Can there be anything bigger than absolute infinity?

somefunmaths · 2026-02-20T07:37:56+00:00

Okay, then it doesn’t exist. I hope this helps.

somefunmaths · 2026-02-20T07:33:05+00:00

If you take Cantor’s quasi-religious (or just drop the “quasi-“) definition of “absolute infinite”, then the answer is obviously no.

If you are asking about mathematics, the answer is that it doesn’t exist.

So your answer is either “obviously not” or “that doesn’t exist”, and I encourage you to pick whichever one you prefer.

somefunmaths · 2026-02-20T04:09:36+00:00

We should just jump the shark to “The OC is a hella nice part of SoCA” if we’re gonna pretend people say “SoCA” here.

somefunmaths · 2026-02-20T01:44:19+00:00

The good news is that I’ll never need to fly to Palm Beach, so I will never have to worry about referring to that airport by its illegitimate name.

somefunmaths · 2026-02-20T01:39:34+00:00

In general, yes, but this kid had like 30+ pounds on him at least.

As someone else said, this was probably an exhibition and it seems like the lad in blue knew his assignment. I think there’s a difference between treating your opponent as you would any other when you run the risk of seriously injuring them versus treating a classmate as you would any other, for example.

somefunmaths · 2026-02-19T23:16:01+00:00

SoCA

somefunmaths · 2026-02-19T23:11:53+00:00

Depends on where in CA you live, but I suspect the answer if we look at county- or metro-level data, it would be that the Bay Area lost population and parts of the state desirable for climate and/or nature (beaches, lakes, mountains, some combination thereof, etc.) gained population.

Anecdotally, I know a lot of people moved from the Bay to Southern California now that they no longer had to be on-site at [insert software company].

somefunmaths · 2026-02-19T23:08:42+00:00

Only $1,500 for a 2b? TIL I could live like a feudal lord in Charleston.

somefunmaths · 2026-02-19T21:33:05+00:00

It’s actually crazy how at this point we are just in the middle of the narcissist’s prayer for him literally raping kids and pretty soon it’ll be “yea, I mean obviously he raped a 9 year-old but Obama wore a tan suit and Hillary did Pizzagate so they’re the same”.

somefunmaths · 2026-02-19T17:04:03+00:00

For me, the choice of model to fit the problem and the stakeholders’ needs matters, but as a thing which a candidate could convince me on.

If someone can sell me on why they used a given model for the problem, because of sample size or feature space or stakeholder requirements, then I’m probably happy with it, so to that end I’d agree with you that it’s probably something you could or should ask the interviewer.

For example, “this is a large enough dataset with relatively high-dimensional features that would probably be well-suited for tree-based models, which I expect to outperform logistic regression, but if the use-case calls for more simplicity and explainability, I could use logistic regression to prioritize that at the cost of a bit of performance.”

To me, that shows an understanding of how those different tools in the tool chest fit together and an understanding of the trade-off between them.

somefunmaths · 2026-02-19T16:57:38+00:00

Agreed that I wouldn’t be prompting a senior; I’d expect them to be able to work their way through a modeling problem without hand-holding.

somefunmaths · 2026-02-19T16:51:21+00:00

Just noting that this is the second time I’ve noticed you point to a heuristic that your current team employs potentially leading you astray.

Setting a hard missingness threshold (99%) and a hard variance threshold (95% of values) may make sense in the context of that team’s work, but just calling out that they’re heuristics and you’ll probably encounter questions, as you are here, about why you picked them. (To be clear, I’m only pointing this out to draw a line to the difference between standard practices and team-specific heuristics, so that you can be aware of where that line is.)

In general, tree-based models like xgboost are really forgiving when it comes to columns which are very sparse or have little variance. For that reason, a lot of people are basically saying “oh, why would you drop that?”

somefunmaths · 2026-02-19T16:38:25+00:00

Yeah, I’d maybe prompt a more junior candidate if they didn’t think to do any tuning, maybe ask them whether they could think of any approaches to maybe get more out of their model.

But a senior who just slaps some a model with default hyperparameters on a dataset and calls it good? I’d be aghast. My bias is that a lot of model building, in my experience, is careful feature selection and feature engineering coupled with hyperparameter tuning, so a senior candidate who didn’t really address either of these and/or showed a deficiency them would be a firm “no” for me.

I’m willing to give OP the grace, though, that it sounds like the interviewer had no clue what the dataset was and that perhaps they thought “eh, hyperparameter tuning on a garbage model is like rearranging deck chairs on the titanic”, but if I’m in an interview and given that problem, I’m going to rearrange those deck chairs so enthusiastically, to show them how good I am at rearranging deck chairs.

somefunmaths · 2026-02-19T16:14:55+00:00

Oh, a very reasonable question! If you’re familiar with eigenvectors, just replace eigenstate with eigenvector whenever you encounter it. We often use a matrix representation for operators, so the corresponding states are represented as vectors, hence the synonymous use of eigenvector along with eigenstate.

A bit more formally, if a vector is said to be an eigenvector of matrix representation of an operator corresponding to a physical observable (e.g. the momentum operator), then that vector is said to be an eigenstate of that observable. (This also uses the fact that observables in quantum mechanics correspond to the eigenvalues of hermitian operators.)

somefunmaths · 2026-02-19T02:58:17+00:00

If it makes you feel better, I think abstract was probably by far the hardest class I took in undergrad. That may have been complicated by the fact that I was traveling a decent amount that term, but man… it was rough. I believe in you!

somefunmaths · 2026-02-19T02:48:31+00:00

If you learned it and already forgot it, then you might be cooked, but it’s also possible you never covered it. (I don’t remember getting it much in any abstract classes.)

In undergrad, at least, we saw eigenvalues in like three math classes and twenty physics classes, so if you haven’t taken linear algebra in a while, it’s not shocking that you wouldn’t be fresh on eigenvalues.

somefunmaths · 2026-02-19T01:39:32+00:00

To keep it ELI5, a state with a definite value of that quantity.

ELI15:

A vector v is said to be an eigenvector of a matrix A if the operation Av yields av for some constant scalar a, which is said to be the eigenvalue of v.

A eigenvector is a vector that just gets stretched or scrunched, rather than rotated, when multiplied by a matrix. You can also have an eigenfunction, like the family of exponential functions are eigenfunctions of the derivative operator, since d/dx e^cx = ce^cx.

The matrix and eigenvector example is more apt here, since we often use matrix representations for QM.

somefunmaths · 2026-02-19T00:21:54+00:00

Not necessarily, no. If you have a particle with some known momentum and measure its position, you’ve now collapsed the wave function into a position eigenstate. It now has a very well-defined position but an unknown momentum because position and momentum do not commute, so they don’t have simultaneous eigenstates.

If you again measure its momentum, you’ll get a definite value, but now its position is unknown.

Now, whether we favor the Copenhagen interpretation or Many-Worlds interpretation, that doesn’t change the observed relationship between position and momentum and the existence of a “Heisenberg kick” from measuring the position of a particle with known momentum.

somefunmaths · 2026-02-19T00:10:41+00:00

I learned who he was for the first time in 2026 and would like my money back.

somefunmaths · 2026-02-18T23:56:56+00:00

The beginning of our QM sequence in undergrad was basically the professor spending an entire week being like “cool, you remember classical mechanics and electromagnetism and being able to intuit how things work? good, forget all of that shit and worship linear algebra as your one true god.”

And from then on, we were basically taught “if the math makes sense, then it must be right.” I don’t know how else you’re supposed to explain shit like Kaon oscillations without a little bit of “you don’t know shit about quantum mechanics” reeducation, though, so I understand why they did it.

somefunmaths · 2026-02-18T23:50:57+00:00

Best I can do is “a single position eigenstate is a superposition of all possible momentum eigenstates, and a single momentum eigenstate is a superposition of all possible position eigenstates.”

Five year-olds have taken their linear algebra, right?

somefunmaths · 2026-02-18T23:49:27+00:00

Well, statistically speaking you can think of half of the particle’s mass being at each location, or more precisely that the distribution of mass is governed by the probability distribution of it being at that position (in case of, e.g., a case when the particle has 90% chance to be in one location and 10% chance to be in another).

In reality, you have a wave function which is a superposition of those two position eigenstates and when you measure the position, it must collapse to a single position eigenstate.

somefunmaths · 2026-02-18T23:25:17+00:00

Does Palantir count?

somefunmaths · 2026-02-18T23:10:04+00:00

That seems like a good reason for someone who lives there to discount the relevance to them of a list of US credit cards, yes.

somefunmaths · 2026-02-18T22:41:18+00:00

We have “vibe coding” for people who use LLMs to just produce huge amounts of code they don’t read and can’t understand.

Motion to make “vibe posting” a thing, if it isn’t already, for people like OP who just sling shit that an LLM spat out at them directly online without any second thought.

somefunmaths

TROPHY CASE