Titles and thumbnails have a huge impact on video performance, and when it's your main income it seems reasonable to try to marginalise the impact.

Right, but then there's this thing called "shared reality" and once you break it, all kinds of bad consequences happen.

This is even worse, as it also breaks temporal continuity for individual reality. E.g. I expect that if I saw a video titled X today, I'll be able to find it under title X tomorrow, and if I can't, it's one of the rare/marginal cases when it got banned/deleted/retitled, or I just misremembered. Titles becoming unstable in the general case is a bad situation.

Gaslighting is now a government policy

And video performance = ad revenue.

Badly phrased but not wrong, this is the minimum frame rate for humans to perceive motion as supposed to a slide show of images.

The maximum frame rate we can perceive is much higher, for regular video it's probably somewhere around 400-800.

Maximum depends on what it is you are seeing. If it’s a white screen with a single frame of black, you can see that at incredibly high frame rates. But if you took a 400fps and a 450fps video, I don’t think you would be able to pick which is which.

I would love it if you had time to publish it!

I think what you're looking for is a bike.

Could you elaborate what you think the problems are? I guess they should be using some form of multiple comparison correction?

The daily scale is not statistically significant and is meaningless. You should lower the confidence interval by either increasing the scale or the evaluations.

Until you need to schedule GPUs or other heterogenous compute...

Are you saying that running your application in a pile of containers somehow helps that problem ..? It's the same problem as CPU scheduling, we just don't have good schedulers yet.. Lots of people are working on it though

Not really? At the moment it's done by some user-land job scheduler. That could be something container based like k8s, something in-process like ray, or a workload manager like slurm.

LLM summaries of papers often make overly broad claims [1].

I don't think this is a good example personally.

[1] https://arxiv.org/abs/2504.00025

When there's nothing else to go on, it's still more useful than nothing.

The story was being upvoted and on the front page, but with no substantive comments, clearly because nobody understood what the significance of the paper was supposed to be.

I mean, HN comments are wrong all the time too. But if an LLM summary can at least start the conversation, I'm not really worried if its summary isn't 100% faithful.

But there has been continual improvement over that time, both in the ecosystem, and in the language (like a syntax for generics).

NileRed?

Not currently, but it is being worked on https://github.com/ray-project/ray/issues/53976.