This week, I will be leading a workshop as part of Data Day 2019 in Seattle. The workshop will focus on uses of machine learning in architecture and construction with hands-on examples of LunchBoxML for Grasshopper. If you are attending the workshop or just want some of the materials for your own reference, here they … Continue reading LunchBoxML @ Data Day 2019
One symptom of being at the 'peak of inflated expectations' on Gartner's famed hype cycle is the often relaxed use of terminology used in discussion about highly publicized technology. In some cases, this 'relaxation' is due to unfamiliar vocabulary for new technology that will take time to synthesize around a clear set of definitions. In … Continue reading Design Modeling Terminology
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
Data literacy comes about from a much deeper investment directed towards growing knowledge and expertise. Skill sets in statistical analysis or the ability to prepare meaningful visual representations of data are practical examples of being literate in data. Cultivating data literacy can also be a much higher barrier to overcome due to entrenched corporate politics, competing business interests and resistance from decision-makers to implement analytical recommendations that challenge the status quo. In short: changing people is harder than purchasing new tools.