论文标题
ai aigned研发的经济影响
Economic impacts of AI-augmented R&D
论文作者
论文摘要
自2010年左右出现以来，深度学习已迅速成为人工智能（AI）中最重要的技术，在蛋白质折叠，药物发现，综合芯片设计和天气预测的区域中产生了一系列科学第一的技术。随着越来越多的科学家和工程师采用深度学习，重要的是要考虑到广泛部署将对科学进步以及最终的经济增长产生什么影响。我们通过在两项计算机视觉任务中估算AI的想法生产功能来评估这种影响，这两种计算机视觉任务被认为是深度学习的关键测试床，并表明AI Ideas生产比传统的R＆D更重要。由于提高研发的资本强度会加速使科学家和工程师提高生产力的投资，因此我们的工作表明，AI-EAGMENT的研发有可能加快技术变革和经济增长。
Since its emergence around 2010, deep learning has rapidly become the most important technique in Artificial Intelligence (AI), producing an array of scientific firsts in areas as diverse as protein folding, drug discovery, integrated chip design, and weather prediction. As more scientists and engineers adopt deep learning, it is important to consider what effect widespread deployment would have on scientific progress and, ultimately, economic growth. We assess this impact by estimating the idea production function for AI in two computer vision tasks that are considered key test-beds for deep learning and show that AI idea production is notably more capital-intensive than traditional R&D. Because increasing the capital-intensity of R&D accelerates the investments that make scientists and engineers more productive, our work suggests that AI-augmented R&D has the potential to speed up technological change and economic growth.
