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Engineerable AI Project

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The Engineerable AI Project focuses on developing 'Engineerable AI' technology for AI systems that respond to detailed needs, particularly in dependability-critical domains such as medical and autonomous driving. The project addresses two key technical challenges in machine learning, especially deep learning: firstly, AI systems' strong dependence on large datasets, leading to weaknesses in low-data situations, which are often crucial for safety. Secondly, the difficulty in controlling system behavior; updates through data changes often result in unpredictable overall behavior, making continuous improvement challenging as fixing one part can break another. To overcome these, the project pursues two main directions: embedding human knowledge into AI instead of solely relying on data, and developing techniques to investigate AI behavior and its quality to modify it into a desirable form. These 'Engineerable AI' technologies are being demonstrated through proof-of-concept initiatives in medical and autonomous driving applications, where system quality is paramount. The project is supported by the JST MIRAI Program.

Platform

Task

Features

• proof-of-concept in autonomous driving

• proof-of-concept in medical applications

• ai behavior investigation and modification

• embedding human knowledge into ai

• improving ai system behavior control

• addressing data dependency in ai

• ai system development for critical domains

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