Description
This session will explore how language learning models (LLMs) can be integrated with Autodesk Platform Services APIs for optimization of hyperparameters like structural design, reduction of material usage, and embodied carbon. We'll demonstrate this using Autodesk Platform Services to extract building information modeling (BIM) data from Revit models to train LLMs, generating intelligent-design suggestions. The optimized designs are later visualized in Autodesk Platform Services Autodesk Viewer, clearly identifying improvements. Using sample Revit models, we'll showcase how this approach has led to substantial reductions in material consumption and carbon emissions, such as a 25% reduction in steel usage and a 30% decrease in embodied carbon. Discover how using AI and Autodesk Platform Services can create more-sustainable, more-efficient, and more-innovative structural designs, driving the industry toward a greener future.
Key Learnings
- Learn about constructing a business case for using LLMs to understand your structural optimization needs and what to look for.
- Learn how to use pyRevit, .NET Core, and .NET Framework (Autodesk Platform Services) for extracting BIM data and training LLM to understand the data.
- Explore a case study (Revit model) demonstrating LLM integration inside the Autodesk Platform Services full-stack application.