Rahul Modak

Rahul Modak is a co-founder and a key figure at Bayesian Analytics, where he focuses on developing large language models (LLMs) for customer data platforms and visualization. His work involves leveraging Bayesian methods and Direct Preference Optimization (DPO) techniques to enhance AI models, particularly in refining their alignment with human preferences and improving user engagement through custom visualizations. This innovative approach aims to simplify model fine-tuning while maintaining computational efficiency.12

In his role, Modak is actively engaged in research and development, exploring how Bayesian statistics can address challenges in generative AI, such as the common issue of model hallucinations, thereby improving the accuracy and reliability of AI outputs.2 His contributions to the field are underscored by his background in machine learning and data analytics, which he applies to drive significant business outcomes for clients.

Modak's expertise and leadership in these areas position him as an influential figure in the intersection of AI and data analytics, particularly within the context of enhancing customer data platforms.