I really like the question this post asks. The post itself is a pretty scattered, but that’s not necessarily a bad thing given that it’s obviously a dump of in-progress research.
One place where I might direct effort differently: it seems like the “ideas that differ between people” in Appendix A offer more total bits-of-evidence than all the ML experiments combined, despite (I would guess) the ML experiments taking far more effort. This is a common pattern: the existing world offers an enormous number of bits-of-evidence at much lower cost than experiments. Often the experiments are necessary, in order to check how things behave outside the distribution offered by the real world, or in order to check something difficult to directly observe in the real world. But before investing lots of effort in an experiment, it’s worth stopping to ask whether you can get a lot more bits for your buck by looking at existing real-world instances. That’s especially true in the very early stages, when we’re not really sure what outside-of-real-world-distribution experiments will actually tell us anything useful.
I really like the question this post asks. The post itself is a pretty scattered, but that’s not necessarily a bad thing given that it’s obviously a dump of in-progress research.
One place where I might direct effort differently: it seems like the “ideas that differ between people” in Appendix A offer more total bits-of-evidence than all the ML experiments combined, despite (I would guess) the ML experiments taking far more effort. This is a common pattern: the existing world offers an enormous number of bits-of-evidence at much lower cost than experiments. Often the experiments are necessary, in order to check how things behave outside the distribution offered by the real world, or in order to check something difficult to directly observe in the real world. But before investing lots of effort in an experiment, it’s worth stopping to ask whether you can get a lot more bits for your buck by looking at existing real-world instances. That’s especially true in the very early stages, when we’re not really sure what outside-of-real-world-distribution experiments will actually tell us anything useful.