I would definitely consider collaborative filtering ML, though I don't think people normally make deep models for it. You can see on Recombee's website that they use collaborative filtering, and use a bunch of weasel language that makes it unclear if they actually use anything else much at all
They tout their transformer ("beeformer") in marketing copy, but I expect mostly its driven by collaborative filtering, like most recommendation engines
We've actually been thinking about something quite related! More info soon.
(Typo: Lightcone for a writing retreat -> Lighthaven for a writing retreat)
My writing is often hard to follow. I think this is partly because I tend to write like I talk, but I can't use my non-verbals to help me out, and I don't get live feedback from the listener.
Interesting! Two yet more interesting versions of the test:
Moderation note: RFEs with interesting writeups have been a bit hard to frontpage recently. Normally, an announcement of a funding round is on the "personal" side, but I do think the content of this post, other than the announcement, is frontpage-worthy. For example, it would be interesting for people to see in recommendations in a few months time.
With the recent OpenPhil RFE, we asked them to split out the timeless content, which we then frontpaged. I would be happier if this post did that, but for now I'll frontpage it. I might change my mind and remove it from recommendations if I see it showing up and it feeling strange.
(Another thing that would help me feel comfortable frontpaging it would be a title change, where the new funding round was mentioned parenthetically).
This popped up in my Recommended feed, and it piqued my interest: I think it relates to a design skill I've picked up at Lightcone. When staging a physical space, or creating a website, I often want to stop iterating quite early, when the core idea is realised. "It would be a lot of work to get all the minor details here, but how much does stuff feeling a bit jank really matter?"
I think jank matters surprisingly much! When creating something, it's easy to think "wow, that's a cool idea. I've got a proof of concept sorted". But users, even if they think similar thoughts, either experience delight and ease, or they don't.
In design, it's kind of easy to "turn off your eyes" for a bunch of problems, and stop being able to notice them as things to improve. Which seems a bit different from mortgages and driving.
I had terrible luck with symbolic regression, for what its worth.
Two options I came up with:
This is a bit of an aside, but I hesitate to be too shocked by differences in funding:DALY ratios. After all, what you really want to know is change in DALYs at a given level of funding. It seems pretty plausible that some diseases are 10x (or even 100x) as cost-effective to ameliorate as others.
That said, funding:DALY seems like a fine heuristic for searching for misallocated resources. And to be clear, I expect it's not actually a difference in cost-effectiveness that's driving the different spending, but I'd want to check before updating too much.