In this episode, Neil explores how agents, foundation models, and AI are set to transform the Computer-Aided Engineering (CAE) and Electronic Design Automation (EDA) landscapes. He shares a comprehensive historical perspective and predicts a near-future where AI-driven automation redefines engineering workflows, productivity, and innovation.
Main Topics:
The evolution of simulation codes from the 1960s to modern commercial software
The rise of cloud computing, GPUs, and their impact on CAE and EDA industries
The integration of AI, surrogate modeling, and foundation models into simulation workflows
The emergence of agentic AI systems capable of autonomously performing complex engineering tasks
The strategic responses of major software companies to AI and agent technologies
The potential democratization and automation of engineering design through AI agents
Critical questions on model ownership, transparency, and industry adoption
Timestamps:
00:00 - Podcast intro
00:40 - Introduction: How agents and foundation models will disrupt CAE & EDA
01:40 - Historical overview: From code writing in the 60s to commercial software
03:10 - Growth of aerospace and automotive industry codes and commercialization
04:40 - The impact of HPC, cloud computing, and hardware evolution
06:25 - Rise of cloud SaaS models and "sassification" of simulation tools
07:40 - Big tech entrance: AWS, Microsoft, and Google in CAE & EDA
09:00 - GPU acceleration: Changed landscape in past three to four years
09:10 - The role of AI startups offering surrogate models and real-time simulation
10:40 - Industry consolidation: Mergers and acquisitions among software giants
11:40 - The emergence of foundation models and surrogate systems in simulation
13:00 - The significance of agents: Combining AI, models, and automation
14:10 - Capabilities of autonomous AI agents in complex engineering workflows
15:25 - Practical use cases: Running simulations, setting up experiments, and data analysis
16:10 - Questions about model ownership, open-source codes, and licensing
16:40 - How agent-driven automation could democratize engineering expertise
19:40 - The future of AI in engineering: Collaboration, transparency, and scientific rigor
21:25 - Final thoughts: Opportunities, challenges, and the transformative potential of AI
Please note that this episode expresses my personal opinion and does not represent the views of NVIDIA.
Full episode, corrected transcript and resources:
https://neilashton.co.uk/podcasts/s4-e1-are-ai-agents-and-foundation-models-about-to-rewrite-cae/
