Event details
AI is rapidly entering the world of engineering, but how capable are today's large language models when faced with real physics, real data, and real design challenges?
In this one-demand webinar, the CoreWeave Physical AI team reveals insights from its LLM Benchmarking Study, in which we tested models across real engineering workflows on the CoreWeave platform, including Claude 4, Grok 4, Gemini 2.5 Pro, and ChatGPT o3.
Uncover which models show genuine engineering reasoning, which struggle with complex analysis, and what these results tell us about current and future capabilities of AI in engineering.
Webinar highlights
- How we benchmarked today's top LLMs, tested on realistic engineering scenarios inside CoreWeave's MCP framework
- How effectively LLMs understand engineering problems, from feature selection and model training to reasoning through physics-based constraints
- Where current models fall short and where they excel, drawing insights into performance, repeatability, and engineering intuition
- How AI is lowering the barrier to engineering analysis, making advanced problem-solving faster, easier, and accessible to more engineers
Who should watch?
This session is for engineers and technical leaders who want to stay ahead as AI reshapes engineering workflows:
- Engineers who are curious about advanced AI in engineering and how it could be applied in real R&D and testing contexts
- Professionals who want to stay ahead of the curve and see how new AI standards like MCPs are shaping engineering
- Early adopters in R&D and testing who are eager to explore practical, cutting-edge applications before they become mainstream
