Working with the fabulous Vikash Mansinghka, I’ve spent a lot of time building novel computing architectures for solving hard problems in probabilistic inference. It turns out that when you embrace, not suppress, stochasticity, you can build systems that are lower power, more robust to noise, and quite composible.
