The speaker says the company must build its own stack for supervised fine-tuning and reinforcement-learning workflows, including RLHF.

“So we have to build our own stack for doing a...”

“SFT if we're doing RLHF, doing RL, I mean that becomes IP to some extent so it's one of the reasons we decided not to open source everything was really to keep the IP a little bit closer to us and not opening it but then there are downsides like there is less less an opportunity for the community to contribute it's harder to adopt it's hard to do on-prem kind of like deployments and so on.”