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Joined 2 years ago
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Cake day: July 31st, 2023

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  • Here’s the thing… the people in power right now are trying to make new generations of Nazi fucks out of young people. Continue this insanity.

    Gutting education and every fucking system we’ve tried to put in place to help people and show that things can be better. They’re being taught that it isn’t the fault of the rich man who won’t let you take a bathroom break! He’s just trying to scrape by while being robbed by the tax man! If only they’d give him a break then he could afford to pay you better. Really, it’s the fault of your fellow worker because he’s an immigrant, or your neighbor because he’s disabled, or your kid’s friend because he isn’t not masculine enough, or your wife’s fault for selfishly working instead of staying home and raising your boy right…





  • As tempting as it is and as upset as I am with everyone who voted for Fascism (purposely or due to ignorance), these people need to be compassionately educated rather than jeered at and told “That’s what you get you fucking idiot.”

    This is a moment where they might realize the value of the services that the left believes they deserve as a fellow human being. Maybe they’ll finally figure out that the propaganda they’ve been fed isn’t a reliable source of truth.


  • Clearly the author doesn’t understand how capitalism works. If Apple can pick you up by the neck, turn you upside down, and shake whatever extra money it can from you then it absolutely will do so.

    The problem is that one indie developer doesn’t have any power over Apple… so they can go fuck themselves. The developer is granted the opportunity to grovel at the feet of their betters (richers) and pray that they are allowed to keep enough of their own crop to survive the winter. If they don’t survive… then some other dev will probably jump at the chance to take part in the “free market” and demonstrate their worth.



  • I think the word “learning”, and even “training”, is an approximation from a human perspective. MLs “learn” by adjusting parameters when processing data. At least as far as I know, the base algorithm and hyperparameters for the model are set in stone.

    The base algorithm for “living” things is basically only limited by chemistry/physics and evolution. I doubt anyone could create an algorithm that advanced any time soon. We don’t even understand the brain or physics at the quantum level that well. Hell, we are using ML to create new molecules because we don’t understand it well.


  • I think you’re either being a little dismissive of the potential complexity of the “thinking” capability of LLMs or at least a little generous if not mystical in your imagination of what the purely physical electrical signals in our heads are actually doing to learn how to interpret all these little shapes we see on screens.

    I don’t think I’m doing either of those things. I respect the scale and speed of the models and I am well aware that I’m little more than a machine made of meat.

    Babies start out mimicking. The thing is, they learn.

    Humans learn so much more before they start communicating. They start learning reason, logic, etc as they develop their vocabulary.

    The difference is that, as I understand it, these models are often “trained” on very, very large sets of data. They have built a massive network of the way words are used in communication - likely built from more texts than a human could process in several lifetimes. They come out the gate with an enormous vocabulary and understanding of how to mimic, replicate it’s use. If they had been trained on just as much data, but data unrelated to communication, would you still think it capable of reasoning without the ability to “sound” human? They have the “vocabulary” and references to mimic a deep understanding but because we lack the ability to understand the final algorithm it seems like an enormous leap to presume actual reasoning is taking place.

    Frankly, I see no reason for models like LLMs at this stage. I’m fine putting the breaks on this shit - even if we disagree on the reasons why. ML can and has been employed to achieve far more practical goals. Use it alongside humans for a while until it is verifiably more reliable at some task - recognizing cancer in imaging or generating molecules likely of achieving a desired goal. LLMs are just a lazy shortcut to look impressive and sell investors on the technology.

    Maybe I am failing to see reality - maybe I don’t understand the latest “AI” well enough to give my two cents. That’s fine. I just think it’s being hyped because these companies desperately need VC money to stay afloat.

    It works because humans have an insatiable desire to see agency everywhere they look. Spirits, monsters, ghosts, gods, and now “AI.”


  • Yes, both systems - the human brain and an LLM - assimilate and organize human written languages in order to use it for communication. An LLM is very little else beyond this. It is then given rules (using those written languages) and then designed to create more related words when given input. I just don’t find it convincing that an ML algorithm designed explicitly to mimic human written communication in response to given input “understands” anything. No matter *how convincingly" an algorithm might reproduce a human voice - perfectly matching intonation and inflexion when given text to read - if I knew it was an algorithm designed to do it as convincingly as possible I wouldn’t say it was capable of the feeling it is able to express.

    The only thing in favor of sentience is that the ML algorithms modify themselves and end up being a black box - so complex with no way to represent them that they are impossible for humans to comprehend. Could it somehow have achieved sentience? Technically, yes, because we don’t understand how they work. We are just meat machines, after all.





  • Thanks for being so detailed!

    I use caddy for straightforward https, but every time I try to use it for a service that isn’t just a reverse_proxy entry, I really struggle to find resources I understand… and most of the time the “solutions” I find are outdated and don’t seem to work. The most recent example of this for me would be Baikal.

    Do you have any recommendations for where I might get good examples and learn more about how do troubleshoot and improve my Caddyfile entries?

    Thanks!


  • I replied to the following statement:

    I could look up my dad’s name and all I get are articles about a serial killer who just happened to have the same name

    I countered this dismissal by quoting the article, which explains that it was more than just a coincidental name mix up.

    You response is not really relevant to my response, unless you are assuming I’m arguing for one side or the other. I’m just informing someone who dismissed the article’s headline using an explanation that demonstrated that they didn’t bother to read the article.

    Nothing is wrong with the tech (except it doesn’t seem very useful when you firmly know what it can’t do), but everything is wrong with that tech being called artificial intelligence.

    If the owners of the technology call it artificial intelligence and hype or sell it as a potential replacement for intelligent human decision making then it should be absolutely be judged on those grounds.