Meta AI

“Lama two, maybe I would say it's like Lama one. We had a flagship model, which was seven TB. It's also because the project was taking some routes to reproducing a chinchilla, which was a seven TB.”

“So what we did is that we generated all the data on the prompts with LAMA-II, and we applied, like, basically the last round of LAMA-II we had to kick off and start LAMA-III post-training. So Lama-free post-training doesn't have any, like, human-written answer…”

“As, like, Mark announced, we have more and more GPUs, so the next generation will be bigger.”

“I expect some incremental and significant progress on pre-training and post-training, but I'm really hopeful that we can gain some order of magnitude of scaling by interconnecting well models into agents as a more complex system that can do planning, that can …”

“Having bigger models enables to collect better data, for instance, at RLHF stage, because that's the model we use for the annotation. And so we distillate straight forward, like those annotations from this better model to the other models. So I can guarantee y…”

“Meta AI, for example, which I don't think gets necessarily remarked upon a ton in the like AI enthusiast, AI developer community, but like it's a silent monster, right? Because of Meta's distribution and reach.”