One quick point: I feel pretty confused about the “Lack of Senior ML Research Staff” criticism. Senior ML research staff are one of the biggest bottlenecks in alignment, and so this feels particularly un-actionable as a criticism, especially given that you’re leading with it. (That’s particularly true when it comes to hiring for full-time roles, but I expect also relevant when it comes to recruiting good advisors.)
You concretely note that Redwood “terminated some of their more experienced ML research staff”, but once you’ve hired somebody you get a huge amount of data on their performance on many different axes, which makes it hard to interpret this as a bias against experienced ML researchers.
One quick point: I feel pretty confused about the “Lack of Senior ML Research Staff” criticism. Senior ML research staff are one of the biggest bottlenecks in alignment, and so this feels particularly un-actionable as a criticism, especially given that you’re leading with it. (That’s particularly true when it comes to hiring for full-time roles, but I expect also relevant when it comes to recruiting good advisors.)
You concretely note that Redwood “terminated some of their more experienced ML research staff”, but once you’ve hired somebody you get a huge amount of data on their performance on many different axes, which makes it hard to interpret this as a bias against experienced ML researchers.
Seems like to the degree it’s valid, it’s actionable for people who might consider working with or funding Redwood.