…are you serious?

There would be so much data in understanding people’s light usage. For example, you could figure out how late or early people get up, number of people living in a house, how crowded the house is, how many lights are used per room, etc etc. it would be a gold mine of information.

Let’s say you’re a home automaton designer. You want to design devices to be used in the home, but in order to design such devices, you need enough of a stockpile of user data. This lightbulb data would be incredible valuable.

You can probably even analyse the data and determine things like whether someone is watching tv late at night.

From a nefarious view, how valuable would this data be to robbers and thieves?

Unfortunately here in the UK there has been systematic defunding of things like libraries.

This wasn’t what I read but this looks excellent.

https://archive.org/details/jonah-edwards-presentation

Another super interesting story is about Marion Stokes, who recorded around 71000 cassettes worth of television media from 1975 to 2000s. She houses them in 9 apartments. I need to watch the documentary about her. https://en.m.wikipedia.org/wiki/Marion_Stokes

I remember I started reading about about this when I wondered what kind of media is “safe” for storage. It sounds like a simple question but it’s not. Digital media, unlike print media, is so easy to lose.

I love how so many comments and replies ascribe some form of ‘guilt’ to this, as if HP employees would feel shame. This doesn’t really mean anything to a company that size.

One of the great things about moving to the UK is that, despite all its problems, consumer protection Europe is so much better than in the US.

Sorry, I think you misunderstand that I’m talking about a large scale problem rather than a personal problem. Of course people can individually download videos to preserve.

Imagine losing YouTube’s videos next week. You would have effectively lost nearly two decades worth of media chronicling human and technological development (more if you take into account that YouTube has repositories of older media).

Someone described it like the Library Alexandria. In terms of density of information, I think the comparison is apt.

A good comparison that might be too old for some readers. Back in the 80s and 90s, the early internet was populated via usenet discussions. Google eventually bought this data and merged it into Google Groups. However Google Groups was disbanded. This meant that some archives can no longer be accessed because to do so requires some active component no longer in service. We have effectively lost gigantic chunks of early 90s internet history. A lot of this history was quite important in many facets of life.

There is already something like this via the Wayback Machine (who indeed do copies of video media but more typically VHS and other things) and things like the Russian Library genesis, which is kept in torrent format.

The problem really is that storage for video media is insane compared to storage of document or even photo data.

If people here haven’t read into it, it’s incredibly interesting to look into the way the Internet Archive works. In particular you have to begin to concern yourselves with how long it takes for HDs, SSDs, and other media to degrade in time.

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Hmm to be fair with YouTube you don’t think this is now a repository of incredibly valuable resources? If YouTube went down and we lost all videos, we would be losing many important resources, from historical documentaries no longer easily found in media, to guides on woodworking.

It’s a bit scary. Once you remove the crap, it’s an incredibly valuable library resource and time capsule.

I just noticed this.

As others have mentioned the stars have been largely useless in the last little while so to be honest I’m not sure this has any impact. Even sites that try and give a rating based on fake reviews are not helpful because so many reviews are faked. The only helpful part is to try and read negative reviews.

I imagine this star fiasco is something that’s easy for browser plugins to reverse.

I would love to see AI and Machine Learning used to filter out fake reviews. This would actually be useful.

Yes.

I think with something like this you have to do a literature search. Even then it’s kind of tough because I’m sure it’s very hard to do objective tests of these traits.

You might say that any activity has similar aspects. Learning a difficult passage in music, learning to speak languages, learning to throw a basketball through a hoop, etc.

I’m not sure there is a huge amount of evidence that video games teach resilience any more than any other similar activity. Moreover, it’s easily the kind of thing that our biases set us up to believe things that aren’t there. For every person who learned resilience from video games, there might be three other people who learned poor lessons, like “I should be lazy and play video games and not study for my exams.”

With academic or professional resilience, I can’t say I’ve seen any positive correlation with video games.

I could easily argue that excessive video game play makes you less resilient to doing non-video-game challenges.

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As a scientist I briefly read the Twitter chain by the company with some description of their methodology.

Honestly I didn’t really follow it and it’s hard to critique based on buzzwords and Tweets. The person who was posting it sounds like a businessman, throwing jargon and words rather than something coherent.

Ultimately I think that people are surprised by figures like “50% of gamers are female”. It might be 30%, or it might be something else. Maybe asking the questions a certain way biases the responses a certain way.

It’s hard to glean anything based on what I’ve seen. I don’t have any skin in this game, and I don’t care either way, but all I’ll say is that it’s hard to figure out the truth based on the information available.

Women also make up 50% of PC video game players and 54 percent of mobile game players.

I find a lot of these figures really hard to believe, to be honest.

Looking at the link, there is little I can find about their methodology.

Part of the problem with AI is that it requires significant skill to understand where AI goes wrong.

As a basic example, get a language model like ChatGPT to edit writing. It can go very wrong, removing the wrong words, changing the tone, and making mistakes that an unlearned person does not understand. I’ve had foreign students use AI to write letters or responses and often the tone is all off. That’s one thing but the student doesn’t understand that they’ve written a weird letter. Same goes with grammar checking.

This sets up a dangerous scenario where, to diagnose the results, you need to already have a deep understanding. This is in contrast to non-AI language checkers that are simpler to understand.

Moreover as you can imagine the danger is that the people who are making decisions about hiring and restructuring may not understand this issue.