It uses a different engine, so this is as related to ChatGPT as a Toyota Corolla is related to a BMW car. This is an efficient and open-source chatbot, which is very good news, but the authors just wrote a clickbait title and they know it.
In formal analogies, : is pronounced "is to" and :: is pronounced "as".
The purpose here is to use the relationship from a known, to describe the relationship between a partial known.
ChatGPT is to GPT3 as ChatLLaMa is to LLaMa. It uses the relationship between ChatGPT and GPT3 to extrapolate a relationship between an unknown and LLaMa.
Corolla:Toyota::3-Series:BMW. If you had heard of a Corolla, Toyota, and BMW, but not a 3-Series, you now roughly know that a 3-Series is BMWs equivalent to a Corolla.
I think I prefer the other commenter's point, referring to ChatGPT as a known learning paradigm for chatbots. But thanks for the little crash course on analogies ;)
The analogy is somewhat accurate, but also moot, since within the ML community "ChatGPT" can be used either as the product or the method (more specifically called RLHF) somewhat interchangeably. It's more like Google/Googling, where the largest/most popular provider becomes the defacto way to refer to a method.
As someone who develops DL models, the title seems quite apt.
basch|3 years ago
The purpose here is to use the relationship from a known, to describe the relationship between a partial known.
ChatGPT is to GPT3 as ChatLLaMa is to LLaMa. It uses the relationship between ChatGPT and GPT3 to extrapolate a relationship between an unknown and LLaMa.
see Analogies.pdf https://resources.finalsite.net/images/v1584287027/brockton/...
Corolla:Toyota::3-Series:BMW. If you had heard of a Corolla, Toyota, and BMW, but not a 3-Series, you now roughly know that a 3-Series is BMWs equivalent to a Corolla.
levesque|3 years ago
f_devd|3 years ago
The analogy is somewhat accurate, but also moot, since within the ML community "ChatGPT" can be used either as the product or the method (more specifically called RLHF) somewhat interchangeably. It's more like Google/Googling, where the largest/most popular provider becomes the defacto way to refer to a method. As someone who develops DL models, the title seems quite apt.