My students and collaborators have been doing some particularly awesome work over the past several months, and to highlight that I wanted to summarize their papers here, and explain why I’m excited

In Future ML Systems Will Be Qualitatively Different [https://bounded-regret.ghost.io/p/1527e9dd-c48d-4941-9b14-4f7293318d5c/], I argued that we should expect ML systems to exhibit emergent capabilities. My main support for this was four

Previously, I argued [https://bounded-regret.ghost.io/p/1527e9dd-c48d-4941-9b14-4f7293318d5c/] that emergent phenomena in machine learning mean that we can't rely on current trends to predict what the future of ML will be like.

Previously, I've argued that future ML systems might exhibit unfamiliar, emergent capabilities [https://bounded-regret.ghost.io/p/1527e9dd-c48d-4941-9b14-4f7293318d5c/], and that thought experiments provide one approach [https://bounded-regret.ghost.io/p/a2d733a7-108a-4587-97fb-db90f66ce030/] towards predicting

In the previous post [https://bounded-regret.ghost.io/thought-experiments-provide-a-third-anchor/], I talked about several "anchors" that we could use to think about future ML systems, including current ML systems, humans, ideal optimizers, and complex