Thanks for these points! I think I understand the history of what has happened here better now—and the reasons for my misapprehension. Essentially, what I think happened is
a.) LLM/NLP research always (?) used ‘pretraining’ for a long time back at least to 2017 era for a general training of a model not specialised for a certain NLP task (such as NER, syntax parsing, etc)
b.) rest of ML mostly used ‘training’ because they by and by large didn’t do massive unsupervised training on unrelated tasks—i.e. CV just had imagenet or whatever
c.) In 2020-2022 period NLP with transformers went from fairly niche subfield of ML to memetically dominant due to massive success of transformer GPT models
d.) This meant both that their linguistic descriptions of ‘pretraining’ spread much more widely due to uptake of similar methods in other subfields and that I got much more involved in looking at NLP / LLM research than I had in the past where I personally had focused more on CV and RL leading to its sudden appearance in my personal experience (which turned out to be wrong).
Thanks for these points! I think I understand the history of what has happened here better now—and the reasons for my misapprehension. Essentially, what I think happened is
a.) LLM/NLP research always (?) used ‘pretraining’ for a long time back at least to 2017 era for a general training of a model not specialised for a certain NLP task (such as NER, syntax parsing, etc)
b.) rest of ML mostly used ‘training’ because they by and by large didn’t do massive unsupervised training on unrelated tasks—i.e. CV just had imagenet or whatever
c.) In 2020-2022 period NLP with transformers went from fairly niche subfield of ML to memetically dominant due to massive success of transformer GPT models
d.) This meant both that their linguistic descriptions of ‘pretraining’ spread much more widely due to uptake of similar methods in other subfields and that I got much more involved in looking at NLP / LLM research than I had in the past where I personally had focused more on CV and RL leading to its sudden appearance in my personal experience (which turned out to be wrong).