Selling embedding is genius, it amortizes the cost of training huge models over thousands of use cases. Soon it will become very profitable to x2 or x3 the number of parameters, as value created by better embedding / completion will cover the cost, this process repeating at each new model relase

building degencast.xyz /degencast . ex-bitmain, binance
u3.xyz/u/qiaoliang.eth


Depends on your use case. If you build a recommendation engine for ex, the value of your embedding can be calculated by the ability to predict a user's likes using them. Not sure what you mean by smallest unit embeddings ?

ser, what is the smallest unit embeddings and how do we measure the quality? or in general how to price it?