I've been lurking on LW since 2013, but only started posting recently. My day job was "analytics broadly construed" although I'm currently exploring applied prio-like roles; my degree is in physics; I used to write on Quora and Substack but stopped, although I'm still on the EA Forum. I'm based in Kuala Lumpur, Malaysia.
I like it too, although there's 500+ fiction posts on LW (not including the subreddit) so you probably meant something else.
What about just not pursuing a PhD and instead doing what OP did? With the PhD you potentially lose #1 in
I actually think that you can get great results doing research as a hobby because
- it gives you loads of slack, which is freedom to do things without constraints. In this context, I think slack is valuable because it allows you to research things outside of the publishing mainstream.
- and less pressure.
I think these two things are crucial for success. The slack allows you to look at risky and niche ideas are more likely to yield better research rewards if they are true, since surprising results will trigger further questions.
Also, since you are more likely to do better at topics you enjoy, getting money from a day job allows you to actually purse your interests or deviate from your supervisor’s wishes. Conversely, it also allows you to give up when you’re not enjoying something.
which is where much of the impact comes from, especially if you subscribe to a multiplicative view of impact.
Wikipedia says it's a SaaS company "specializing in AI-powered document processing and automation, data capture, process mining and OCR": https://en.wikipedia.org/wiki/ABBYY
To be clear, GiveWell won’t be shocked by anything I’ve said so far. They’ve commissioned work and published reports on this. But as you might expect, these quality of life adjustments wouldnt feature in GiveWell’s calculations anyway, since the pitch to donors is about the price paid for a life, or a DALY.
Can you clarify what you mean by these quality of life adjustments not featuring in GiveWell's calculations?
To be more concrete, let's take their CEA of HKI's vitamin A supplementation (VAS) program in Burkina Faso. They estimate that a $1M grant would avert 553 under-5 deaths (~80% of total program benefit) and incrementally increase future income for the ~560,000 additional children receiving VAS (~20%) (these figures vary considerably by location by the way, from 60 deaths averted in Anambra, Nigeria to 1,475 deaths averted in Niger) then they convert this to 81,811 income-doubling equivalents (their altruistic common denominator — they don't use DALYs in any of their CEAs, so I'm always befuddled when people claim they do), make a lot of leverage- and funging-related adjustments which reduces this to 75,272 income doublings, then compare it with the 3,355 income doublings they estimate would be generated by donating that $1M to GiveDirectly to get their 22.4x cash multiplier for HKI VAS in Burkina Faso.
So: are you saying that GiveWell should add a "QoL discount" when converting lives saved and income increase, like what Happier Lives Institute suggests for non-Epicurean accounts of badness of death?
the obvious thing to happen is that nvidia realizes it can just build AI itself. if Taiwan is Dune, GPUs are the spice, then nvidia is house Atreides
You mention in another comment that your kid reads the encyclopaedia for fun, in which case I don't think The Martian would be too complex, no?
I'm also reminded of how I started perusing the encyclopaedia for fun at age 7. At first I understood basically nothing (English isn't my native language), but I really liked certain pictures and diagrams and keep going back to them wanting to learn more, realising that I'd comprehend say 20% more each time, which taught me to chase exponential growth in comprehension. Might be worth teaching that habit.
That's fair.
Society seems to think pretty highly of arithmetic. It’s one of the first things we learn as children. So I think it’s weird that only a tiny percentage of people seem to know how to actually use arithmetic. Or maybe even understand what arithmetic is for.
I was a bit thrown off by the seeming mismatch between the title ("underrated") and this introduction ("rated highly, but not used or understood as well as dynomight prefers").
The explanation seems straightforward: arithmetic at the fluency you display in the post is not easy, even with training. If you only spend time with STEM-y folks you might not notice, because they're a very numerate bunch. I'd guess I'm about average w.r.t. STEM-y folks and worse than you are, but I do quite a bit of spreadsheet-modeling for work, and I have plenty of bright hardworking colleagues who can't quite do the same at my level even though they want to, which suggests not underratedness but difficulty.
(To be clear I enjoy the post, and am a fan of your blog. :) )
Scott tried out an intuition pump in responding to nostalgebraist's skepticism: