[treprinum]

That's why the LLaMA 2 release is so significant. You can run the full 70B in 8-bit on two prosumer A6000 Ampere (cost around $10k together) which is within the reach of most companies and some devs. This could further accelerate all research to make it both efficient and available even to regular folks.

[amkkma]

But it's still not comparable to GPT 4, nor will it likely be for some time at least. And by the time we have GPT 4 class open source models, I'd imagine there'd be significant advancements in closed source models, such as inference time symbolic reasoning using MCTS, something google is working on for gemini...or just bigger/better architectures, data etc

[treprinum]

Yeah, I don't really see a solution. Even Stanford can't keep up with the latest AI research. Still, having LLaMA 2 is better than not having it.