This is only true if you can find someone else selling them at cost.

If a company has a product that cost them $150, but they would ordinarily sell piecemeal for a total of $250, getting a stable recurring purchase at $200 might be worthwhile to them while still being a good deal for the customer.

I would argue that puzzles in commercial collections are more likely to have that problem than ones made freely available by hobbyists, as commercial enterprises inevitably cut corners on things like labour costs for an actual human setter.

I have seen dozens of commercial puzzle games and applications that do not make any attempt to verify the (auto-generated) puzzles as solvable, but I don't think I've ever had the same problem on a site like LMD.

No, the user's recourse is to stop using the streaming website and go back to piracy instead.

Any speedbump to UX is a lost customer. You can not and should not assume that users are going to jump through hoops, because the overwhelming majority will not.

Knowing exactly what they look like would help, but the point is more that you're supposed to look them up and see if they match to rule out regions or confirm suspicions. You've got the wealth of human knowledge at your fingertips, use it - if knowing what a Kentucky numberplate looks like might be useful, you can just look that up in a matter of seconds.

> Also, picture has to contain all these clues of course, conveniently, including a couple of street numbers.

Given how many times this individual has narrowed down an exact location from a photo of a straight road with nothing but trees on either side, I think it's fair to suggest that he was picking an easy target for the purposes of tutorialisation.

It might take more than a couple of minutes to narrow down a photo with less obvious clues than this one, but it's fairly difficult to take a photograph outdoors that doesn't give away enough for someone with sufficient knowledge to identify exactly where it was taken.

Exactly the same thing that Rainbolt did in this video: cut down the amount of work you have to do on each street from checking dozens or potentially hundreds of photos/angles to just 1-3.

Of course if you've only narrowed the streets down to 20,000 candidates instead of 20 of them, that doesn't get you straight to the answer, but it's still a massive proportional improvement.

But the lesson being presented here is to use data that's available to you in the photograph. Maybe you don't have any street numbers (or any particularly useful ones) visible, but you can see the sun at the end of the road and therefore know that it's running directly East-West. That filters out tons of roads. Maybe you can see that houses are only on one side and a river is on the other, you can use that as well. In the video he mentions similar constraints with regards to local parks as being other options for this kind of search narrowing.

The point of that portion of the video isn't "hope the house number is really weird lmao", but to extract any geographical information out of the image and then query that with open mapping databases. House numbers are just one of the most common ones, and while they're typically not quite as powerful as was shown in this video, they're very often going to help dramatically.

There's certainly regions of the world where doing this would be much more challenging (e.g., Central Africa, China, rural India), but the stuff he covered in the video is going to be extremely helpful in the vast majority of cases.

But to answer the "why?" - likely because this type of AI is a tool that is going to become universal very rapidly, and the overwhelming majority of the population has little to no understanding of the finer details of the technology. So the default persona has been fine-tuned to include the annoying "as an AI language model [...]" disclaimer very frequently, amongst other disambiguations, couched remarks, and clarifications that a power user would not necessarily require.

In theory channel owners have the ability to handle that for YouTube specifically, but in practice the tools and incentives aren't there to make it actually happen.

Pretty much every other social site of note doesn't have a rep for moderation, on account of not having moderation at all. A solid 20% or higher of the YouTube comments I see are straight-up phishing scams, Facebook and Twitter are complete cesspits where only content that's literally illegal to post ever gets removed, and the less said about imageboards the better.

Wikipedia is the only even remotely comparably large site I can think of that actually has anything resembling moderation, and you'll find the exact same crowd criticising them for enforcing their rules as well.

It's difficult enough to find anyone willing to actually put the hard yards in to moderation as it is, let alone when all of the resources and tools currently at moderator disposal get shut down.

The idea of colour-coding the parties at all didn't really become widespread until 1980, and the exact colours in use weren't standard until the aftermath of the 2000 election - ABC had initially used yellow for Republicans, and even as late as 1996 The Washington Post, Time, and NBC were all still using blue for Republicans and red for Democrats, in line with the colour schemes of most other nations.

Captain Disillusion is definitely up there. His Flight of the Navigator video is one of the most remarkable things I've ever seen on the internet.