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.
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
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
We are in the heat of the summer season and we have invited summer interns to work with us to experiment with new concepts and technologies. In 2016, we focused on rapid development of focused problem-first workflows and published our content as an open source project. This year, Ally and Nazanin have joined us for … Continue reading Analytics, machines, and our summer so far…