Psst ... why don't you spend 30 minutes of quality time with chatGPT and get to the bottom of this? Get those personalised explanations and enjoy its unlimited patience.
I have felt the same in the past, related to a completely different topic. I know how it feels, it's like people are not saying things what they are, just using weird words.
"weights" - synapses in the AI brain
"tokens" - word fragments
"model" - of course, the model is the AI brain
"context" - the model can only handle a piece of text, can't put whole books in, so this limited window is the context
"GPT" - predicts the next word, trained on everything; if you feed its last predicted word back in, it can write long texts
"LoRA" - a lightweight plug-in model for tweaking the big model
"loss" - a score telling how bad is the output
"training" - change the model until it fits the data
"quantisation" - making a low precision version of the model because it still works, but now is much faster and needs less compute
"embedding" - just a vector, it stands for the meaning of a word token or a piece of image; these embeddings are learned
I have felt the same in the past, related to a completely different topic. I know how it feels, it's like people are not saying things what they are, just using weird words.
"weights" - synapses in the AI brain
"tokens" - word fragments
"model" - of course, the model is the AI brain
"context" - the model can only handle a piece of text, can't put whole books in, so this limited window is the context
"GPT" - predicts the next word, trained on everything; if you feed its last predicted word back in, it can write long texts
"LoRA" - a lightweight plug-in model for tweaking the big model
"loss" - a score telling how bad is the output
"training" - change the model until it fits the data
"quantisation" - making a low precision version of the model because it still works, but now is much faster and needs less compute
"embedding" - just a vector, it stands for the meaning of a word token or a piece of image; these embeddings are learned