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This is a major problem for all democracies, and LLM driven troll accounts probably do exist. But this xitter post is a fake error message. It’s clearly a troll.
Blocking fake accounts would help with the misinformation problem, but it’s a cat and mouse game. It could ultimately give additional credence to the trolls who slip through if the platform is assumed to be safe. The reality is that there will always be ways for fake accounts to avoid detection and to spoof account verification. Making it harder would help, but it’s not a comprehensive solution. Not to mention the fact that the platform itself has the power to manipulate public opinion, amplify their preferred narrative, etc.
The solution I’ve always preferred is the mentality the 4chan community had when I was younger and frequented it. Basically, and I’m paraphrasing:
Everyone here needs to grow up and understand that no post should ever be presumed to be true or legitimate. This is an anonymous forum. Assume that everything was written by a bot or a troll in the absence of proof that it wasn’t.
I think people put too much trust in social media precisely because they assume that there’s a real person behind every post. They assume that a face and a few photos gives an account legitimacy, despite the fact that it’s trivial to copy photos from a random account (2015/16 pro-Trump Facebook style) or just generate all of the content from scratch with AI (to avoid duplicate detection).
Trust itself is driver of misinformation. On social media, people should only fully trust posts made by people they know. That is the simplest and most comprehensive solution to the problem.
This problem desperately needs to be fixed, but the solution isn’t some expensive, over-engineered laser LED matrix. The solution is basic headlights that don’t blind people. You know, like every headlight that existed in the US until a few years ago.
Surely it’s not an insurmountable task to use a cheap LED bulb with the optics to give the beam proper directivity—i.e. not direct the beam into the eyes off oncoming drivers. Maybe even make it replaceable with a screwdriver. Call me crazy.
Surely the original “someone” is Meta. Good to have a redundant system I guess /s
Whoosh
Edit: My point was that a couple of kids doing this on a small scale pales in comparison to Meta’s reach. The students didn’t do anything particularly novel, and Meta, which has a much more comprehensive dataset of faces linked to personal information, personal communications, etc, is already using every means available to do the same thing. The college students simply demonstrated what Meta is already doing on a global scale.
Hal Finney, no?
The software engineer, cryptography expert, and cyberpunk who received the first ever Bitcoin transaction and had a neighbor named “Dorian Satoshi Nakamoto”?
There are. There isn’t any difference. It’s like people being afraid of facial recognition for border checks. It’s creepy at first, but governments already have pictures of everyone’s faces from their ID’s. They don’t gain anything from the additional photo except efficiency to speed up a process that’s already in place.
Edit: I will say that I would never want a government app directly linking my ID to my phone unless I could be absolutely sure it wasn’t doing anything creepy in the background. I wish sandboxing apps was a default feature for all smartphones.
I’m an EE and audiophile who did a bit of audio engineering in university for the student radio station. Our station had a whole rack of hardware audio processing tools, but honestly, this DSP software does a better job of making broadcast audio sound professional than anything else I’ve used—including some mastering VST’s I’ve used in music production. Highly recommend it.
I wouldn’t worry about the extra features. Most of the ones you’ve listed are used to clean up bad recordings, but that’s something you’re in control of here.
For recording, the software doesn’t matter much. The most important thing IMO is to record at a level where the typical amplitude of the input audio (normal speech in this case) sits at around half the max level of the input. That’s because you can always increase the volume level after recording, but once a loud segment clips above the max level, that distortion is there forever. Recording in 24-bit vs 16-bit helps with this strategy, because the extra bit depth in recording amplitude resolution allows the headroom to boost the volume later without any perceptible loss. Large diaphragm mics sound best for voice recording. Of course, I’m not recommending you run out and buy a large diaphragm USB mic that can record in 24-bit if it’s prohibitively expensive. I don’t know what your setup is currently, and for most listeners, good mastering will make a bigger difference than great recording gear.
Stereo Tool can make almost anything shine, but if that’s too pricey as well, just find a post processing tool with a good compressor/limiter combo and an expander. There are probably good open source tools out there.