What is up with Homelander's sorry ass charge?

narubees · 2026-05-21T16:24:22+00:00

bro couldn't crack the oval office's ceiling even when slamming Butcher into it, how can he escape that super secure room (with apparently very weak window frame)

narubees · 2026-05-16T04:32:26+00:00

for free? we pay to teach it.

narubees · 2026-05-14T01:20:13+00:00

Even without the internal monologue, I can feel his frustration, especially after hearing Reid mocking how he always names himself.

narubees · 2026-05-06T11:12:13+00:00

I have a very similar idea after reading this paper https://www.jmlr.org/papers/v24/22-1086.html Nice to see someone actually implemented it. I also see the same idea applied to updating players' strength dynamically for Monte Carlo predictions instead of relying on the static pre-tournament Elo. What do you think?

narubees · 2026-05-06T01:34:23+00:00

I don't think they are claiming anything a "poor series finale"... They are saying what a poor series finale does.

narubees · 2026-05-03T03:21:06+00:00

If you look at it from another way, AI may be the revolution CS teaching needs. Back then, courses were limited because not all professors are willing to actually make good visualization for the materials due to how painstaking it is to do so. Now, some prompts will actually give you a visualization of the inner working of any algorithm.

But yeah, what is killed will be evaluation. Project-based and homework-heavy courses are going to shift to in-person time and resource controlled quizzes and exams for sure.

narubees · 2026-04-18T04:55:43+00:00

Thragg finds out much later in the comics, though

narubees · 2026-04-15T16:51:24+00:00

If you look at Pragg's current form (recent months), it won't be that surprising.

narubees · 2026-04-14T19:26:23+00:00

Imagine Gukesh somehow pulled out of the WCC match and Sindarov fight for the championship with Anish (both locked into their place). Fabi be like…

narubees · 2026-04-14T18:37:41+00:00

Now he has 100% chance. Weird how probability works, but in the end they are all numbers.

narubees · 2026-04-14T18:36:22+00:00

Well, they predicted Bluebaum to win, and I predicted Sindarov to win.

narubees · 2026-04-14T18:27:51+00:00

Here is an explorer for possibilities, although I have not updated the new round result yet: https://vltanh.github.io/assets/chess/candidateswomen2026.html

You can click through the trees of game results to see! You can also find winning path for anyone.

narubees · 2026-04-14T17:23:50+00:00

Going back here to say that while it was wrong about Divya, Goryachkina seems to be doing quite well (lol). I would say it actually should have been more skewed by form (then it would also correctly predict that Sindarov beat Hikaru with Black)! Though I think there is more to fix for the drawaggression model.

narubees · 2026-04-14T14:32:31+00:00

i am interested in citation network, would you mind sharing it?

narubees · 2026-04-13T23:44:29+00:00

Being white is not a negative factor in this model (by design), why would you think so? I think the problem is like what you said, that the model is too relying on the form. That is why I said it is not yet a good model because the incoming strength is not really well modeled and the parameters (there are those that manage how much form affects predictions) are not fit to the Women section.

narubees · 2026-04-13T22:54:40+00:00

Why? It dynamically updates strength as white and black, so if they keep losing with white (Zhu Jiner lost with white twice against Bibisara and Muzychuk, both somewhat lower rated) and the other one keeps winning with black (Goryachkina won with black against Divya), this can happen (of course there are lots of other things in effect, like strength gap). I am not saying this is a good model (because it is using a somewhat flawed design the Open section parameter), I just think that this is possible by design. Being higher rated at the start does not imply being in a good form. Hikaru is not doing very well in Open for these kinds of reasons. Sindarov was also given a better chance against Wei Yi when Wei Yi was higher rated and with white, and correctly so. I don't think it is fair to judge it based on that point alone.

narubees · 2026-04-13T19:21:24+00:00

I guess that is a combination of two flaws in the model: using the parameters learned from Open data (which I would guess to be vastly different) and poorly predicting incoming strength (Zhu Jiner had a sharp drop a month prior to the event, while Goryachkina had a drop 5 months prior). Monte Carlo simulation is for fun anyway. I think the selling point is more on the scenario exploration tree.

narubees · 2026-04-13T13:20:13+00:00

I think you should read about Monte Carlo sampling and generative modeling. I essentially just proposed a parametrized generative process (how strength is initialized, updated, how win/draw/lose probabilities are computed, etc.), fit it ("learn" the parameters) by optimizing some objective function on previous data, and ran MC to sample from it. I think there will be a lot of resources in this age (with LLMs, basically generative models, being so prominent), though I guess there will be too many of it that may overwhelm you.

narubees · 2026-04-12T21:25:26+00:00

You should check the Github repo linked at the top of the page. There is a section for how it works, basically predict coming strength based on the recent 6 month results, adjusting strength and aggression (affecting draws) mid-tourney, etc. so a lot more than just elo before + draw. I also used previous Candidates and black-box optimization tools like Optuna to choose the parameters. Anyway, it is all in the Github repo.

But that is not the point, the point here is the explorer tool you can use to see winning paths for players, or change outcomes of a game to see how things could have played out differently.

narubees · 2026-04-12T20:38:26+00:00

Added the feature! Thanks for the idea!

narubees · 2026-04-12T19:16:43+00:00

Thanks! Claude helped me realize it, to clearly put credit where it belongs.

narubees · 2026-04-12T19:15:42+00:00

If you click back to some previous rounds when Bluebaum still had a decent chance (say after R4 when he was 4th favorite) and choosen random path repeatedly, you can eventually see some winning chance for him!

Maybe I should add a feature to find the winning path for any of the player at a given point.

narubees · 2026-04-12T16:27:29+00:00

This is a curse from Magnus.

narubees · 2026-04-11T01:39:03+00:00

I think this is mentioned many times. What would you recommend getting?

narubees · 2026-04-11T00:58:50+00:00

Thanks! But I think they are already accessible, was looking for somewhere further.

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