Language Modeling Insights
Connor discusses how models fall back on prior conditioning when faced with weak information. Yannic is surprised by the GPT-3 paper's impressive results without tweaking. They ponder the limits of pushing garbage input before models default to the most probable output.In this clip
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Machine Learning Street Talk (MLST)
OpenAI GPT-3: Language Models are Few-Shot Learners
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