This paper investigates the role of the materiality of computation in two domains: blockchain technologies and artificial intelligence (AI). Although historically designed as parallel computing accelerators for image rendering and videogames, graphics processing units (GPUs) have been instrumental in the explosion of both cryptoasset mining and machine learning models. The political economy associated with video games and Bitcoin and Ethereum mining provided a staggering growth in performance and energy efficiency and this, in turn, fostered a change in the epistemological understanding of AI: from rules-based or symbolic AI towards the matrix multiplications underpinning connectionism, machine learning and neural nets. Combining a material political economy of markets with a material epistemology of science, the article shows that there is no clear-cut division between software and hardware, between instructions and tools, and between frameworks of thought and the material and economic conditions of possibility of thought itself. As the microchip shortage and the growing geopolitical relevance of the hardware and semiconductor supply chain come to the fore, the paper invites social scientists to engage more closely with the materialities and hardware architectures of 'virtual' algorithms and software.

中文翻译：

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接近金属：走向计算认识论的物质政治经济学。


本文研究了计算重要性在区块链技术和人工智能（AI）两个领域中的作用。尽管图形处理单元 (GPU) 历史上被设计为图像渲染和视频游戏的并行计算加速器，但它在加密资产挖掘和机器学习模型的爆炸式增长中发挥了重要作用。与视频游戏、比特币和以太坊挖矿相关的政治经济在性能和能源效率方面提供了惊人的增长，这反过来又促进了对人工智能认识论理解的变化：从基于规则或符号的人工智能到支撑联结主义的矩阵乘法、机器学习和神经网络。本文将市场的物质政治经济学与科学的物质认识论相结合，表明软件与硬件、指令与工具、思想框架与思想可能性的物质和经济条件之间并没有明确的界限。本身。随着微芯片短缺以及硬件和半导体供应链日益增长的地缘政治相关性日益凸显，本文邀请社会科学家更密切地研究“虚拟”算法和软件的物质性和硬件架构。