Cryptography nerd

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  • 479 Comments
Joined 1 year ago
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Cake day: January 18th, 2025

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  • Did you not pay attention to how Kamala was called a liar by media for saying Trump would send the military against cities?

    … And then he did?

    Did you not pay attention to how he claimed credit for Covid funds that Democrats established? Blaming Democrats for Trump judges’ decisions? Setting up Afghanistan so the exit would happen at the start of Biden’s turn to hurt his approval when it predictably turns to chaos? How Biden’s age was somehow a problem but Trump’s never was?

    Media was hysterical about how democrats would make everything worse somehow but never explaining it, then repeating Trump’s claims that he’s deliver the best economy ever and all kinds of bullshit like it.

    And with all that Trump still didn’t even get 50%!


  • Real-time in computing usually either means a real-time OS with guaranteed low latency response (typically for stuff like microcontrollers regulating machines) or streaming live data (low latency delivery of the most recent value)

    This sounds like the latter, and a typical SQL database don’t guarantee real-time updates (you can have “atomic writes” to prevent inconsistency but usually this would make it slower) but some databases like this one are designed to ensure you can read out updated correct and consistent values much faster. Also with standard databases you usually make scheduled individual requests, but a real-time database could often send a stream of updated values to a “subscribing” program




  • It’s actually kinda easy. Neural networks are just weirder than usual logic gate circuits. You can program them just the same and insert explicit controlled logic and deterministic behavior. To somebody who don’t know the details of LLM training, they wouldn’t be able to tell much of a difference. It will be packaged as a bundle of node weights and work with the same interfaces and all.

    The reason that doesn’t work well if you try to insert strict logic into a traditional LLM despite the node properties being well known is because of how intricately interwoven and mutually dependent all the different parts of the network is (that’s why it’s a LARGE language model). You can’t just arbitrarily edit anything or insert more nodes or replace logic, you don’t know what you might break. It’s easier to place inserted logic outside of the LLM network and train the model to interact with it (“tool use”).




  • Trump lost the popular vote in 2016 and 2020 and still was below 50% in 2024 AND his policies never got support from a majority ever when presented without a name.

    There has never been a majority who has liked anything he had to offer.

    This was a propaganda war from racist wealthy assholes who bought out a ton of the companies controlling the media landscape. They exploited bullshit election rules and lied and bribed and extorted to suppress resistance, all just so they could be assholes in public without being called in it.