AI Science & Discovery

USC Researchers Enable AI to Fix Its Own Knowledge Gaps

A new feedback loop helped GPT-5 master the Idris language, raising its success rate from 39% to 96%.

By Kronos News Desk··1 min read
A holographic display in a research lab showing lines of programming code being analyzed and automatically updated by an artificial intelligence system.

A holographic display in a research lab showing lines of programming code being analyzed and automatically updated by an artificial intelligence system.

Photo: Kronos News

Researchers at the USC Viterbi School of Engineering developed a method for AI to bridge its own knowledge gaps [1]. The system uses a structured feedback loop to correct errors in real time [1]. This allows models to learn concepts that were not part of their original training [1]. The team tested this approach using GPT-5 and an obscure programming language called Idris [1]. While the model was initially unfamiliar with the language, the feedback loop allowed it to refine its understanding [1]. This process occurred without manual human intervention during the task [1]. The AI's success rate jumped from 39% to 96% during the study [1]. Experts believe this breakthrough could change how future large language models are trained and updated [1].

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Risk level set to high because the story relies on a single primary source domain (USC News), failing the requirement for three independent domains.

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Kronos News Desk covers ai science & discovery and editorial analysis for Kronos News.