currymj

OTC decongestants that actually work, some useful info for those of us with bad sinuses.

- pseudoephedrine taken orally.

- phenylephrine, but only as nasal spray, not if you take it orally.

- Oxymetazoline (Afrin) nasal spray and others in this broad family

- propylhexedrine, sold OTC as Benzedrex as a vapor inhaler. Unfortunately people crack open the inhaler and swallow the whole thing as a drug of abuse, so often they are out of stock seemingly because of shoplifting, or not sold at all because the pharmacies don't want to deal with the hassle.

Anything that goes directly in your nose has the potential to cause rebound congestion after a couple days which can be pretty bad.

unfortunately everyone is now doing this with LLMs, it actually feels like it might be on its way to being a negative signal, as strange as that sounds.

do you know why residencies value the number of research items? Why would having a large number of garbage papers be seen as a positive signal at all?

Attendings and existing residents are consulted in the ranking process, they are picking people they will have to work pretty closely with for 4 years, they have skin in the game. Why does anyone put any weight on such a clearly bogus metric?

residencies have decided to outsource part of their hiring decisions to journal peer-review processes. so now for some submissions, editors and reviewers are not actually doing scientific peer review, but rather screening job candidates for hospitals.

peer review is built to assume good faith work by people who are all part of a community of scholarship, it can partially hold up to people within the community gaming metrics. if people are just going to appear, game the system to publish some papers, and then disappear into their real careers, there's no hope of this working.

i don't understand why residencies want med students to publish papers anyway. it's very difficult to do good scientific research, it requires training, time, and almost always apprenticeship. none of this is part of the medical school curriculum, which is why we need special MD-PhD programs for people who want to do both. nobody expects that doing a PhD in biology or epidemiology would give you any clinical know-how, why is it reasonable to expect the reverse?

this paper makes a lot of modest, carefully hedged, and reasonable claims.

in its tone however it's written as if it's a brutal takedown of... somebody's perspective. It's hard to tell whose or what perspective exactly. Maybe I'm just misreading the writing style.

(Personally, I think the general case here is one of the better objections to computationalism about consciousness. You can make it even more absurd.

There exists some isomorphism between the velocities of the molecules in a glass of water, and the states of a Turing machine simulating a human mind. So is the glass of water conscious? Actually there are many such isomorphisms to many possible conscious minds, so is every glass of water simultaneously having every possible conscious experience?)

for a truly profound and powerful buzzword, you can even honestly and accurately call what you've done "neurosymbolic AI"

I believe you, but if you are ever in a position of authority, please don't expect anyone else to function well on 4 hours of sleep.

it has been known to happen.

For example, spearheaded by Knuth, the community effectively abandoned the Journal of Algorithms and replaced with with ACM Transactions on Algorithms.

however it's difficult. a big factor is that professors feel obligated towards their students, who need to get jobs. even if the subfield can shift to everybody publishing in a new journal, non-specialists making hiring decisions may not update for a few years which hurts students in the job market.

On the whole you should rarely read papers, you want to read a whole literature in an area. Academics embedded in the field can do this easily. Academics outside of an area know to do this, and to bounce things off an expert to make sure you have the context and aren't over-indexing on a flashy result. Everybody learns the painful lesson in grad school to not just read a paper and believe everything will work as it says.

Somehow the general public and policymakers got the idea that if a paper gets published in any non-fake journal, this is an official endorsement that it's 100% correct, everything in it can be read in isolation, and it's safe to use all claims in the paper to direct policy immediately.

I think academia is partially to blame for encouraging people to believe this rather than insisting on explaining the nuances of how to interpret published research. On the other hand, nobody wants to hear a message that things are nuanced, and they will have to do costly hard work to get at the truth.

I think a world where "you can take any published paper at face value...without going direct to primary sources and bouncing it off an expert in the space" would be great, but it never existed, and it's just fundamentally impossible.

it varies enormously by field.

in CS you will have intense grind weeks around conference deadlines and a more manageable but challenging pace of life otherwise.

in wet lab science you live by the schedule set by your experiments, which often involves intense hours.

if you think of it like a bond it’s pretty fantastic. coupon rate 3.5% and you got it at a giant discount to par even though it’s actually (according to this guy’s beliefs which proved correct) nearly certain to be repaid.

sometimes you can see them do this and sometimes you can see they just work through the problem in the reasoning tokens without invoking python.

sympy is good enough for typical uses. the user interface is worse but that doesn't matter to Claude. I imagine if you have some really weird symbolic or numeric integrals, Mathematica may have some highly sophisticated algorithms where it would have an edge.

however, even this advantage is eaten away somewhat because the models themselves are decent at solving hard integrals.