=== ANCHOR POEM ===
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what if the secret to LLM computation is to just not reduce the fractions and
keep it all in english language ram
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=== SIMILARITY RANKED ===
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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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--- #2 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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--- #3 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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--- #4 fediverse/181 ---
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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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--- #5 fediverse/6413 ---
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to understand something, work backward from present understandings back to the
fundamentals of algebra. insert words. wield LLM. build a neuronal structure
many layers wide. let them coprocess bit-by-bit as they are adding new
processors to be "learning" new domain specific memory
context-processing-thingy.
"over here's the memory cells, over here are the conceptual structure"
suddenly, organified. not ideal.
much better, I feel, is for a disambiguous association of processor selves,
each contextualizing a cache in a ram. ['s horn]
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--- #6 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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--- #7 fediverse/5619 ---
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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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--- #8 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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--- #9 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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--- #10 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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--- #11 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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--- #12 messages/247 ---
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An LLM is just the mask that autistic people make
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--- #13 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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--- #14 fediverse/5141 ---
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all you have to do is include the current state of the LLMs registers in the
output so that it can use them as a base next time it starts up.
boom, infinite context width.
like playing a video from the beginning as it's recording
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--- #15 fediverse/2900 ---
image.png
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│ CW: capitalism-mentioned-AI-dataservers-mentioned │
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what if all the AI advancements they're doing are just them building more
hardware infrastructure in datacenters and not actually improving the software
that much
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--- #16 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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--- #17 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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--- #18 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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--- #19 fediverse/384 ---
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@user-283
let us pray
for a day
when we can say
that computing makes sense
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--- #20 messages/140 ---
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Remind me again why we need computers that are so mind numbingly fast that we
can't possibly hope to understand their entire stack?
Oh yeah, so we aren't able to understand their stack. How could I forget.
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--- #21 fediverse/3745 ---
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everyone's all like "why would you spend so much effort writing that software
in a distributed way when it works so well in a centralized manner" and the
answer is because you never know when you're going to need to train an LLM on
like, 400 raspberry pi's or calculate the velocity of an unladen swallow as it
circles a black hole the size of mercury or whatever physicists do in their
spare time
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--- #22 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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--- #23 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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--- #24 messages/940 ---
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*perfect*, we solved computation - just become a computer! easy!
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--- #25 fediverse/5990 ---
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I have this local language model framework but it's not built into anything
more than a single-response question. It's runnable as a bash script or lua
require, which is easy enough. Alas, if only I didn't have to use evil
corporate infrastructure to make evil corporate cursed artifacts
[hey don't blame this on us]
oh I'm not, I'm just saying that it'd be cooler if I could build my own tools.
Alas, I'm...
lasy?
n...no
I'm drawn to the power of it
it's got a different magnitude
it's hard for me to apply myself for things that last longer than a "get
stoned", but I try as if every time afterwards I might die.
well, more distraction time, as I wander through claude code
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--- #26 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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--- #27 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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--- #28 messages/1236 ---
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true AI is when no decision or logical momentum can be explained by "... and
that value was randomly generated." -- (my opinion)
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--- #29 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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--- #30 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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--- #31 fediverse/2720 ---
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ah nuts, they replaced my LLM setup with one that outputs gibberish. I swear
it was working just a moment ago, and I didn't change it's configuration at
all, and it's local only... right? so uh that's weird, surely it's not because
they altered some value somewhere that I have no access to
eh, maybe the newest technologies are overrated. At least, the software ones.
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--- #32 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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--- #33 messages/1208 ---
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Almost all of the recorded information is stored in your computer. But none of
it would be noticed by a god, reading the entire contents of the computer, 0
by 1 by 1 by 0.
Wikipedia and a reasonable LLM networking interface apparatus is really all
you need in order to make any type of workflow you want. And now, everyone
gets one. As soon as we can make them all go... (setup)
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