Thanks to Hao Zhang, Kayvon Fatahalian, and Jean-Stanislas Denain for helpful
discussions and comments.
Addendum and erratum. See here
[https://kipp.ly/blog/transformer-inference-arithmetic/] for an excellent
discussion of similar ideas by Kipply
Last week [https://bounded-regret.ghost.io/early-2022-paper-round-up/], 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
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.
