20240612-海通国际-中国互联网：“人工智能+”引爆新质生产力革命.pdf
who have developed a method to decompose neural networks into more interpretable components using dictionary learning. This approach has been successful in extracting millions of high-quality features from large language models, such as ChatGPT and Transformer-based models.
The authors argue that explainable AI is crucial in the industry as black box models can lead to difficulties in debugging errors, identifying biases, and taking responsibility for AI system decisions. They emphasize the need for transparent and interpretable AI systems, especially in the context of the "AI+X" revolution in China's internet industry, which aims to integrate AI with other technologies to drive innovation and growth.
Overall, the article suggests that the integration of AI with other technologies will require the development of more transparent and interpretable AI systems.
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