Optimizing AI Inference on Non-GPU Architectures by Rajalakshmi Srinivasaraghavan

This story was originally published on HackerNoon at: https://hackernoon.com/optimizing-ai-inference-on-non-gpu-architectures-by-rajalakshmi-srinivasaraghavan . Rajalakshmi Srinivasaraghavan drives AI innovation by optimizing inference on CPUs, making AI faster, scalable, and more accessible beyond GPUs. Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning . You can also check exclusive content about #ai-inference-optimization , #cpu-ai-performance , #non-gpu-ai , #scalable-ai-systems , #rajalakshmi-srinivasaraghavan , #high-performance-computing , #sustainable-ai-infrastructure , #good-company , and more. This story was written by: @kashvipandey . Learn more about this writer by checking @kashvipandey's about page, and for more stories, please visit hackernoon.com . While GPUs dominate AI, Rajalakshmi Srinivasaraghavan proves CPUs can deliver powerful, scalable AI inference. Her work in CPU optimizations boosted performance by up to 50%, automated CI pipelines, and enabled day-one readiness on new hardware. With a focus on mentorship and forward-looking design, she is shaping AI infrastructure that’s affordable, efficient, and accessible.