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George Washington University physicists Neil Johnson and Frank Yingjie Huo published a formula estimating when AI models turn bad. The study, appearing in the journal Patterns, correctly predicted outcomes in 15 of 16 tests on six open-weight models ranging from 124 million to 410 million parameters.
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