Using more training data and computational power is meant to make AIs more reliable, but tests suggest large language models actually get less reliable as they grow
Large language models seem to get less reliable at answering simple questions when they get bigger and learn from human feedback.
The researchers tested the AIs by posing five types of task: arithmetic problems, solving anagrams, geographical questions, scientific challenges and pulling out information from disorganised lists.
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