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Wait, this makes it sound like you were doing it by hand? There’s quite a few tools to do that for you, e.g. https://github.com/j0be/PowerDeleteSuite
Wait, this makes it sound like you were doing it by hand? There’s quite a few tools to do that for you, e.g. https://github.com/j0be/PowerDeleteSuite
I always thought the Mer de Glace at the Mont Blanc illustrates this really well. You arrive and there’s a sign “the glacier was here in 1910” and that’s where tourists back then.
To get to the actual glacier, you have to eall down many flights of metal stairs for about half an hour and there’s several signs for different years, 1950, 1990, 2002, 2006, 2009, 2012, 2014, 2015, something like this, with the years between each sign getting shorter but the distance staying roughly the same. And from the top it’s really far away.
Of course, once you actually reach the glacier, you get to the main attraction, a 3m diameter tunnel they bored 100m deep into it as a tourist attraction with ice sculptures inside. Above the tunnel you can see the remains of the tunnel from the previous year, half melted…
Uhm, this came out as part of a law suit against them by the record industry? So they are in the process of being sued.
While not surprising, the admission, which was made as part of court proceedings responding to a massive recording industry lawsuit against the company, shows yet again that many AI tools are trained on, essentially, anything that companies can get their hands on.
It’s not. A single miner often has like 4 GPUs running at 100% load, 24/7 and I doubt someone will build a 100 Megawatt facility with thousands of computers to get fallout tokens.
Though it is the same thing in the sense of running computer to generate worthless digital tokens. The main difference in that sense is that fallout tokens do actually have a use(in game)!
Have you tried Jellyfin? It’s a FOSS fork of emby, so pretty much a drop in replacement and it’s been working very well for me.
Personally I use jellyfin as a backend, with the web interface and jellyfin app as frontend. Plus Kodi as an additional frontend for my beamer, with the Kodi Jellyfin plugin and Yatse remote to make it feel more like a TV.
Just to add to this, because it’s fascinating. GPS satellites signals are about as strong as radiation from a light bulb, 20000km away. The signal that arrives on earth is 20db weaker than the noise floor, so background noise is a lot stronger than the signal is.
The way it works is that the background noise is random and the signal is repeated many times a second, so you can split the signal and add it together. The random background noise averages out and you’re left with a strong signal. But due to this, it’s enough to have a very weak signal that adds non random noise on the correct frequency for it to just break.
And actually what I desribed above is just the first layer of a GPS signal, it gets a lot more complicated with signals within signals, it’s pretty crazy how well it works. this is an amazing write uo on how the signal actually works, in case anyone is interested
Adding a copilot button to a laptop, 10 years jail