this post was submitted on 02 Aug 2023
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the models are also getting larger (and require even more insane amounts of resources to train) far faster than they are getting better.
I disagree, with models such as llama it has become clear that there are interesting advantages on increasing (even more) the ratio of parameters/data. I don't think next iterations of models from big-corp will 10x the param count until nvidia has really pushed hardware, models are getting better over time. ChatGPT's deterioration is mostly coming from openAI's ensuring safety and is not a fair assessment of progress on LLMs in general, the leaderboard of open source models has been steadily improving over time: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard
But bigger models have new "emergent" capabilities. I heard that from a certain size they start to know what they know and hallucinate less.
Wow you heard that crazy bro
One of the papers about it https://arxiv.org/pdf/2206.07682.pdf