![LLMs are getting much cheaper — business impact? [D]](https://jfbmhhfxbbrxcmwilqxt.supabase.co/storage/v1/object/public/resource-images/MachineLearning_AI_for_business_20250328_183445_processed_image.jpg)
LLMs are getting much cheaper — business impact? [D]
Saw this out of Stanford. Apologies if it’s been shared here already.
We introduce Alpaca 7B, a model fine-tuned from the LLaMA 7B model on 52K instruction-following demonstrations. On our preliminary evaluation of single-turn instruction following, Alpaca behaves qualitatively similarly to OpenAI’s text-davinci-003, while being surprisingly small and easy/cheap to reproduce (<600$).
Basically, starting w an open source Meta 7B LLaMa model, they recruited GPT-3.5 to use for self-instruct training (as opposed to RLHF) and were able to produce a model that behaved similar to GPT-3.5. Amazingly, the process only took few weeks and $600 in compute cost.
Any thoughts on how such low cost to train/deploy LLMs could affect companies like AMD, Nvidia and Intel etc? This seems like new idiom of AI tech and trying to wrap my head around CPU/GPU demand implications given the apparent orders of magnitude training cost reduction.
Link: https://crfm.stanford.edu/2023/03/13/alpaca.html
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