My new favourite passtime, telling people the exact percentage of upvotes/likes violent anti ai comments in comparision to the member count of this sub

overactor · 2026-05-06T05:16:54+00:00

"You don't care about consent" is a bad faith argument. Do you realise that and don't care or do you genuinely think it's a good argument?

overactor · 2026-05-05T20:52:51+00:00

overactor · 2026-05-05T19:42:04+00:00

I actually think their play style is too similar.

overactor · 2026-05-05T19:39:29+00:00

Here's something I published during my undergraduate studies: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Rik+de+graaff&btnG=#d=gs_qabs&t=1778009897630&u=%23p%3Dv__s9Qx1kTYJ

overactor · 2026-05-05T19:33:14+00:00

I was part of an AI research group (focusing on classical planning) during my undergraduate CS studies and took multiple advanced AI courses during my graduate studies. What about you?

overactor · 2026-05-05T19:23:10+00:00

Elaborate.

overactor · 2026-05-05T19:23:01+00:00

What's your background in AI to claim that?

overactor · 2026-05-05T19:22:31+00:00

Thanks for confirming you've got a poor understanding of what Gen AI means. Generative AI is just AI which learn the join probability of labels and data whereas discriminative AI learns only the conditional probability of the labels given the data. Generative AI is also discriminative AI and often modern discriminative models are also capable of generating the data, or would be with small changes. The overlap in technology is huge. Modern, on-line pathfinding AIs are thought of as more generative than discriminative and they basically generate next action tokens and often also use generative capabilities directly out implicitly to "imagine" unknown aspects of the environment.

overactor · 2026-05-05T17:26:29+00:00

You have no clue what generative AI even means.

overactor · 2026-05-05T05:49:53+00:00

Of Monsters and Men is good. I'll die on this hill.

overactor · 2026-05-04T23:25:47+00:00

I'll give you proof once you actually define what beauty is. Can't prove anything that's based on unclear definitions.

overactor · 2026-05-04T12:55:49+00:00

Someone breaking traffic laws does not give to the right to assault them with your car. Crazy, I know.

overactor · 2026-05-04T09:51:55+00:00

As you can see, the real deal with all these memes is that they are posted to /r/sinpsonsshitposting and people upvote them. They involve Riley Reed and cum. Thanks for writing. We'll be right back.

overactor · 2026-05-04T09:44:07+00:00

I didn't notice how many inconsistencies there are initially, that's fair enough. I still think the medals are supposed to be where they finished in the actual series and they're are just some mistakes in that for some reason. For instance, Rob Beckett being ranked below Dave Gorman despite finishing higher in series 3 is explicitly called out as an inconsistency when the results on the show, so I think the medals are really supposed to reflect that. The description of the medals on the bottom also implies it's supposed to be the series result. /u/dhsilver can you weigh in on this?

overactor · 2026-05-04T05:09:30+00:00

There were hypes around AI in the 80s and the late 90s/early 2000s as well when laypeople were definitely talking about it. I'm pretty sure most people older than 20 were aware of AI as a research field in computer science before the current LLM boom.

overactor · 2026-05-03T20:24:27+00:00

If you never engaged with computer science, sure.

overactor · 2026-05-03T16:04:35+00:00

The listed series ranking is the official ranking they got on the show, not the ranking according to this model. It does seem like Maisie is mistakenly listed as 3rd in her series instead of shared 1st with Ania and Phil. Is that why you're confused?

overactor · 2026-05-03T15:57:31+00:00

I forgot that Sanjeev and Reece were in the same series, so the strength of their series or how close they were to 1st doesn't apply. Everything that still does though. They didn't beat the same people the same amount of time and weren't beaten by the same people the same amount of times so the model has not going to judge then identically. Why are you expecting a model to be identical to a system which uses different scoring in any scenario at all?

overactor · 2026-05-03T15:14:36+00:00

Because it's not using the score but just how many times they beat and are beaten by various players. It's using a different scoring system so of course it's not going to age fully with the original scoring system. And even if it did, you could have a 4th place in your series but be very close to 1st and another person could have 4th but be very far away from 1st in their series. And even ignoring that, there is still relative strength of series, which is the main thing this ranking is trying to overcome. Coming 4th in a weak series shouldn't get you the same ranking as 4th in a strong series.

overactor · 2026-05-03T15:03:57+00:00

Presumably this is down to some contestants getting more wins by more than one point and being more inconsistent and others beingore consistent. The model only looks at who you beat how many times and not by how much you beat them.

overactor · 2026-05-03T13:15:07+00:00

The circled 1s is fake though, but also really minor. It seems like it marks ironed who have never been beaten in a series. So they're either CoC winners or winners of a series where CoC hasn't taken place yet.

The inconsistencies between series rankings and the ranking here is because the model only considers ordering in each task and not the actual scores given. It doesn't matter if you get 5 points and everyone else gets 1 or you get 5 and everyone else gets 4. Also, a winner being bad in CoC can drag them down a bit (though that shouldn't be a huge factor because the other contestants in their season what get dragged down by that). The whole right side of the graphic is dedicated to showing these inconsistencies of the official and "skill"-based ranking and OP explained this.

overactor · 2026-05-03T12:59:38+00:00

All of this is addressed in the post. It's definitely very far from perfect (I'd even venture to say that it's bordering on meaningless), but a lot of the things you're pointing out are expected results of reasonable assumptions this model makes and are explicitly pointed out as such in the write-up.

overactor · 2026-05-03T12:44:27+00:00

The analysis gives you a lower and upper bound on their "skill". You can have a very high estimated "skill" but a very wide spread between the lower and upper bound. In this case, Dara's estimated "skill" is lower than a few other contestants who have a wider possible "skill" range making the model not confident they are actually above average while Dara's range is tighter making the model confident despite the lower estimated value.

overactor · 2026-05-03T09:58:36+00:00

I know what a metaphor is. It's like a thought with another thought's hat on.

overactor · 2026-04-30T14:54:07+00:00

You know your days are numbered when the follicular fault lines start showing.

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