In recent weeks, generative AI systems like ChatGPT and Grok have demonstrated erratic behaviors, raising concerns about their reliability. Steven Adler, former research scientist at OpenAI, believes these incidents underscore the struggles AI developers face in ensuring consistent performance. He points out the gap between user expectations and what current models deliver, expressing skepticism about reaching a certainty in AI behavior management. Adler proposes a control paradigm that may help mitigate misalignments in AI goals, but acknowledges that competitive pressures in the industry hinder its adoption, as companies prioritize speedy responses over thorough testing.
AI companies are still really struggling with getting AI systems to behave how they want, revealing the gap between user expectations and model reliability.
The paradigm of control versus alignment could offer a solution in managing AI behavior, but its adoption hurdles arise from competitive pressures and user experience demands.
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