CIRCLE WITH A DOT

@shlee dunno but there's a CBC piece about it

https://www.cbc.ca/news/canada/edmonton/inglewood-league-lawsuit-missing-funds-9.7136933 if you were wondering

if you're on mstdn.ca you might want to move lol

wow that story about the mstdn.ca admin embezzling money from a sports league is fascinating

tired: t4t

wired: bun4bun

@davidgerard @dysfun these are the types of jobs I used to take on

@davidgerard man if i were younger i would take them up on this, but now days i don't think i have the spoons to deal with this level of shitshow

@cadey boooooooooooo

who hasn't teleported to a waffle house

@ptrc but where is the bunny

@pixx @mirth yes, i agree that the main usecase for automated text generation is antisocial stuff like spam. what i am pursuing is more "language as I/O" than text generation. think Siri.

@pixx @mirth i think small LLMs do not really have an ethical problem: i trained a 1.3B parameter LLM off of my own personal data in my apartment by simply being patient enough to wait. no copyright violations, no boiling oceans, just patience and a professional workstation GPU with 96GB RAM.

the ethical problem is with the Big AI companies who feel that the only path forward is to make bigger and bigger and bigger monolithic prediction models rather than properly engineer the damn thing.

that same ethical problem is driving the hoarding, because companies are buying the hardware to prevent their competitors from having it IMO.

@jannem @pinskia @mirth that said, i think that OpenAI and other hardware/resource hoarders need to be called out on the fact that they don't need all of this to ship product

there really is no need to destroy the climate or make professional GPUs cost as much as a recent vintage used car

@jannem @pinskia @mirth yes, this is what i eventually want to build. a set of libre building blocks for building ethical, libre and personal agentic systems that are self-contained.

the shit Big AI is doing is not interesting to me, but SLMs and other specialized neural models legitimately provide a useful set of tools to have in the toolbox.

today, however, I just want to prove the ideas out by shitposting in IRC

@pinskia @mirth yep they broke the illusion.

IMO the real reason OpenAI reserved all of this RAM and shit is to prevent competitors from buying it

@mirth back in the earlier AI wars, these were called "expert systems"

my idea is basically SLMs for I/O with other small models and tools governed by a user-generated expert system

@mirth i mean, i don't think that necessarily holds *if* you have the ability to build whatever you need with legos.

in many cases simply translating natural language to a specification for an expert system is enough

@mirth interesting. what I've built is a modular pipeline which takes language input, converts it into structured data, enriches that structured data with other relevant information, processes the final query into a plan (which is also structured data) and then uses that plan to formulate a response

@mirth the question is why compete with them at all? it has same energy as the unix wars. large, proprietary models that lock people in. I would rather see a world of small, modular libre models that anyone with a weekend and a GPU can reproduce.

@dngrs I wanted something cooler than a Markov bot, and was already researching SLM (small language model, e.g. language strictly as I/O) technology for a Siri-like thing anyway.

@mirth sure, but the "thinking" ones do some consensus stuff to ensure it doesn't go off course