smoothbrain coldtakes

why would you take anything you see on the internet seriously?

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Joined 2 years ago
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Cake day: June 26th, 2023

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  • There are easier ways to spy on your employees. This is not cost-effective.

    I use Zoom for work now and each call can be several gigabytes large, depending on resolution of shared materials and a few other factors. If you want to save that kind of stuff long term, you have to pay to keep it somewhere. If you multiply several gigabytes over a few dozen calls a day, you’re going to end up with terabytes of garbage you need to store. Zoom also informs you of when a recording is starting and active, offering for you to leave the call or otherwise implicitly agree to being recorded. You have to pay for all these things because there’s a significant amount of processing power involved. It’s not like it’s free to run facial recognition and speech recognition.

    When I did contract work for Apple support, the spying was way more efficient than just listening to my calls. My supervisor could literally always see my monitor through the chat program we had installed. There’s all kinds of remote software for things like this. If an admin wants to see you misuse your equipment, they have easier ways of finding out than sifting through calls to find wrongthink.












  • It’s also only valuable if people keep contributing to it. It’s highly likely the majority of current existing reddit data has been largely incorporated into many LLMs prior to the API access limiting. Google paying them 60 million dollars is a hilarious pittance to keep training their LLMs, given how much money AI services will likely generate off of the training data.

    I don’t actively use reddit anymore, but when I need an answer to something that isn’t programming-related, it’s usually the top source on any given web search. That kind of content is basically the only stuff I would give a shit about. I can’t imagine how much absolute garbage you have to sift through on the platform to get reliable training data. Maybe the ratio is terrible and that’s why Google paid so little.