AI agents get better by anticipating errors in their own software changes

Some artificial intelligence agents can modify the programs and instructions governing their own work, with the goal of improving performance. These changes, however, can introduce errors, while testing unsuccessful modifications consumes resources. Researchers at the University of Virginia, Microsoft Research and Tsinghua University recently developed forecasting software that helps AI agents anticipate the consequences of proposed edits before testing the modified software.

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