems. Here are some of the key themes shaping AI adoption in financial services.
In this episode of FinTech Focus TV, recorded live at Quant Strats 2025, our CEO, Dr. Yichuan Zhang discusses e evolving world of large language models in quant finance and the realities of how these technologies are being adopted by the buy side, sell side, and trading communities.
From the outset, this discussion stands apart because it deals not with theoretical speculation about artificial intelligence, but with its grounded application in financial institutions that handle enormous quantities of data. Dr Zhang’s experience spans more than fifteen years as an AI researcher, with a strong focus on deep generative models before the current wave of generative AI even began. His work at Google and the University of Cambridge shaped the expertise that now drives Boltzbit’s mission: enabling non-tech, data-heavy industries to use customised large language models trained on their own proprietary information. This ambition aligns closely with the challenges facing financial firms, where staggering amounts of data, wide-ranging tasks, and deeply embedded workflows create the perfect environment for targeted AI deployment.
