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Joined 3 years ago
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Cake day: May 31st, 2023

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  • I agree with your first point, but the latter two:

    —GPS data that could be stored and extracted from the dealership and sold or given to the government, insurance companies, and law enforcement. —GPS data that could be sent in real time if the car has a cellular connection or hijacks the cellular connection in your phone when you connect it to the car.

    Why do you think this is more likely to happen with this new regulation, when most modern cars already have a functioning GPS module for navigation and cellular connection for software updates?







  • Maybe we should clarify what a slur is? Because to my knowledge, a slur is a term that has such negative connotations that it is considered offensive and discriminatory against a certain group of people in itself, without any additional context. You simply do not use it unless you want to insult or offend someone from that group. If a term is only offensive based on how it’s used, it’s just a regular insult, not a slur.

    So, “can be used as a slur” is not a thing. A word is either a slur, or it isn’t. Neither trans nor cis are slurs at the moment. I’ve never seen trans be used as an insult before. And even cis is almost never meant as a direct insult, merely as a reminder that someone is talking about things they have no lived experience with and should probably check their privilege. Yes, that can be in a demeaning way, but the goal there is not to hurt you, but to make you piss off. It’s an act of self protection. Nobody is seeking cis people out and starting to call them names unless they insert themselves into trans spaces and start talking shit about trans issues. If you’re doing that, and getting told off insults you or hurts your feelings, then, frankly, that’s a you problem.








  • From the article:

    For many years, we’ve had software that can generate lists of valid conclusions that can be drawn from a set of starting assumptions. Simple geometry problems can be solved by “brute force”: mechanically listing every possible fact that can be inferred from the given assumption, then listing every possible inference from those facts, and so on until you reach the desired conclusion.

    But this kind of brute-force search isn’t feasible for an IMO-level geometry problem because the search space is too large. Not only do harder problems require longer proofs, but sophisticated proofs often require the introduction of new elements to the initial figure—as with point D in the above proof. Once you allow for these kinds of “auxiliary points,” the space of possible proofs explodes and brute-force methods become impractical.

    So, mathematicians must develop an intuition about which proof steps will likely lead to a successful result. DeepMind’s breakthrough was to use a language model to provide the same kind of intuitive guidance to an automated search process.