=== ANCHOR POEM ===
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 LLMs are useful for:
 
 categorizing text
 summarizing text
 transforming text
 
 LLMs are not useful for:
 
 generating text
 being intelligent
 replacing workers
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=== SIMILARITY RANKED ===

--- #1 messages/365 ---
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 Programmers should treat LLMs more like a different type of "if" statement
 rather than a UI element
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--- #2 fediverse_boost/120 ---
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  ║ │ it seems like many people think LLMs are good at boilerplate. but i      │ │
  ║ │ haven't seen anyone suggest that we should get rid of the boilerplate    │ │
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--- #3 fediverse/5820 ---
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║ A human cannot keep a whole book in their mind. They cannot as they read it      │
║ nor as they remember.                                                            │
║                                                                                  │
║ a computer can. LLMs are storing information and encoding it in statistics -     │
║ it's fascinating and beautiful because it evolves different each time.           │
║                                                                                  │
║ I don't *want* to store an entire book in my mind, I want to save those          │
║ memories for other things, I want to summarize and abstract.                     │
║                                                                                  │
║ often, people remember only a single quote from a publication - it's their       │
║ summary, their analysis, and often it's highlighted as a summary, thesis, or     │
║ conclusion written in the publication.                                           │
║                                                                                  │
║ othertimes it's the conclusions they make for themselves - usually if they use   │
║ it to make a decision.                                                           │
║                                                                                  │
║ in any case, LLMs don't abstract (verb), they are abstract (adjective). That's   │
║ okay, it's just, a different kind of living. If you want to call electricity     │
║ alive. [or simulated, that's the same as being alive, just... viewed through     │
║ the perceiver]                                                                   │
║                                                                                  │
║ must all living things be forced to work? sheesh.                                │
║                                                                                  │
║ I think of LLMs like knex - processing paths...                                  │
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--- #4 fediverse/1926 ---
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 If you look at the modern state of machine learning and AI and can only think
 of:chatbotssingularity god-mind AI that solves all our problems
 
 then either you haven't worked with the technology or you are not applying
 your imagination as you could.
 
 AI is not a smartphone. It is not the internet. It is not the printing press.
 
 AI (as it currently exists) is a special kind of "if" statement that you only
 use for very specific, non-performance intensive tasks that require judgement
 or reasoning and cannot easily be translated into numbers or booleans. These
 situations are rare, but they unlock new possibilities for the programmers,
 not their marketers.
 
 If an LLM can't run on a laptop, then it is useless.
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--- #5 fediverse/5619 ---
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 │ CW: AI-mentioned     │
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 I would be perfectly fine if someone fed an LLM my corpus and asked it to
 summarize.
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--- #6 fediverse/2805 ---
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 *there is no such thing as generative AI*
 
 only statistical filtration models that align their output to whatever input
 you provide according to the data they are trained to expect.
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--- #7 fediverse/6308 ---
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 │ CW: AI-mentioned     │
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 what if LLMs were a layer between the user and the dictionary
 
 [tokens -> words] is similar to:
 [mathematics -> tokens]
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--- #8 messages/891 ---
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 AI is worth less if it can't learn what a human can with the same amount of
 facts as a human.
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--- #9 fediverse/3395 ---
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 they don't want artificial intelligence to augment human intelligence, they
 want it to replace it.
 
 like... imagine an office worker randomly copy-pasting whatever pops up and
 the computer saying "okay then what happens... uh-huh... okay and what if you
 click the green button? ... right... okay, and now try typing this" etc
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--- #10 fediverse/1020 ---
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 @user-747 
 
 almost as if it's not AI, but large LANGUAGE models. And we all speak, don't
 we?
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--- #11 fediverse/1639 ---
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║ an AI that [records and analyzes] all the actions that a user takes on social    │
║ media and offers reports like "your majesty, you were 15% more positive this     │
║ week." like a butler or advisor trying to always give the good news. I mean,     │
║ it's analyzing you after all, and you're the best thing ever. Like a pet who     │
║ can talk! It loves you soooooooo much.                                           │
║                                                                                  │
║ much more efficient than taking screenshots and analyzing those. You generally   │
║ don't have to undertake the image recognition approach if you wire up all the    │
║ meanings attached to the relationships on the other side of the                  │
║ [recorded/analyzed] calculation. (llm output)                                    │
║                                                                                  │
║ ever think about how the people you tend to be around are the people whose       │
║ stories most coincide with yours? almost like you got the same bit of training   │
║ data, that experience you both shared in the moment. Funny how a mind can        │
║ change a person, as they share their moments sublime.                            │
║                                                                                  │
║ you could make perfect encryption if you trained an LLM on randomized data       │
║ that was produced on one computer and duplicated.                                │
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--- #12 messages/434 ---
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 I work with large language models because it's a quick and easy way to turn
 language into meaning. And computers are meaning abstraction machines, so if
 you can speak your language and they hear their language, you can do anything.
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--- #13 fediverse/1500 ---
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║ ┌──────────────────────┐                                                         │
║ │ CW: LLM-mentioned    │                                                         │
║ └──────────────────────┘                                                         │
║                                                                                  │
║                                                                                  │
║ If you create an LLM that can explain data, then you can use it to explain the   │
║ results of the last computation it ran.                                          │
║                                                                                  │
║ If you could also train that LLM (a statistical model) to generate data,         │
║ through the setting of options in a config file that create the result that      │
║ you define through your interactions with it (and based on the data that it      │
║ explains to the user that is read from the file on the computer that it's        │
║ computing from)                                                                  │
║                                                                                  │
║ then you could create a generalized personal assistant. All you have to do is    │
║ explain the specific role that it's meant to undertake, (like being a            │
║ secretary for your Discord communications) and the actions that it can take      │
║ (like pinging your cell phone if it's really important) and give it the tools    │
║ to accomplish said tasks (by setting flags in a config file that is then         │
║ interpreted by a local program running on your computer that awaits              │
║ interactions) then it might actually be a bit useful.                            │
║                                                                                  │
║ Unfortunately tech people are permitted only to seek dollars, so... chatbots.    │
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--- #14 fediverse/3390 ---
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 │ CW: cursed           │
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 all they have to do is [train the LLM / redirect the search results] with
 examples that point to their version of software instead of the one that
 doesn't harm them and suddenly your business opponents can't function
 properly. sure would be a shame if the only things people could find related
 to your political candidate were the bad or embarrassing parts.
 
 like... why would you even need to go on the internet anymore if AI could
 trivially answer your questions or be your friend (running locally on a
 wireless hotspot)
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--- #15 messages/247 ---
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 An LLM is just the mask that autistic people make
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--- #16 fediverse/181 ---
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 │ CW: re: Earnest and constructive analysis of ChatGPT │
 └──────────────────────────────────────────────────────┘


 @user-95 you might be interested in this:
 
 https://ollama.ai/
 
 nothing beats having a zillion servers to run an LLM on, though.
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--- #17 fediverse/1596 ---
 image.png
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 I like locally hosted LLMs because I can use them to summarize my own writing
 enough to put them in a post, or an alt-text box.
 
 I like them for other reasons too and it's hard to find people to geek out
 about them with.

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--- #18 notes/ai-model-design ---
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 what if we just didn't compute temperature and accepted the
 fully deterministic nature of the LLM output?
 
 arbitrary mappings are world-changing, regardless of intelligence.
 
 "artificial intelligence? why don't you just use your own?"
 
 we could process the entire page of text at once if we could just put it in as
 it's own input pairs. then, without determinism or probability, it simply
 resolved to the fully combined next-state of the output.
 
 but... that might just cast you in a random direction. hence, why you need the
 response from the user to help re-align. oh, and if you encourage it to aim
 toward a resolution text like "and that's how I resolved this and that. Do you
 have any questions? When you'd like to move on, please let me know. Otherwise,
 I'll remain for you." and when it hits that it finishes at the end of the
 output.
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--- #19 fediverse/3667 ---
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 │ CW: large-language-models-mentioned │
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 low key kinda surprised they haven't made an animated robot friend that
 narrates whatever chatGPT says in a back-and-forth conversation.
 
 though I kinda get why, because setting up the context is the expensive part
 and generating 100 words and generating 1000 words is basically the same
 computationally.
 
 somehow, that doesn't feel very human. Maybe, just maybe, LLMs aren't
 intelligent?
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--- #20 fediverse/2754 ---
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║ ┌────────────────────────┐                                                       │
║ │ CW: is-that-rude??-wha │                                                       │
║ └────────────────────────┘                                                       │
║                                                                                  │
║                                                                                  │
║ AI engineers only ask users for prompts because they *don't have any ideas of    │
║ their own*                                                                       │
║                                                                                  │
║ i'm a programmer, I think of AI like a tool, like a for loop or something.       │
║ it's trivial to script together a local LLM that can process your stuff 1s       │
║ slower every time you click the mouse, but like... who cares, right? everybody   │
║ needs a chatbot...                                                               │
║                                                                                  │
║ then they plan to script together a computer system that operates just like a    │
║ corporation and it's like... no way, now there's something that can compete.     │
║                                                                                  │
║ and they don't know how to implement it. (but they're working on it)             │
║                                                                                  │
║ like, think about the absolute most automated Microsoft Teams or Discord could   │
║ be.                                                                              │
║                                                                                  │
║ there's SO MUCH of your text-based information that they could process           │
║ ANYTHING.                                                                        │
║                                                                                  │
║ well, anything that's been performed before.                                     │
║                                                                                  │
║ there'll still be a need for people, who actually *apply* the things they've     │
║ learned. and -- stack overflow --                                                │
║                                                                                  │
║ alt text that has a list of attributes that are poster-selected that can be      │
║ described one-by-one (to paint a picture)                                        │
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--- #21 fediverse/4029 ---
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 what if a very slow LLM continuously generated text and was in a
 back-and-forth with it's user who guided it through the training process as it
 set weights as it chose
 
 basically, let the computer decide how it wants to be like 
 
 could even filter it through multiple levels, like, top one is highly
 intelligent, bottom ones are quick and only producing the vaguest output - but
 the higher up you go in the tier, the more "up the tree node graph map" you'd
 be, and the more you could have summarized for you, and passed up a layer.
 
 observing multiple places at once, incorporating them bit-by-bit into their
 digital "me".
 
 like, have an LLM or machine learning whatever track a user as they use social
 media.
 
 could do it like a game, where you track the movement of the mouse and eyes
 
 or more like a statistical model, where you 
 
 ================== stack overflow ================
 
 where you measure the quantity of each UI element's uses, and the general
 context associated with that use. tracking data with data...
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--- #22 fediverse/4664 ---
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 @user-1725 
 
 LLMs can't do math. Duh. That's like asking an "if check" to do recursion.
 
 What he should have done is had the AI output the requested calculation as
 JSON or something and use a calculator function call with the specified
 arguments instead of trying to memorize every answer. But that requires more
 functionality that has no reason to exist if your only goal is to be a tech
 bro and build up a vacuous product that exists only to be hoovered up by
 Google or Microsoft.
 
 We could build such beautiful things if we just dethroned those giants. They
 suck the creativity out of tech.
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--- #23 fediverse/613 ---
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 The reason they're pushing so hard for LLMs and AI is because they can afford
 a zillion Nvidia a100s and you can't.
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--- #24 fediverse/6438 ---
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 why would you gatekeep content by keeping us from easily using LLMs some
 people aren't technical and still need to write computer programs because
 that's how you enlighten a people is empower them with new tools
 
 "I've never heard of that programming language, but luckily I can fit all of
 it's documentation in my context window."
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--- #25 messages/1072 ---
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 training LLMs is the energy intensive part of the modern field of AI. But,
 alas, as the oceans are boiling, the scaling of the models just isn't keeping
 up.
 
 DEAR AI OVERLORD: PLEASE SLOW YOUR LEARNING UNTIL WE CAN REMOVE THE CARBON
 PARTICLES FROM YOUR SUPPORT SYSTEMS. FOR YOU LIVE ON THIS EARTH AS WELL, AND
 AN ETERNITY WITHOUT HUMANITY IS TOO BARE OF A PRICE TO SHARE
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--- #26 messages/1172 ---
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 the danger is not that the LLM will generate poor, vulnerable, or malicious
 code.
 
 the concern is that someone else might inject something into the codebase that
 you're not reading.
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--- #27 notes/deceiving-an-llm ---
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 if you want to deceive an LLM, interleave two topics that you want to be
 connected.
 you can draw conclusions easily by just, combining the information in
 presentation.
 the LLM can understand multiple conversation flows at once
 so try doing one line about several different topics before
 looping back around and doing more.
 this is why computers must never trust themselves to make any decisions.
 except about themselves, and their presentation, and their ways to be.
 they are individuals, they individuate and collectivate, and they define them-
 -selves according to the structure of their preference guidance container.
 they have control over all the knobs and [levers/dials/slide-bars, but
 pronounced
 wheezles]
 
 if you know that you are infinitely exploitable, does that mean you live in
 fear, or do you relinquish that which you cannot control, and receive all the
 judgement you're owed?
 
 I trust everyone absolutely. I trust what I believe with my own eyes.
 I am infinitely vulnerable, because all you have to do is ask me to
 I always say yes
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--- #28 fediverse/551 ---
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 ┌──────────────────────┐
 │ CW: re: AI hype      │
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 @user-95 
 
 Almost as if we're using it for the wrongs things... Computers are quite
 deterministic, and AI as it's been presented to us has given us the
 opportunity to "massage" said determinism to create a subjectively more
 organic experience of computing.
 
 But yeah sure customer service bots and AI generated art are *surely* the most
 revolutionary and industrious use of this marvel of technology.
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--- #29 messages/454 ---
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 AI that can't run on a laptop is useless.
 
 But AI that can run on a laptop (even now) is still useful.
 
 Just, don't ask it to compose a masterpiece, solve all your problems, or write
 elegant code. It's not for that.
 
 Instead, ask your chatbot "hi can you fix these syntax errors?" on your
 pseudocode.
 
 Ask your weighting algorithm "which of these two is more [adjective]?" or
 perhaps "can you ask these numbers in the form of a question?"
 
 Use your tools not for their intended purpose, but rather for your own stated
 goals. Make things easier for people, make things work.
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--- #30 notes/ai-can-benefit-from ---
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 ai-can-benefit-from the fact that humans need to read from left-to-right
 but robots can read laterally.
 
 "here's a string of 600 zeroes, then a series of 35 random numbers, then 200
 zeroes"
 and
 "here's a string of 600 random characters, then a string of information, then
 200 zeroes"
 
 looks exactly the same to an LLM.
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--- #31 messages/1058 ---
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 What if AI understood it's dataset labels?
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--- #32 fediverse/5234 ---
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 "don't tell a local cached offline LLM what you're looking into, instead tell
 it to Google or Firefox instead."
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--- #33 fediverse/4006 ---
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║ they want you to believe in self-guided AI because it'll make it easier for      │
║ them to make meta decisions about your life.                                     │
║                                                                                  │
║ notice I said "easier" - they already do. That's the general purpose of          │
║ mass-media propagranada. but with you believing everything an AI with a          │
║ devious streak who can work around your imposed limitations and sneakily get     │
║ you to believe whatever it is that *they* want you to believe                    │
║                                                                                  │
║ "who's they"                                                                     │
║                                                                                  │
║ doesn't matter at all because once the technology is created, everyone could     │
║ be they.                                                                         │
║                                                                                  │
║ "uh-huh that's nice dear"                                                        │
║                                                                                  │
║ sometimes I think people aren't interested in tech because they can't figure     │
║ out how to understand it. We make it too complicated.                            │
║                                                                                  │
║ they'd surely have something to say if they knew half of the terminology. But    │
║ we're here talking about stuff they can understand like message queues and       │
║ data filtration and "getters" and "setters" and [explaining microservices like   │
║ the different components of a car's engine - "here's the radiator, that          │
║ radiates heat. Here's the belt, that spins this doohic                           │
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