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.
A drafting studio at Bell Labs, 1942. Source “The future is already here - it’s just not evenly distributed.” - William Gibson As we approach the finish line for 2017, I continue to reflect on the state of the architecture and construction industry as I have in years past. As we contend with global issues … Continue reading Reflecting on the Future of Work
When we work with our clients to create data strategies or custom software, we often find ourselves facilitating and prioritizing a multitude of viewpoints, debating skepticism, and building consensus. In this context we have often found that understanding one variable, more than others, is central to navigating the complexities of stakeholder positions: professional bias. Biases … Continue reading Industry Transformation and the Challenge of Professional Bias
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