Someone should do the obvious experiments and replications.

Ryan Greenblatt recently posted three technical blog posts reporting on interesting experimental results. One of them demonstrated that recent LLMs can make use of filler tokens to improve their performance; another attempted to measure the time horizon of LLMs not using CoT; and the third demonstrated recent LLMs' ability to do 2-hop and 3-hop reasoning.

I think all three of these experiments led to interesting results and improved our understanding of LLM capabilities in an important safety-relevant area (reasoning without visible traces), and I'm very happy Ryan did them. 

I also think all three experiments look pretty obvious in hindsight. LLMs not being able to use filler tokens and having trouble with 2-hop reasoning were both famous results that already lived in my head as important pieces of information about what LLMs can do without visible reasoning traces. As far as I can tell, Ryan's two posts simply try to replicate these two famous observations on more recent LLMs. The post on measuring no CoT time horizon is not a replication, but also doesn't feel like a ground-breaking idea once the concept of increasing time horizons is already known.

My understanding is that the technical execution of these experiments wasn't especially difficult either, in particular they didn't require any specific machine learning expertise. (I might be wrong here, and I wonder how many hours Ryan spent on these experiments. I also wonder about the compute budget of these experiments, I don't have a great estimate of that.)

I think it's not good that these experiments were only run now, and that they needed to run by Ryan, one of the leading AI safety researchers. Possibly I'm underestimating the difficulty of coming up with these experiments and running them, but I think ideally these should have been done by a MATS scholar, or ideally by an eager beginner on a career transitioning grant who wants to demonstrate their abilities so they can get into MATS later. 

Before accepting my current job, I was thinking about returning to Hungary and starting a small org with some old friends who have more coding experience, living on Eastern European salaries, and just churning out one simple experiment after another. One of the primary things I hoped to do with this org was to go through famous old results and try to replicate them. I hope we would have done the filler tokens and 2-hop reasoning replications too. I also had many half-baked ideas of running new simple experiments investigating ideas related to other famous results (in the way the no-CoT time horizon experiment is one possible interesting thing to investigate related to rising time horizons).

I eventually ended up doing something else, and I think my current job is probably a more important thing for me to do than trying to run the simple experiments org. But if someone is more excited about technical research than me, I think they should seriously consider doing this. I think funding could probably be found, and there are many new people who want to get into AI safety research; I think one could turn these resources into churning out a lot of replications and variations on old research, and produce interesting results. (And it could be a valuable learning experience for the AI safety beginners involved in doing the work.)