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this post was submitted on 20 Jul 2023
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It's almost certainly because OpenAI is throwing less computing power at it in order to decrease the cost.
And there are more and more offline GPT AIs available for free. Now everyone with an above average computer can have their own chatGPT.
I mean an "average" computer would require a pretty beefy set of hardware. I think most of the average local llama's would run fairly decently on a MacBook without issue nowadays (that m3 is going to be a pretty awesome beast). But the quality is pretty reduced even compared to something like 3.5 which most people thought wasn't all that great.
But really, I'm excited about researchers have access to more computer for smaller amounts (see this https://www.chatgptguide.ai/2023/07/20/worlds-largest-supercomputer-for-ai-training-is-out/) currently we have 1T models that are good, but we could pretty soon have 100T models from the open source community. Let's see whether we can scale the hardware needs with the parameter growth so we don't need A100s to run a decent model.
It's still pretty rough to selfhost an LLM. You can get one that's kind of okay on an average computer, but to get a really competitive one running locally at a good speed, you need a huge amount of RAM that is still beyond most average users (VRAM for GPU based projects).
I've been trying to get Vicuna going and the RAM usage is rough, 60gb is suggested, and I've got 64 and I think I need a lot more honestly.