We have. This is acceptable for some clients, but not for others. Both groups, however, prefer maintaining complete control over their data, given the chance.
Edit: plus, my personal view is that local LLMs are the future. They've already caught up to GPT-3.5 (based on my testing); and they continue to evolve rapidly. Makes sense to focus our limited resources on riding that wave.
OpenAI won't go away, but neither will they remain the first choice (or only choice!) for most use-cases.
There's some . . entrepreneurs . . who have been promising NIST/ITAR-compliant LLM frameworks on Azure, but when you ask around, they have not done all the legwork (AG/AGS). They're working off Azure Public, with "waivers" that they won't show anyone. Also, the history of their leadership is . . questionable. It all feels just a little hinky. Until that's cleared up, I advise anyone fooling with LLMs to do it on-prem, at least for the moment. One thing I'm worried about: doing LLMs with something like GovCloud is going to be absolutely bananas in terms of price-per-compute.
Edit: plus, my personal view is that local LLMs are the future. They've already caught up to GPT-3.5 (based on my testing); and they continue to evolve rapidly. Makes sense to focus our limited resources on riding that wave.
OpenAI won't go away, but neither will they remain the first choice (or only choice!) for most use-cases.