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Joined 3 years ago
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Cake day: July 4th, 2023

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  • Something that some coworkers have started doing that is even more rude in my opinion, as a new social etiquette, is AI summarizing my own writing in response to me, or just outright copypasting my question to gpt and then pasting it back to me

    Not even “I asked chatgpt and it said”, they just dump it in the chat @ me

    Sometimes I’ll write up a 2~3 paragraph thought on something.

    And then I’ll get a ping 15min later and go take a look at what someone responded with annnd… it starts with “Here’s a quick summary of what (pixxelkick) said! <AI slop that misquotes me and just gets it wrong>”

    I find this horribly rude tbh, because:

    1. If I wanted to be AI summarized, I would do that myself damnit
    2. You just clogged up the chat with garbage
    3. like 70% of the time it misquotes me or gets my points wrong, which muddies the convo
    4. It’s just kind of… dismissive? Like instead of just fucking read what I wrote (and I consider myself pretty good at conveying a point), they pump it through the automatic enshittifier without my permission/consent, and dump it straight into the chat as if this is now the talking point instead of my own post 1 comment up

    I have had to very gently respond each time a person does this at work and state that I am perfectly able to AI summarize myself well on my own, and while I appreciate their attempt its… just coming across as wasting everyones time.




  • You… understand the Cortana on windows is literally named as a reference to Cortana from Halo right? Because Microsoft owns Halo…? They named it from her… So its the same “Cortana” so to say.

    Its a fundamental counterpoint to the OPs post, because it wasn’t made feminine as some kind of mental gymnastics misogyny thing, its just a nerdy reference to an already existing character Microsoft had the rights to, its not that deep.




  • The name was chosen because it was a play on the SRI technology and because it is a girl’s name.

    The name was actually chosen because it was originally going to be the name of one of the founder’s soon to be daughter, but then his child ended up being a son so he gave the name to the machine instead as his “second child” effectively…

    So it had literally nothing to do with whatever point the poster was trying to make, and everything to do with a sense of paternal love if literally anything, lol… People will find literally fucking anything to mald over, even making shit up to try and make it sound right.


  • Yeah but also is a heavy counterpoint to the point in the post, because Cortana was already a “higher level of autonomy” AI in her first depiction (Halo games), from the start, and Microsoft named it after the character because Microsoft bought Halo and was just doing a nod to the character… So thats literally an outright counterpoint to whatever mental gymnastics the poster of the post was doing…



  • Literally only one AI assistant Im aware of was given a feminine persona out the gate and thats Alexa which is Amazon’s.

    Every single other one has been purposefully kept gender neutral.

    They intentionally gave Siri a gender neutral name ages ago cuz you can pick what its voice sounds like

    Same for gemini, copilot, gpt…

    Only 1 out of many agents had a female name, and it wasnt “tech bros” that named it.

    And only one tool has been given a male name, Claude



  • pixxelkick@lemmy.worldtoFuck AI@lemmy.world"lessons learned"
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    23 days ago

    Once a model is trained, they become functionally opaque. Weights shift… but WHY. What does that vector MEAN. True, but I guess my point is a lot of people ascribe, as you pointed out, way more “spirit” or “humanity” to what an LLM is, whereas in reality its actually a pretty simple lil box. Numbers go in, numbers come out, and all it does is guess what the next number is gonna be. Numbers go BRRRRRRRRR

    I think where I fundamentally disagree is that “they do what they say they do” by any definition beyond the simple tautology that everything is what it is.

    I guess I was referring to when theres a lot of tools out there that are built to do stuff other than what it outta do.

    Like stick a flashlight onto a wrench if you will. Now its not just a wrench, now its a flashlight too.

    But an LLM is… pretty much just what it is, though some people now are trying pretty hard to make it be more than that (and not by adding layers overtop, Im talking about training LLMs to be more than LLMs, which I think is a huge waste of time)


  • pixxelkick@lemmy.worldtoFuck AI@lemmy.world"lessons learned"
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    23 days ago

    I apologize for any confusion.

    I meant LLMs are what they say they are in a non literal sense.

    Akin to abscribing the same to any other tool.

    “I like wrenches cause they are what they say they are, nothing extra to them” in that sort of way.

    In the sense the tool is very transparent in function. No weird bells or whistles, its a simple machine that you can see what it does merely by looking at it.



  • When using the word “they”, in English it refers the the last primary subject you referred to, so you should be able to infer what “they” referred to in my sentences. I’ll let you figure it out.

    “I love wrenches, they are very handy tools”, in this sentence, the last subject before the word “they” was “wrenches”, so you should be able to infer that “they” referred to “wrenches” in that sentence.


  • pixxelkick@lemmy.worldtoFuck AI@lemmy.world"lessons learned"
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    24 days ago

    Everything I said was very much correct.

    LLMs are fairly primitive tools, they arent super complex and they do exactly what they say they do.

    The hard part is wrapping that up in an API that is actually readable for a human to interact with, because the lower level abstract data of what an LLM takes in and spits out arent useful for us.

    And then even harder is wrapping THAT API in another one that makes the input/output USEFUL for a human to interact with

    You have layers upon layers of abstraction overtop of the tool to make it go from just a bunch of raw float values a human wouldnt understand, to becoming a tool that does a thing

    That “wrapper” is what one calls the “platform”.

    And making a platform that doesnt fuck it up is actually very very hard, and very very easy to get wrong. Even a small tweak to it can substantially shift how it works

    Think of it a lot like an engine in a car. The LLM is the engine, which on its own is not actually super useful. You have to actually connect that engine to something to make it do anything useful.

    And even just doing that isnt very useful if you cant control it, so we take the engine and wrap it up in a bunch of layers of stuff that allow a human to now control it and direct it.

    But, turns out, when you put a V6 engine inside a car, even a tiny little bit of getting the engineering wrong can cause all sorts of problems with the engine and make it fail to start, or explode, or fall out of the car, or stall out, or break, or leak… and unlike car engines, these engines are very very new and most engineers are still only just now starting to break ground on learning how to control them well and steer them and stop them from tearing themselves out of the car, lol.

    So, to bring this back to the original post:

    Most LLMs (engines) are actually pretty good nowadays, but the problem was Clawdbot (a specific brand of car manufacturer) super fucked up the way they designed their car so the car itself had a very very stupid engineering mistake. IE in this case, the brakes didnt work well enough and the car drove off a cliff.

    That has nothing to do with how good the engine is or is not, the engine was just doing its job. The problem was with some other part of the car entirely, the part of the car Clawdbot made that wraps around the engine.


  • To be clear: this isnt an AI problem, the LLM is doing exactly what its being told to

    This is an Openclaw problem with the platform itself doing very very stupid things with the LLM lol

    We are hitting the point now where, tbh, LLMs are on their own in a glass box feeling pretty solid performance wise, still prone to hallucinating but the addition of the Model Context Protocol for tooling makes them way less prone to hallucinating, cuz they have the tooling now to sanity check themselves automatically, and/or check first and then tell you what they found.

    IE a MCP to search wikipedia and report back with “I found this wiki article on your topic” or whatever.

    The new problem now is platforms that “wrap” LLMs having a “garbage in, garbage out” problem, where they inject their “bespoke” stuff into the llm context to “help” but it actually makes the LLM act stupider.

    Random example: Github Copilot agents get a “tokens used” thing quietly/secretly injected to them periodically, looks like every ~25k tokens or so

    I dunno what the wording is they used, but it makes the LLM start hallucinating a concept of a “deadline” or “time constraint” and start trying to take shortcuts and justifying it with stuff like “given time constraints I wont do this job right”

    Its kinda weird how such random stuff that seems innocuous and tries to help can actually make the LLM worse instead of better.