The exponential growth in AI model complexity has driven parameter counts from millions to trillions, requiring unprecedented computational resources that…
The exponential growth in AI model complexity has driven parameter counts from millions to trillions, requiring unprecedented computational resources that require clusters of GPUs to accommodate. The adoption of mixture-of-experts (MoE) architectures and AI reasoning with test-time scaling increases compute demands even more. To efficiently deploy inference, AI systems have evolved toward large…
