Who benefits from OSS LLMs?
As use cases become clearer for how to use LLMs, companies look to save costs. Startups like OpenPipe, a company from the last YC batch, provide model distillation as a service. Record all your GPT-4 or Claude 2 interactions and teach them to a smaller model. Not only can you save a lot of money with this, but also potentially even gain higher quality than before. Simple tasks requiring GPT-3.5 can now be delegated to a smaller model, such as Mistral 7b.
How did we get here? Since the Llama release in March, we experienced the Cambrian explosion of open-source LLM models. Hundreds of fine-tuned options of Llama 1, but since then also, Llama 2 have been released, fighting for the first place in the LLM leaderboard. I believe that Mark Zuckerberg did this very intentionally. He knew that Meta wouldn’t have a model on the GPT-4 level yet, which they’d be able to monetize, but at least he’d be able to “eat the bottom” of OpenAI’s revenue by kickstarting this revolution. In other words, this can be seen as asymmetric warfare. Instead of directly attacking someone, I give the power to the people, so that the delta of the OpenAI offering compared to what’s out there shrinks. The game is on, OpenAI needs to deliver to stay in the spot of number one.
So who benefits from this? Everyone besides the few big AI labs.
Enterprises win, as they can now safely deploy legit GPT 3.5 alternatives in their own datacenter, without having to transmit PII
Startups win, as OSS models create a variety of opportunities around inference, training and fine-tuning
Everyone wins, as these models are able to run locally
Everyone wins, because we’re now enabling anyone to do AI research at home on their laptop by finetuning these models
Just OpenAI, well… They might get into trouble.