Model Consistency Challenges
Daniel discusses the complexities of self consistency in AI models like GPT-4, highlighting how responses can vary not only due to settings like temperature but also over time as the models undergo updates. Kate adds that from a research perspective, controlling for specific versions can help mitigate inconsistencies, yet user experiences are still subject to unpredictable changes. The conversation delves into the implications of these variations for both developers and users.In this clip
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The Gradient
Kate Park: Data Engines for Vision and Language
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