Last week, I talked about six recent papers from our group, and discussed the first two in detail. This week, I'll discuss the remaining four. They fall into two categories: robustness, and science

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, I argued that we should expect ML systems to exhibit emergent capabilities. My main support for this was four historical examples of emergence in ML.

Previously, I argued 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. In this post, I will argue

Previously, I've argued that future ML systems might exhibit unfamiliar, emergent capabilities, and that thought experiments provide one approach towards predicting these capabilities and their consequences. In this post I’ll describe a