PassiveLogic’s truly autonomous control of buildings and more is enabled by the use of physics-based digital twin simulations. To match these simulations to the real world and use them to make optimal control decisions, we need to be able to run these simulations faster than real-time. Additionally, we need to be able to optimize them at the edge, not on massive servers. Differentiable programming and gradient descent optimization are the key items needed to make this possible.

Recently, members of the PassiveLogic compiler team had the opportunity to attend the 2023 LLVM Developers’ Meeting in Santa Clara, CA. It was a tremendously rewarding experience for all of us.

The iPhone App Store launched 15 years ago, and transformed the way that we make, use, and obtain software. More personally, it had a tremendous positive impact on my life. I had one of the first 500 applications that launched with the store that day, an open source 3D molecular modeler called Molecules.

For the vast majority of programmers, when our code doesn’t build or doesn’t run correctly it’s almost always our fault. The compiler is pretty much the last thing we blame. However, at PassiveLogic, we push the limits of the Swift programming language, in particular by using an experimental language feature and helping in its evolution. As a result, “my code broke the compiler” is something you hear a little more frequently around here.