Prompt engineering and using an expensive general model in order to prove your market, and then putting in the resources to develop a smaller(cheaper) specialized model seems like a good idea?
Are people down to have a bunch of specialized models? The expectation set by OpenAI and everyone else has set is that you will have one model that can do everything for you. It’s like how we’ve seen basically all gadgets meld into the smart phone. People don’t have Garmin’s and beepers and clock radios anymore (or dedicated phones!). It’s all on the screen that fits in your pocket. Any would-be gadget is now just an…
But cloud services run in... the cloud. It's as big as you need it to be. My cloud service can have as many backing services as I want. I can switch them whenever I want. Consumers don't care.
"One model that can do everything for you" is a nice story for the hyper scalers because only companies of their size can pull that off. But I don't think the smartphone analogy holds. The convenience in that world is for the the developers of user-facing apps. Maybe some will want to use an everything model. But plenty will try something specialized. I expect the winner to be determined by which performs better. Developers aren't constrained by size or number of pockets.