It is great that he’s doing this and it’s making the world a better place.
It’s a bit disappointing that in articles like this there’s relatively little discussion around what organisations receive the money and what impact it has.
We should ultimately judge people by that, not abstractly by “charity == good”?
If a billionaire donates millions to the Against Malaria Foundation I would judge that differently than a donation to an art museum in a developed country - and I think people should, and it matters morally.
The difference between for profit and non-profit isn’t really important either compared to “what concretely did they spend money on and what does that plausibly achieve”.
(Tbc some cause areas he donates to are explained, and they seem reasonable and close to his life, but unfortunately not in any depth).
I think what would be great is to have eg a concise example where it works well for you and a concise example where it doesn’t. This shows you have explored it and thought about it enough to explain interesting observations. It’s good to then be ready to go deeper if of interest.
> The authors warn the consequences are already becoming visible. AI-generated papers could overwhelm peer-review systems with low-quality work …
It seems like a key problem here is that peer-review is expected but not explicitly funded/rewarded while it is probably one of the aspects where humans still add a lot of value. Academia’s incentives are hugely misaligned (… as usual unfortunately).
Yeah 3 - 4 is typical in STEM at Imperial, depends on the scholarship or funding source. The standard funding tends to assume 3 - 3.5 years, but I vaguely recall that in some departments supervisors had a habit of forcing people to stick around for a few months without funding.
I was in a similar situation as the parent post and skipped/was moved up by two years of high school.
I think it was very beneficial to have to work hard to catch up with more advanced classes. I feel flexibility around this is something parents and schools should take seriously.
(Tbf I was also super lucky to find a very accepting group of nerdy friends in the new year that would tolerate someone younger.)
There’s also a vague argument around hedging some actual risks that some market participants genuinely want to hedge… which depends a lot on the specific bet. Eg hedging exposure to specific political events, wars or even company announcements can be relevant and worth a premium for non-insiders. Where there’s a premium to be collected there are speculators to do so.
> “Hedge funds invest a ton in "alternative data", like credit card transaction data or satellite-imagery (are Walmart's parking lots full?) and need to process as much relevant information as possible to make predictions that are relevant to investments. “
Ah yes the famous credit card data and Walmart parking lots example that hedge funds were giving a few years ago in every interview and news article. Safe to assume that specifically these data sets are not what you should look at to make money.
It's possible but unlikely given the short timeline, diverse questions that require multiple matheamticians, and low stakes. Also they've already run preliminary tests.
Interesting topic and seems like a reasonable thing to study.
It would be cool to see a study where participants behave in a way that leads to more light exposure in month A and the opposite in month B, randomising the time ordering etc.
Despite power analysis and all the “50 people convenience sample, mostly observing based on what people do anyway” seems a bit like it won’t really lead to any action guiding outcomes beyond vaguely confirming people’s priors? As in, perhaps this style of research is not ambitious enough in a way?
Yeah sure SU(2) up to sign is isomorphic to SO(3) and whatnot…
I think it’s probably mostly the computer graphics history and the cool name that gets people excited about quaternions?
I like quaternions as much as the next guy (I’ve used them in numerical computations etc), but what is it about them that makes them show up on the front page every few weeks?
Imo the fun quant stuff these days is about predicting returns and not pricing derivatives. As others have said here, the pricing part is mostly commoditised and more about managing software.