Current AI training methods often rely on large data sets and simulations, which limits the system’s ability to make decisions in the face of limited information. GUIDE’s new approach allows a human to observe the AI’s actions and provide it with timely, detailed suggestions, improving its ability to adapt and learn.
In its first demonstration, GUIDE helped AI learn to play hide and seek. The human trainer provided feedback using a gradient scale, which improved the AI’s performance by 30% compared to traditional training methods.
Additionally, using an AI model built from instructor data, researchers showed that AI can continue learning even after the human stops giving feedback. This approach opens up new possibilities for creating more intuitive and adaptable AI systems.
Source: Ferra
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