AEC Tech 2018 – LunchBoxML Workshop Examples

David Stasiuk and I instructed a 4-hour workshop on Machine Learning as part of AEC Tech 2018 - an annual conference hosted by Thornton Tomasetti. The workshop focused on demonstrating architectural use cases for machine learning in the context of our open source LunchBoxML tools. Our course examples are now available on the LunchBoxML Bitbucket … Continue reading AEC Tech 2018 – LunchBoxML Workshop Examples

Summer 2018 – Part 2

Our 2018 summer research internship has come to the finish line! In the last 8 weeks, the Proving Ground research team developed design uses cases for multi-objective evolutionary solvers and  created game engine prototypes to visualize complex spatial databases. The team learned a lot this summer and we wish Maren and Ian all the best … Continue reading Summer 2018 – Part 2

New Machine Learning Examples with LunchBoxML

Last year, we introduced LunchBoxML - a machine learning (ML) plugin for Grasshopper and Dynamo that uses the Accord framework. LunchBoxML introduces several generalized supervised and unsupervised learning tools to visual programming including regression analysis, neural networks, and mixture models. We have published a few new examples to the Bitbucket repository to demonstrate the application … Continue reading New Machine Learning Examples with LunchBoxML

Transform your Building Information into a Big Data Resource

We have recently created a database framework called Minecart which harvests data from building information sources such as Revit and IFC formats. Our database is designed to represent building information as a scalable relational structure connecting data across multiple projects, documents, elements, and parameters.