hgibbs

If you want to work in a Hilbert space (i.e. have angles) then you are stuck with the euclidean metric up to scaling of the axes.

Can you give an example? I am unfamiliar (and interested).

The term "matrix derivative" is a bit loaded - you can either mean the derivative of functions with matrix arguments, or functions with vector arguments that have some matrix multiplication terms. Either way, I don't really understand what the confusion is about - if you slightly modify the definition of a derivative to be directional (e.g. lim h->0 (f(X + hA) - f(X))/h) then all of this stuff looks the same (vector derivatives, matrix derivatives and so forth). Taking this perspective was very useful during my PhD where I had to work with analytic operator valued functions.

Yes UNSW maths. Maybe everybody else had it figured out, but certainly Norman was the first to publicly acknowledge that all the learning would have to be online within a few months.

I made a public bet with Norman in early 2020 (late Feb) about whether the university we were at would hold classes until the end of the term (he believed they would not due to covid). Norman was the only one with the guts to publicly point out the obvious (anybody with the Wikipedia page for China case numbers and a spreadsheet could have figured out what was going to happen in late Feb). Among other things he was a great lecturer and a talented go player, although I never really thought that rational trig was worth all the effort - regular math seems to have plenty of utility even if you think it is built on shaky philosophical foundations.

I'd like to plug riptables (https://github.com/rtosholdings/riptable), which is (more-or-less) a performance upgrade to pandas.

Earthsea is great. Ursula also wrote a lot of amazing science fiction: left hand of darkness, the dispossessed, the lathe of heaven, the word for world is forest etc. All are worth reading.

I would appreciate references on the time complexity of merging sorted lists (if I am not worried about space complexity at all), for arbitrary n and m. There is an excellent discussion in Volume 3 of TAOCP, but the references within are quite old.

Why do you say it fits very few uses cases?

Having a paper published can take a very very long time, a year is quite short and 6 months is basically the minimum wait. My last paper has taken 2 years to be accepted from the first time I submitted it, despite it being largely the same as the initial submission, accepted as part of my thesis over a year ago, and having several citations. It is very frustrating, and it also means that easier (and less original) work is easier to publish.

But the symptoms of covid are very similar to e.g. the flu, and this would make you and your partner some of the first people on Europe to have had covid (given exponential increase in case counts it cannot have circulated for long before early 2020). My prior on anybody having covid in Europe in Dec 2019 is extremely low, I think yours should be too - just having been really sick is no evidence at all.

My point is exactly that though - the choice of cost function is subjective. There is no best cost function, just a mapping from costs functions to optimal strategies.

As a point of curiosity, what do you mean by optimal?

To me, I can see at least two (potentially different) cost functions that a Wordle strategy can aim to minimise. Firstly, you can try to minimise the expected number of guesses, and secondly you can try to minimise the expected number of guesses conditional on never losing the game. In principle you could optimise for the first but not the second by allowing a small list of hard words to take > 6 guesses on average.

Part of my point is the lack of an absolute definition of optimal: strategies are only optimal up to the specified coat function.

Very roughly I think you are saying that it is unclear whether rationalists are thinking differently, or whether the think in the same fashion and just think that they think differently?

I suspect their are elements of both: I believe some members of the rationality community do routinely think in a different way to many other people, but I also believe that there is some post hoc rationalisation (as you put it) in the community as well.

Try lesswrong.com

One problem solving approach which I adopted around the time that I was very frequently reading Terry's blog was to personify the problem as a combatant. For example, when trying to prove an inequality that seemed straightforward I would focus on how it could be false, and to then consider what structure the resulting 'conspiracy' of variables would have to have. I have a feeling that this is something that Terry did (and I emulated), but I can't remember a specific post.

He also has a very nice post on 'amplification and arbitrage' as tricks for strengthening inequalities.

I honestly can't think of a use case for excel that pandas doesn't handle better. The 1 million row limit is crazy limiting, it's just nicer to not have to worry about that kind of stuff.

Why?

Why is it ludicrous - do you have a specific issue that you object too? How is living on Mars very different from e.g. the international space station or conditions in a nuclear sub in terms of human habitats? The other bits seem relatively easier than the problem of getting people to the planet. In general I think arguments of the form "it can't be done soon because of resource constraints" are very weak - there are plenty of examples of people making such arguments and being proven wrong a couple of decades later.

Why won't we go to Mars (ever)? You may be sceptical of it happening in the next 100 years but very confident in it happening in the next 500 years, it is a very strong claim to argue that it will never happen in the broader context of increasing global wealth and massive improvements in space/energy technologies.

At the beginning of the most recent lockdown in my city I had been introduced by a friend to magic (specifically commander), and I had played enough with him to have started to be annoyed at how often I was losing - so I went out and bought a couple of decks. My girlfriend and I were immediately hooked, and have been playing every other day since then (2-3 months now). Now that the lockdown has lifted I am able to play with my friend, as well as introduce the game to other friends. It's a lot of fun and I've only scratched the surface of the game; as an example we have only been playing with preconstructed decks, while most people will design a deck and purchase the required cards. I think the game design really lends itself to being enjoyed by programmers: building a deck is about looking for combos/synergy between cards, high level play requires knowing the exact way that turns resolve and how/when you can respond to other players actions. I think there has been a lot of stigma around tcg for a while, but the truth is it is just fun.

As an aside, my gf has been collecting Pokemon cards. The high premium for a Charizard is known as 'the lizard tax' by the community, which I think is hilarious.

I thought a lot of the ideas in snowcrash were very interesting - particularly when you consider that the book was published in 1992 and so a lot of the elements that were cutting-edge on release have had time to diffuse into scifi culture. For example, the potential for 'ideas' to be viruses of the mind, or the degree to which thought is shaped by language.

Thank you for all your suggestions and commentary!

Thank you for your suggestions! I have read some of N.K Jemisin and enjoyed what I read, the others I have not heard of except for Liu Cixin. I've read the three-body problem but I found it a bit jarring how 'magical' the resolution was - it was speculative but in a bizarre/surreal way rather than in a 'plausible extension of reality' way. Is it worth pushing through to the later books?

Can anybody recommend authors like Stephenson? He is my favourite author by far and it's going to be a sad day when I exhaust his works.

Is what you say less true of traditional exchanges? Maybe it is, but I haven't seen someone crunch the numbers - I'd be happy to read a comparison to that effect.

My question was in relation to the parent comments claim that buying puts can cause unlimited losses - I was pointing out that this was wrong. The original comment seems to be edited now

That's not right either, your downside for selling puts is limited by the strike (worst case is you pay K for a stock worth 0). Short call positions are the ones with unlimited downside (worse case is that you get K but have to cover the cost of arbitrarily high priced underlying).

Puts have limited downside?

But how do we get the prices? If I tell you the at-the-money front-month call is $1000 will you tell me the vol is 100pa?