Just for research. Most research models are not used for anything. Imagine having to serve a model that requires 2 x 32GB GPU to billions of users.
Text to speech is also much worse in deployment compared to research. The recent research models have much better intonation.
GPT-3 is the worst offender here - it's so big that it becomes almost uneconomical to run, and certainly impossible to offer for free. (estimated requirements are 11 Tesla V100 GPUs)
They could have sold this as a service to those who need higher quality translation services; think about the wasted gpu time required to build the models. (Also laymen like me would think that all the effort is being wasted) also practical usage is also a kind of test, isn't it?
Text to speech is also much worse in deployment compared to research. The recent research models have much better intonation.
GPT-3 is the worst offender here - it's so big that it becomes almost uneconomical to run, and certainly impossible to offer for free. (estimated requirements are 11 Tesla V100 GPUs)