Thank you for your interest, but the downvotes and basic attitude of the sub make me not feel welcome here. My lack of financial security also compels me not to freely share technical details of what could be a breakthrough worth a lot of money (if only in energy and time savings) to a subreddit that is downvoting me for agreeing that they should be more inviting. Once I check the next few things off the to do list maybe I'll post a demo.

This is a hobby to me, I don't have research funding or anything that is compelling me to potentially advance the field just for the sake of it, especially when the community is bitter to newcomers. I recognize ai is most likely going to be a cornerstone of the economy, and if my architecture scales like I think it will, it will be worth something to someone, and you'll see a demo in a few weeks or months once I take it as far as I want to. I think most people understand not wanting to have one's ideas be borrowed for free when one is struggling.

Thanks for being one of apparently 5 people who's curiosity is at least as strong as their skepticism.

Good luck in your endeavors.

There should be an active "beginning and easy questions megathread" instead of the sub just being uninviting. The about says to go to "r/learn machine learning" which was just a dead end for me.

For example, I am here because of chatgpt. So quit reading now if you don't like newbs. But I have over 20 years of programming esperience, I just never tried machine learning before. -I have watched videos about it and read, that's it. But I'm interested in it -now.

In a month of hobby time, I now have a working prototype of a novel llm architecture that can learn and write at blistering speed; and accurately rewrite Wikipedia articles, create new poetry, etc with as little as 7mb of model size while staying coherent. I am allowing in to grow to 8.5 billion parameters sometimes and can still run it on a potato device, -quickly. I am working on ways to simultaneously increase accuracy and long term memory and abstraction capability while lowering the amount of resources it needs. And it's working.

And this sub is too snobby to allow beginner questions, so instead of my project getting any sort of help, momentum or publicity or open sourcing, or guidance, -or I don't know, me becoming part of the community here, I'm just keeping it in dark corner to die or get the ADHD hyperfocus once a month; even if yeah it might be worthless, -but it could potentially open up one other person's input and be a game changer, because none of the approaches I'm taking come up in papers or Google searches, and they are efficient and they work.

But no noob questions. So I run to Google and other places to learn, and I don't post here. this community won't grow and get cross specialization with the attitude it has, it's very off putting.

I recently tried out bloom, https://bigscience.huggingface.co/blog/bloom which is supposedly the biggest open source LLM. Is this really the state of the art for language models that are publcally available?

They would have to offer free service paid by ads and/or selling the resulting training data to the big corps

I feel like dwarf fortress taught me a lot about this with the simple system of "unmet need: be extravagant, unmet need: spend time with family". It's a great approach that gets to the meat of it instantly, and is really healthy introspection that can actually be utilized.