Chrome has fuckton more of Google telemetry, so it evens out.

Why don’t you just go directly to FaltyDL’s own channel directly if you want to listen to their music, instead of relying on some BS playlist unrelated to the artist? Music seems to be accessible there without Andrew Tate shit.

Perl is excellent for text manipulation! I use it time from time when I need to do more advanced text manipulation in bash. perl -ne ‘[code goes here]’ is good for making one liners in bash.

People use YouTube because that’s where you get biggest outreach. YouTube pay a little, but YouTubers mostly rely on secondary incomes like sponsors and Patreon. Both of these are viable on any other platform.

Podcasts have mainly been using this model for a long time.

The underlying tech doesn’t matter. Only it has an easy to use interface. I just took FTP as an example of technology that already exists today.

Recommendation systems don’t need to be that complicated. In its base form it’s just a list of videos you’ve watched (or content creators or topics). It can then be compared with the watching lists of other people to get an idea of what else you might be interested in. No need for any advanced video recognition.

Maybe this list is isolated within a single instance. Maybe it can be shared between instances. Different instances might use different recommendation systems.

Again, it might not work as well as YouTube’s, but I don’t think it needs to.

Recommendation systems are well studied. I don’t think it’s unreasonable to add some form of recommendation layer separate from (or on top of) the content delivery. It doesn’t need to be up to par with YouTube’s, at least before there’s any major content.

Most YouTubers rely on sponsors or Patreon. Podcasters are doing the same - many of which are self hosting. So I don’t think an ad delivery system is that needed.

I don’t see how it would have to work much differently compared to how Pocketcast or Overcast already works.

The first problem is getting content to the platform.

I don’t have an answer to your question, but suicide isn’t that simple.

Bad things can happen to people, and they would never consider suicide. Good things can happen to people, but they still commit suicide.

I don’t think people always know exactly why they’re suicidal. They might believe it’s because they didn’t get into the dream university or failing exams. It might be a triggering factor, but not the full story.

I don’t believe there’s a checklist of things to do and not to do. Why a person might end up in suicide is entirely personal.

I got a Switch. It’s been mostly untouched for years. Most games that aren’t created by Nintendo themselves are available on Steam. I even played Totk on PC using Yuzu.

Easy solution: host an FTP with all the videos. It has existed long before YouTube was a thing.

More advanced solution: Torrent ala Pirate Bay. High quality videos have been distributed this way long before YouTube even supported 1080p. Peertube is based on similar solution as this.

The main problem is to attract content creators to the platform. The problem isn’t technical.

https://www.nature.com/articles/nmeth.4642

This article use different wording than me, but in essence: Statistics is mostly about using a known model to explain the data. Machine Learning is mostly about finding any model that predicts the data well. Different purposes with some overlap. Some statistical methods are used in Machine Learning, but that doesn’t necessarily mean all of Machine Learning is statistics.

The boundary between statistical inference and ML is subject to debate—some methods fall squarely into one or the other domain, but many are used in both. […] Statistics requires us to choose a model that incorporates our knowledge of the system, and ML requires us to choose a predictive algorithm by relying on its empirical capabilities.

Another (potentially lower quality) article that is not from Nature, but discusses the meme in particular:

https://www.datarobot.com/blog/statistics-and-machine-learning-whats-the-difference/

Because of the large number of variables in machine learning datasets, the models developed from them can be simultaneously extremely accurate and almost impossible to understand. Statistical models, on the other hand are typically easier to understand because they are based on fewer variables, and the accuracy of relationships is supported by tests of statistical significance.

If the cops are reasonable they would initiate an escort.

Given they’re reasonable that is.

Technically not debut, but Sam Raimi’s Spider-Man was well timed.

It was shortly after the run of the 90s TV cartoon. VFX had just reached a point where convincing web slinging could be made. A few years earlier it would’ve looked awful.

I would also say that along with X-Men it started a new era of super hero movies where they could be taken seriously. Compare it to the Batman movies in the 90s, which are goofy in comparison.

The only thing stopping a bad driver with a fast car is a good driver with a fast car!

Especially SUVs. They’re death machines even at normal speeds.

Only a Sith would deal in absolutes. Same goes in programming. Microservices have their benefits . So do monoliths. Neither is going away in the foreseeable future.

Safest bet is probably to do monoliths first. Use microservices once it makes sense.

Bermuda Triangle was quicksand all along!

If parameters aren’t neatly interpretable then it’s bad statistics. You’ve learned nothing about the general structure of the data.

Linear regression models are often great tools for explaining the structure of the data. You can directly see which parts of the input are more important for determining the output. You have very little of that when using neural networks with more than 1 hidden layer.

When CCP did a controlled eradication of pest animals destroying their crops, it caused the great Chinese famine and millions died. Mostly because these pest animals were natural enemies to even worse pests.

They didn’t predict newspapers will contain so many ads it’s almost unusable.

Also, each newspaper is distributed by individual articles, so each article has to be low quality bait.