BayesiaLab
Leverage GenAI and Causal Inference to Disrupt Innovation

Leverage GenAI and Causal Inference to Disrupt Innovation

Recorded at the 2024 BayesiaLab Conference in Cincinnati on April 12, 2024.

Abstract

We have been exploring different ways to leverage GenAI and causal inference to disrupt the speed, scope, and economics of product innovation at P&G. This includes LLM like ChatGPT and Mixtral_8X7B, open source packages like Langchain and LlamaIndex and third-party software/module Hellixia. We use these existing tools or build new tools on top of them to understand consumers and drive product innovation. We leverage these tools to generate structure summaries and reports from large volumes of data and to generate qualitative or semiquantitative structural causal models, etc.

Presentation Video

Presentation Slides

About the Presenter

Dr. Yong Zhang leverages Bayesian data and modeling science to develop a strategy for product design, manufacturing, storage, and transportation across P&G to improve consumers’ quality of life and drive positive influence on the environment and society under different climate change scenarios. He develops modeling and simulation methods and tools through Front End Innovation projects to enable and promote the capability across P&G for breakthrough consumer understanding and product innovation. The methods and tools can be used to extract and integrate information from a variety of data sources to find a “Body of Evidence” for consumer and product research based on Nonparametric Bayesian statistics and deep learning algorithms.

Yong Zhang, Ph.D.


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