Thanks for the points!
I agree monetization in the LLM Ops space is hard and complex.
Agreed fully on customizing solutions or consulting.
Yep self hosting solutions like Redhat, or DBs like MongoDB or Gitlab's dashboard style approach could work - the issue is now as you mentioned we offer training and finetuning.
We do plan to offer inference as well, plus the data gathering process, and the final prompt engineering side - but we thought why not have a shot?
It's possible best to make a training and inference platform - maybe some sort of personal ChatGPT training for the public - everyone can train their own personal ChatGPT not via ChatGPT's in context learning or RAG, but coupled with actual fast 30x finetuning, a personal bot can truly be possible.
You have companies that are spending good money on fine-tuning and will start spending money on fine-tuning. It seems like it would almost be easier to just go directly to these companies by looking at their blog posts--they're telling you that they're doing it in some way or another. I know Plaid and friends are doing it.
It's costing them x. you can shave y off. you can get improvements to market faster and cheaper.
Interesting points! I shall try this with my bro!!
I was thinking along the lines of say the cost of A100s or H100s * electricity cost and engineering costs then how much we save, and some discounting factor.
It allows for fast iteration and shorter go-to-market, which can generate virtually infinite value, as opposed to saving electricity, which is a limited game.
You may want to look sideways to companies such as hedge funds. They have DNN teams and experiment with LLMs, you may find interesting optimisation opportunities with such teams. Charge according to opportunity that you open up, not electricity saved!
Yep self hosting solutions like Redhat, or DBs like MongoDB or Gitlab's dashboard style approach could work - the issue is now as you mentioned we offer training and finetuning.
We do plan to offer inference as well, plus the data gathering process, and the final prompt engineering side - but we thought why not have a shot?
It's possible best to make a training and inference platform - maybe some sort of personal ChatGPT training for the public - everyone can train their own personal ChatGPT not via ChatGPT's in context learning or RAG, but coupled with actual fast 30x finetuning, a personal bot can truly be possible.
Thaks for the suggestions!