Overview
AI and Optimization represent distinct approaches to solving engineering challenges. Optimization is rooted in improving solutions to meet defined objectives and constraints, while AI focuses on predictive modeling, generative and novel solutions.
This presentation begins by distinguishing these classes of methodologies, explores the differences and their interplay or complementary natures. We will then delve into our journey of transition from Optimization to AI.
By examining lessons learned, strategic investments, and future plans, we will show how AI accelerates and enhances optimization, ensuring designs meet and exceed standards while driving innovation and fast decision-making in product engineering.
Simon Xu is a Tech Fellow for Vehicle Optimization and AI/ML at General Motors’ Global Total Vehicle Integration and CAE organization. He chairs the GM Global Optimization Focus Group and is responsible for innovations of optimization/AI tools in vehicle and electrified propulsion system development. Simon leads a team of experts focusing on optimization/AI techniques such as parametric modeling, geometric morphing, topology optimization, generative design, multi-disciplinary optimization, predictive AI and generative AI. Through his team’s effort and influence, GM’s virtual vehicle development has been continuously improved by the implementation of new tools and processes to meet the new challenges in CO2, EV architectures, advanced battery design and electric drive technologies.
