Avi Brach-Neufeld argues that a mandatory gap between AI model training and internal deployment could stifle innovation and hinder safety research. The author suggests that such a delay might prevent researchers from quickly identifying and addressing potential risks or emergent capabilities. Instead, Brach-Neufeld proposes that continuous internal testing and iteration are crucial for robust AI safety development. AI
IMPACT Mandatory training-to-deployment gaps could slow down AI safety research and innovation by delaying the identification of emergent capabilities and risks.
RANK_REASON Opinion piece by a named credible voice discussing AI safety implications.
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