AI & ML interests
Experimental craft and research over scale. [p → q] We're interested in the arrow. We study the layer between language and consequence. p what can be said → how it becomes something q what actually happens Right now that means: Today's AI is still bad in many ordinary ways; tomorrow's technology will be better. The bitter lesson we learn from it is that real-world data is continuous, high-dimensional, and noisy. Consistently, the most successful implementations use simple, composable patterns rather than giant complex frameworks. Like software in the 80s, there is a tremendous opportunity to build things that are not upgrades, but something completely different. Above all, we think there is a responsibility to recognize and create new things, and to take part in the strange, interesting, and sacred practice.