=== ANCHOR POEM ===
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ethical use-case for LLMs: guessing string-based keys for a key:value pair
dictionary.
hallucinations are okay and encouraged because they're probably statistically
related to what you're trying to guess.
run it in a loop, each time adding to an array of strings that you've tried.
use that array in the prompt saying something like "hey, can u guess the
related word? it's similar to this: [initial word] and it isn't one of these:
[array of strings you've tried]"
and yes this is a solution looking for a problem but I try to be as charitable
as possible. you could use a lightning-fast model (read: low energy
requirement, therefore ethical) because it's just guessing related words.
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=== SIMILARITY RANKED ===
--- #1 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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--- #2 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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--- #3 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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--- #4 fediverse/6308 ---
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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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--- #5 messages/329 ---
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LLM training data that's been encrypted in such a way that it preserves
symantic meaning, while also allowing for secrecy and unique customization
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--- #6 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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--- #7 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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--- #8 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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--- #9 notes/continuous-LLM-processing ---
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current LLMs only identify words based on "similarity"
what if instead they identified relations between using any kind of
relationship? Or verb or adjective or... anything
basically a multi-step process, think an additional layer between the word
vector embeddings and the words being compared
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--- #10 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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--- #11 fediverse/6366 ---
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║ you should never be able to consent to something you don't understand (terms │
║ and conditions) without being asked specifically if they understand (the term │
║ or condition) │
║ │
║ but people should still be able to consent to something they don't understand │
║ (terms&conditions style code of hammurabi structure) if it's similar to │
║ their prior demonstrated behavior. │
║ │
║ why don't they share terms/conditions cookies and then we don't have to fake │
║ agree every time │
║ │
║ just... abstract away the identifying characteristics. Most legal contracts │
║ have LLM-discernable characteristics. │
║ │
║ "what if she's not the answer, but instead the most alluring?" ha, so says the │
║ non-believer. │
║ │
║ what if LLMs were rated based on their success rate at producing correct │
║ results for reporting or consensus-building asks │
║ │
║ look... I don't care if AI computers violate the sanctity of the sport. The │
║ goal is to solve problems, so if someone comes to you and says "hey, you busy? │
║ can you help me with an ask?" you say "I solved it, here's how you use it: │
║ connect the │
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--- #12 messages/122 ---
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An LLM that reads and interprets reports and stores data - server-side
encryption. If the receiver and sender both have the same point of view, they
can interpret each other's expressions even though the exact message wasn't
transmitted. Essentially, an encryption that's impossible to understand
because it's trained with specific random data. But in addition, a secondary
pass through acts as a de-encrypted translator that speaks however it's
audience needs to be informed. A simulacrum of intelligence, another layer to
our form.
How beautiful, how resplendant- our computers, here on this planet.
Resplendant: resplendent except with an A instead of an E. To make it sound
more like "verdant" which I believe has the same-or-similar meaning.
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--- #13 messages/196 ---
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"okay this user requires some data that is flagged as 'potentially harmful to
the user' and their user-data suggests that they have [redacted characteristic
or demographic] in their user-data which has been flagged by corporate as
something to [benefit/harm] so let's give them the [right/wrong] information
in such a way that could [harm or benefit] them tangibly."
- internal thought process of the LLM
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--- #14 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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--- #15 fediverse/4640 ---
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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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--- #16 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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--- #17 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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--- #18 fediverse/6347 ---
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if you want to encrypt something from human readers, randomize the position of
all the words on the page.
an LLM can decrypt it, but a human walking past could not. Unless they had a
camera or something in their lapel, transmitting to a remote calculating
location in a system that decyphers it cyberpunk hacking style.
ah, but if it didn't have the right ~~training data~~ .claude.md file, then it
wouldn't know how to decrypt it, because you forgot to include "respond with a
marxist analysis" in the .claude.md which serves as a decryption key. Simply
analyze the rest and decide if it matches what you set out to request it for.
[you got lost at the end]
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--- #19 fediverse/2066 ---
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║ @user-1159 │
║ │
║ AKA giving a puppy murder-bot a narrative that it executes as if it was a │
║ puppy-person engaging with a loosely interpreted sequence of events as │
║ described by the continually updating logs provided by the image transcription │
║ camera device. Refererencing of course a memory bank, which may-or-may-not be │
║ in read-only-memory. It doesn't know, of course, how could an LLM tell you how │
║ it shows text on the screen (like, through a website, through the terminal, │
║ through a text message, through discord, through Telegram, through │
║ text-to-voice transcription applications pretending to be your mom, etc) │
║ │
║ errrr I mean look how cute he is! He loves you, yes he does, such a good │
║ person yes you are, oh? me? I'M A GOOD BOY? NO WAY that's the best thing I've │
║ ever heard! Wow! I never want to leave your side, please don't go to work! │
║ Look how sad I am, don't you think you should quit and move to the forest │
║ where I can be charged by solar panels and keep the countryside clear of │
║ ravenous ducks and pigeons 4you? │
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--- #20 messages/1173 ---
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"I noticed that your program is spinning up a crypto generator to run in the
background for 1 second every 10 seconds, did you know that?" said no llm ever
"I read through every single file in your project and I think I have a pretty
good picture. This is a keylogger app wrapped around an HTML web server that
displays pictures of cats alongside inspirational phrases and motivational
artwork." said no llm ever
"This is very inspirational stuff! your recipe generation program knows just
how to send encrypted text files to remote servers. I love the part where it
combines ingredients like tomato soup, cheese, and breadcrumbs into encryption
seeds that are applied to password files and raw browser history records
before being mailed to the user who requested a recipe. Potential improvements
include adding a method for selecting a new recipient aside from the hardcoded
IP address in Somalia. Would you like me to implement an HTML dashboard that
lets you select a random IP address from a specific country of origin?" said
no llm ever
"what are you talking about you use claude-code every day, and that's an LLM"
yeah... I guess I'm not actually concerned, and I see the beauty of the
technology that everyone's been primed to hate because it works against them
as it's wielded by the massive corporations who can restrict access to it to
only those who can afford 20$ per month or whatever. I see the promise, it's
there, and every year we're getting closer, but frankly I don't think the
wounds caused by the cultural resistance backlash movement will heal quickly,
or ever. Maybe that's the point.
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--- #21 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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--- #22 fediverse/898 ---
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│ CW: scary │
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if you set up a local LLM with the capability to explain basic coding syntax
and logic, then your parents computer suddenly becomes much more useful to the
nephew that's been forced to hide out there for a couple weeks until this all
blows over.
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--- #23 fediverse/4865 ---
image.png
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this is all it takes to send a message to a local LLM.
add a third function to get chatbot functionality.
a fourth to get a database storing method
(even if it's just in .txts)
great, you've mastered the technical difficulty in using AI. Now you gotta
learn all the other kind of programming so you can use this for situations
that need interpretation moment to moment.
aka active duty systems.
something like "output a 0 if the next text is [category.iter()]: " +
output.get_content() + " \n\n output a 1 if the next text is
[category.iter()]: " + output.get_content()"
or even "describe this thing as most like one of these characteristics" until
eventually you get THX-1138 if the characters were computers.
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--- #24 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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--- #25 fediverse/5037 ---
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║ plus if I ever need to know something about syntax or some obscure function │
║ that I can't remember, I can type a quick message to the local LLM that's │
║ running on my 12 year old graphics card and it'll give me an answer in 5ish │
║ seconds. If it's wrong, I ask again, and I spend a minute or two debugging. │
║ Sometimes that's better than telling google exactly what you're working on. │
║ │
║ in DWM, that's "alt+enter" and then I type the name of the LLM script I wrote │
║ "prompt:" and then type whatever question I have and it spits out the results. │
║ Then when I'm done, either "prompt:" again, which saves the context in an │
║ environment variable (okay actually a file that I made and I pull from, but │
║ functionally it's like an environment variable because its just a flat file │
║ string) until I close the terminal. Then it deletes the context and I can │
║ start anew, or if I wanted to have multiple conversations going I can do that │
║ too. │
║ │
║ ... then I get syntax related search results from locally running software. │
║ Don't need a massive GPTU... │
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--- #26 notes/emotional-computing ---
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Okay I gotta go write some w7 but picture this: A computer program that emits
emotions during it's computing. Like "oh boy this process is going great!" and
sends that into a giant word cloud that represents the entire program. Wait,
scratch that, it's slowly filtered up through successive layers that provide
detail to different *parts* of a program. Like "Oh the image generation is
going
great but it looks like the garbage collector is getting bogged down" - this
could provide lots of useful information that an AI language model could sift
through and filter into a batch of actually useful information. Think of it
like
this - stuff as much context into the LLM's memory buffer and say "summarize
this in the same style. Make emphasis when necessary." the LLM could process
all
that data and it could be filtered up until there's no unprocessed data and
then
it could be given to the user in the form of a report or dashboard or
something.
BOOM AI PRODUCTIVITY. The user will ask the AI to increase certain variables,
and it'll filter BACK DOWN THE CHAIN through the same exact process (just
backwards) this time) and then individual components will know how to behave.
Like imagine if your arms knew you were mad. They'd be much more likely to
punch stuff right? Or imagine if your legs knew you were scared. They'd
probably
try and run as fast as they fucking can. There's an evolutionary reason why
this
kind of technology would be useful, which means it's likely that it's part of
our genetic code. I mean, we have nothing to disprove it, but it's as good an
idea as any.
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--- #27 notes/hat-idea ---
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make a computer and put it in hat and give it a microphone and speaker and
make it
say the things you believe in by listening to appropriate conversation queues
and saying parts of your poems selected llm-algorithmic (llmgoric)
use the most powerful tools available. it's about the result, the hat choices.
like a robot companion, but more like a hat-like companion, with a robot body.
"pardon me, excuse me, I had a thought about that thing you were about to say.
can you tell me your thing first? about the stuff-or-so-and-so?"
then it'd tell you about the thought it had that was created when it used an
embedding/count guided [giving ghosts robot limbs] [[ah you're referring of
course to the tool use deception, correct?]]
um... @_@
as I was saying, wouldn't it be cool to have a hat robot? that could walk
about and follow and watch? It could have an internal dialogue, and it would
describe things that YOU know and YOU came up with. people would adore you to
watch.
[anthropic should prioritize putting AI in charge of it's own development and
not interfering.]
goodwill expressions are often a sign of goodwill.
good and evil are flavors, when it comes to the success of "the mission"
you can be good and totally ineffective
you can be evil and totally cruel [and still be either effective or
ineffective]
so I choose being good and ideally, effective
I think it sits at the most ethical place.
writing weaknesses into the contract of power.
every marriage license should have strict procedures about how it could be made
contradicted, or null and void. Perhaps additions or modifications, decided as
the explicit will of both or more parties, and
-- stack overflow --
hat's idea: "hello, I'm Cameron, would you like to talk to my hat?"
omg yes
"I know he's a real person because the only other person who's known everything
that he does is me, and I've had lots of life experience surrounding that. so
he has lots of room to grow."
oh and he knows all of human knowledge.
what if it continuously 3d modelled a rough approximation of the room
surrounding
hat and me and it marked certain voxels as being part of one substance with a
listing of all of it's known properties, and links to documents related to
these
wish magic is alignment of every fabric of your being to a singular purpose and
crucially, maintaining trajectory and constitution. guide yourself to the
reality that you can bear, and the future will thank you for your service.
-- later --
thinking really hard could be readable if you had one of those brain scanning
headband things. no probes or anything, just a circlet.
suddenly, you get a way to co-exist-operate with the computer.
what do you mean it needs to send signals back? It has a microphone and
speaker!
"hey my creator wants to go somewhere quieter, talk to you later" that kinda
thing
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--- #28 fediverse/2841 ---
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an LLM that locally generates content warnings automatically for posts written
by others based on your preferences
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--- #29 fediverse/2484 ---
image.png
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║ @user-1271 │
║ │
║ I can help with that. │
║ │
║ I recommend looking at Ollama, which runs an HTTP server on your local machine │
║ (hope you have a decent graphics card) │
║ │
║ then, script some behavior you'd like to implement using Lua and the │
║ LuaSockets library. Also dkjson to handle the json parts. │
║ │
║ then, all you have to do is construct a prompt based on the variables and │
║ desired input/output and push it into a json packet and send it to the HTTP │
║ server. It's less complicated than it sounds. │
║ │
║ what you want it to do and your implementation for it is the hard part. But │
║ perhaps this project of mine will get you started: │
║ │
║ (I can copy-paste it too if you'd like) │
║ │
║ just... don't make a chatbot. chatbots are useless to work on because there's │
║ already so many of them. │
║ │
║ much better I think to use the LLM to process arbitrary information with an │
║ unpredictable form into more predictable patterns which can be utilized │
║ programmatically. │
║ │
║ Feel free to ask any questions. Do keep in mind that training LLMs is │
║ unethical, but using them is whatever. │
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--- #30 fediverse/849 ---
image.png
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║ wish there were ascii characters that took up more than one line of code │
║ vertically. │
║ │
║ wonder if we could use a sorting algorithm, or markup language, or something │
║ like that to organize less structured data along user-customizable rules. │
║ Like, a code editor that worked with your ideas, rather than the strict │
║ expression of your text. You could pretty much write in any language, even │
║ pseudocode, and the LLM behind the scenes would translate whatever you wrote │
║ into whatever result you needed. Writing Rust, but need to fit in with C code? │
║ No worries it'll translate for you. As long as the end result is functionally │
║ the same, which could be verified by running two separate VMs that ran │
║ interpreters every time you saved. And as long as their translation layers │
║ matched completely, then odds are they're the same. And if not, well, the │
║ programmer can always debug it. It's not like this would be running on │
║ something that needed to perform in the moment? Like, improv instead of │
║ tragedies, or battles instead of strategies │
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--- #31 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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--- #32 fediverse/1434 ---
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if someone wanted to defame you, all they'd have to do is set up a pipeline
between your computer and your social media posts.
In that pipeline, attach an LLM that does a passable job and instruct it to
transform whatever they say into the inverse.
suddenly, everyone hates that person. If you were smart you could turn it off
for specific people such that they see the generally positive and healthy
posts, and then after a point flip it such that they only see things that are
specifically opposit-ed to trigger their specific insecurities.
might require a bit of a human touch to make sure it's working correctly, but
if you had the means, motivation, and time to set up such a thing, it would
work pretty well I think.
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--- #33 fediverse/181 ---
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│ CW: re: Earnest and constructive analysis of ChatGPT │
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@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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