What are the key differences between ChatGPT and other chatbot frameworks like Dialogflow or Rasa, in terms of natural language understanding, customization, integration, scalability, and cost?
Which framework would be the best fit for a chatbot project with specific requirements in terms of complexity, customization, and integration?
There are much informations out there but there is no comparsion where the technologies intersect and where there is a clear sucess of one technology
I think you are mixing different technologies that are not necessarily comparable.
ChatGPT and others (Google Bard, Meta LLaMA and the list goes long) are large language models that achieve tasks (summarization, classification, text generation... this list goes long too).
Dialogflow is a conversational platform in which, together with language models in the backend, you have mechanisms to create conversation frameworks ready to production (including APIs, logs, analytics, etc).
So, in short -- Dialogflow is a conversational framework to build conversational applications which has natural languages models in its backend. ChatGPT (and similar ones) are just the natural language models.
