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Research demonstrates how microelectronics can reduce energy consumption in AI applications, suggesting a path for innovation.
Global digital approaches are evolving rapidly in our society. This development appears very useful in a wide range of applications, but it also leads to a considerable increase in the amount of data transferred and processed, more particularly due to Artificial Intelligence (AI) tools. Given that all operations in this field are primarily based on electronic equipment, this consequence is an exponential growth in electrical energy consumption. Within the next decade, this could lead to a deleterious global lock-in. Thus, the microelectronics sector has become a global priority and societal behaviors and technologies must evolve. To achieve this, new skills and know-how are needed to stimulate innovation, corresponding to new jobs in microelectronics. Recent research results predict that the energy consumption of all hardware can be reduced by a factor of 10. By combining software simplification, edge computing, and library minimization for AI, we can hope to meet the challenges.
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Olivier Bonnaud (2026) studied this question.
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