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OpenAI announces plan to transform into a for-profit company
(www.theverge.com)
Ruh roh!
No problem, after they release all the data collected under the excuse of public good and progress.
Booooooooooo!
Anyway: ill just keep using alpaca to run llms locally
is there an easy way to do this that doesn't require me to understand how github works?
I recommend Ollama, its easy to setup and the cli can download and run llms. With some more techsavviness you can get openwebui as a nice ui.
For someone who doesn't understand GitHub, the CLI might be a bit much, FWIW.
It would be nice if there were a GUI, download-and-run single click app with a webui built in.
in that case you're looking for llamafiles. single file, llm included, starts into a web gui. the only limitation is that windows limits the size of executable files to 4GB so on that OS you're limited to smaller models.
Alpaca for linux is easy to use. You just install the flatpak and the llm of your choice. You dont need to know how to use github. (It might have a windows version but im not sure)
I think that in that case, YouTube is your friend. There are a few pretty straight forward videos that can help you out; if you're serious about it you're going have to, eventually, become familiar with it.
Stop depending on these proprietary LLMs. Go to !localllama@sh.itjust.works.
There are open-source LLMs you can run on your own computer if you have a powerful GPU. Models like OLMo and Falcon are made by true non-profits and universities, and they reach GPT-3.5 level of capability.
There are also open-weight models that you can run locally and fine-tune to your liking (although these don’t have open-source training data or code). The best of these (Alibaba’s Qwen, Meta’s llama, Mistral, Deepseek, etc.) match and sometimes exceed GPT 4o capabilities.
The issue with that method, as you've noted, is that it prevents people with less powerful computers from running local LLMs. There are a few models that would be able to run on an underpowered machine, such as TinyLlama; but most users want a model that can do a plethora of tasks efficiently like ChatGPT can, I daresay. For people who have such hardware limitations, I believe the only option is relying on models that can be accessed online.
For that, I would recommend Mistral's Mixtral models (https://chat.mistral.ai/) and the surfeit of models available on Poe AI's platform (https://poe.com/). Particularly, I use Poe for interacting with the surprising diversity of Llama models they have available on the website.
There are open-source LLMs you can run on your own computer if you have a powerful GPU.
What defines powerful? What if you don't have the necessary hardware?
You can check Hugging Face's website for specific requirements. I will warn you that lot of home machines don't fit the minimum requirements for a lot of models available there. There is TinyLlama and it can run on most underpowered machines, but its functionalities are very limited and it would lack a lot as an everyday AI Chatbot. You can check my other comment too for other options.
llama is good and I'm looking forward to trying deepseek 3, but the big issue is that those are the frontier open source models while 4o is no longer openai's best performing model, they just dropped o3 (god they are literally as bad as microsoft at naming) which shows in benchmarks tremendous progress in reasoning
When running llama locally I appreciate the matched capabilities like structured output, but it is objectively significantly worse than openai's models. I would like to support open source models and use them exclusively but dang it's hard to give up the results
I suppose one way to start for me would be dropping cursor and copilot in favor of their open source equivalents, but switching my business to use llama is a hard pill to swallow
And there are also free, online hosted instances of those same LLMs in a (relatively speaking) privacy-protecting format from DuckDuckGo, for anyone who doesn't have a powerful GPU :)
Interesting. So they mix the requests between all DDG users before sending them to “underlying model providers”. The providers like OAI and Anthropic will likely log the requests, but mixing is still a big step forward. My question is what do they do with the open-weight models? Do they also use some external inference provider that may log the requests? Or does DDG control the inference process?
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Oh boy, how surprising.
The bait and switch classic.
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So the development of inorganic intelligence, considered by many as an inflection point in human civilisation is to be handed to business graduates who are historically proven to be capable of any level of atrocity in the name of corporate greed. America, fuck yeah.
~~America~~ Greed, fuck yeah.
Don't fool yourself. The USA lost the exclusivity deal on unchecked corpo greed a long time ago. This is a global issue now.
Always has been.
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Did Elon not block this?
Shocking nobody
Well, apart from the people like me who thought they had always been one because they acted exactly like one.
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"ClosedAI" rebrand when?
🤣
Open Your Wallet AI
NopeAI
That's very open of them
Open to All Income.
I thought they were a for-profit company all this time.
Pretty much non-profit in name only. Some shady hybrid model.
OpenAI sure seems like a case study in how to grift everyone by masquerading as a non profit whilst actually enriching yourself and your shareholders, causing a whole new class of societal problems in the process.
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this post was submitted on 27 Dec 2024
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