When discussing AI inference infrastructure, the word “scaling” can mean several very different things. We might need more GPUs because a model is too large for a single GPU, more copies of a model because concurrency is increasing, or better routing between those copies because repeated context is consuming unnecessary compute. Eventually, we may also […]

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Artificial Intelligence (AI) is undergoing a rapid transformation, driven by advancements in hardware and software. Today, AI relies heavily on high-performance computing (HPC), GPUs, TPUs, ASICs, and optimised software frameworks. However, as AI models become more complex, the limits of current technology become apparent. This raises an important question: will the AI infrastructure we rely […]

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