OpenAI themselves must not have a "reasonable definition of L", then. Their own papers and press releases refer to GPT-2 (from 2019) as a "large language model".
Yes, and 1.5 billion parameters meets no reasonable current definition of large. It would be considered a tiny language model. OpenAI themselves refer to their small/fast models as small models all over their documentation.
Sure we do, since Fei-Fei Li and team created that annotated dataset, which allowed to train first LLMs. So LLMs are here for more than a decade already.
OpenAI themselves must not have a "reasonable definition of L", then. Their own papers and press releases refer to GPT-2 (from 2019) as a "large language model".
https://openai.com/index/better-language-models/
Yes, and 1.5 billion parameters meets no reasonable current definition of large. It would be considered a tiny language model. OpenAI themselves refer to their small/fast models as small models all over their documentation.
Sure we do, since Fei-Fei Li and team created that annotated dataset, which allowed to train first LLMs. So LLMs are here for more than a decade already.
You are confused by what the L and L mean in LLM, or which data set she created, or both, or in general.