I think the problem is time. To replicate the OpenAI RLHF architecture, they need their own high-quality dataset, which takes time to create. Without details about the hyperparameters, RL architecture, and omitted steps, they need to test a lot of things, which takes time and money. It requires more resources than it took SD to replicate DALL-E 2, which took months and was an easier task.
Check out Constitutional AI from Anthropic. They automated "RLHF" by simply writing a few rules.
Thanks, just skimmed the paper, I think that "they automated RLHF" statement is maybe too strong here, there is still manual process but it seems like they optimized away a lot of manual labeling work.
There is Open Assistant by LAION (WiP): https://github.com/LAION-AI/Open-Assistant
At least so far none of them are close to what’s been achieved with ChatGPT, and that could in itself be driving some of the hype. ChatGPT was probably more impressive to me on the first impression being familiar with the limitations of existing AI text gen projects.