Will GenAI scale without enough power to accelerate multi-trillion parameter LLM training, causing economic fallout and impacting GDP growth? The rapid expansion of Generative AI (GenAI) and Large Language Models (LLMs), like GPT, Gemini and LLaMA, has drastically increased the need for computational power, especially as models scale from billions to trillions of parameters. Training these multi-trillion parameter models demands specialized hardware, notably NVIDIA’s H100 and upcoming GB200GPUs, which are designed to handle the immense Teraflop computation processing requirements of such massive model parameters count and datasets. These GPUs outperform traditional models in both speed and efficiency, but at the costof significantly higher power consumption.
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