Learning Lab: Chatting to our Data using LLMs: Harnessing the Power of AI for Data Analysis
Information
Join us for a session where we will demonstrate how GSK is enabling the entire organisation to chat to their data through the transformative capabilities of Large Language Models (LLMs). In this session, participants will explore how GSK is building and harnessing the power of LLMs and AI more broadly to enable scientists and other employees to understand their data in a way never possible before, without the need for specialised coding or data analysis expertise, empowering every team member to make informed decisions and drive innovation, so that we can positively impact the lives of 2.5bn people globally in the next decade.
Speakers:
Lee Clewley
Lee is Head of Applied AI, part of the AI/ML group in R&D at GSK, where we develop state-of-the-art AI/ML-based predictive models, including pioneering Large Language Model (LLM) projects using advanced agent frameworks. He excels in creating custom, user-friendly visualizations and integrating them into our scientists' workflows. Expertise includes machine learning, statistical modelling, and building high-functioning teams from scratch. Currently, he focusses on designing innovative Deep Learning and LLM tools for early drug discovery, navigating complex human biology and drug discovery landscapes.
Srini Raghavan
As a Senior Director of Software Engineering at GSK, I possess a deep-seated passion for crafting enterprise-grade software at scale, driven by a commitment to excellence and innovation. My enthusiasm for Generative AI is at the core of my professional ethos, fueling my ambition to harness its power to bolster productivity, efficiency, and robustness across enterprise services. In my leadership role, I prioritize the principles of DevSecOps and am dedicated to enhancing the developer experience as an API platform owner, ensuring secure, agile, and seamless software development life cycles. My focus is on building resilient software infrastructures that not only meet today's demands but also pave the way for tomorrow's advancements.
