"Don't just grab your training runtime or your favorite framework. Find a runtime specialized for inference serving and understand your AI problem deeply to pick the right optimizations." - Qi
Qi emphasized that the work involves not just infrastructure techniques but also close collaboration with model developers to achieve end-to-end optimization.
Techniques like continuous batching help improve responsiveness and throughput. Quantization, the practice of reducing model precision to unlock hardware efficiency, was highlighted as a major lever for performance gains, often achieving 2-4x improvements.
#large-language-models #infrastructure-optimization #performance-tuning #ai-deployment #computational-challenges
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