from AI researcher Konstantin Pilz suggests that of the 10,000 to 30,000 data centers currently operating worldwide, only between 335 and 1,325 have the capacity to train and host large language models . Although currently few in number, generative AI models and the data centers that house them accounted for; the generative technology is straining the hardware stack that runs it.
with compute hardware as the base, supporting the software layers running atop it. Today, the GPU processor serves as the core of the compute hardware stack.Thunder Takes High Upside Swing In 2024 NBA Draft With Nikola Topic Although GPU performance is marginally improving, that growth is insufficient to keep up with the ever-increasing size of LLMs. As, the rate of model growth drastically accelerated in the four years between 2018 and 2022, increasing by five orders of magnitude. Open AI’s GPT-3 model, for example, was released in 2020 and leveraged 175 billion parameters., GPT-4, released in March 2023, offered a staggering 100 trillion parameters.