Summer 2018 – Part 1

Like with past summers, I thought I'd share some of the things our summer researchers are investigating. In 2016, the team created computational prototypes focused on real-world workflows ranging from building analysis to geometric interoperability. In 2017, the focus was on data analysis and resulted in building data visualization workflows and the first version of … Continue reading Summer 2018 – Part 1

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

LunchBoxML for Dynamo

This past summer, we released LunchBoxML for Grasshopper. Many have asked if we would publish a version for Dynamo. Ask no more! As of the last update, we have included the first version of LunchBoxML for Dynamo! By having this capability in Dynamo, users are able to start leveraging data from Revit to feed the … Continue reading LunchBoxML for Dynamo

Machine Learning with LunchBoxML

Earlier this summer, I previewed some of our research on machine learning which focused on potential applications for the building industry. I am now pleased to announce that these explorations have been released as a new extension to our LunchBox tools for Grasshopper: LunchBoxML. LunchBoxML exposes new open source components built on a popular machine … Continue reading Machine Learning with LunchBoxML