These advances in AI and machine learning from ChatGPT and other AI models like Google’s Bard, Meta’s LLaMA and other open-source models could fundamentally alter the future of computing and improve our quality of life in countless ways, such as enhancing scientific learning, managing complex systems, and improving the productivity and output of virtually all sectors of the economy. [...] 129 Energy and the Economy September 2023 consumption and improve the cost-effectiveness of AI and machine learning.12 While NVIDIA is currently the market leader with respect to GPUs designed for machine learning and data centers, competitors such as AMD and Intel are developing their own GPUs, as are a host of startups.13 Even Google and Amazon are entering the chip market.14 In addition to more. [...] These practices should be encouraged, and policymakers and regulators should be cognizant of both the evolving nature of the market and the inherent, market-driven incentives that reduce the overall power load of data centers. [...] Yet the increase in the demand for energy must be evaluated within a proper framework, which requires comparing the energy use and outcomes achievable through the computing power of AI to the alternative. [...] Although managing the energy needs of AI models is an managing the energy needs of AI models is an important important issue, high energy costs offer natural incentives to develop technologies issue, high energy costs offer and products that increase efficiency and lower the energy costs required to run AI- natural incentives to develop technologies and products that based technologies.
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