As the demand for advanced generative AI models continues to rise, the hardware that powers these models has become a focal point of innovation and exploration. A diverse range of hardware options, including CPUs, GPUs, FPGAs, and ASICs, are vying for prominence in driving the computational capabilities of generative AI. In this article, we embark on a comprehensive comparison of these hardware architectures, elucidating their strengths, weaknesses, and the specific use cases where they excel. Understanding the nuances of each hardware type is pivotal for businesses, researchers, and AI practitioners aiming to optimize the performance of their generative models and navigate the evolving landscape of AI hardware technology.
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