My take on the Garry Tan interview (which seems pretty clear, regardless of whether this is snake oil or not) is that Extropic are building low power analog chips because we're hitting up against the limits of Moore's Law (limit's of physics in reducing transistor size), and at the same time the power consumption for LLM/AI training and inference is starting to get out of hand.

So, their solution is to embrace the stochastic operation of smaller chip geometries where transistors become unreliable, and double down on it by running the chips at low power where the stochasticity is even worse. They are using an analog chip design/architecture of some sort (presumably some sort of matmul equivalent?) and using a "full-stack" design whereby they have custom software to run neural nets on their chips, taking advantage of the fact the neural nets can tolerate, and utilize, randomness.