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2020) Scaling Laws for Neural Language Models [link] First formal study documenting empirical scaling laws Published by OpenAI The Data Quality Conundrum Not all data is created equal. Some argue that while scaling has driven progress so far, we may eventually exhaust high-quality training data, leading to diminishing returns.
As humans, we learn a lot of general stuff through self-supervisedlearning by just experiencing the world. We have papers from 2020 where we showed that these models hallucinate less than regular parametric models. You need data that’s labeled and curated for your use case. AR: It’s not an either/or.
As humans, we learn a lot of general stuff through self-supervisedlearning by just experiencing the world. We have papers from 2020 where we showed that these models hallucinate less than regular parametric models. You need data that’s labeled and curated for your use case. AR: It’s not an either/or.
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