As artificial intelligence models continue to grow in size and complexity, the computational and memory requirements for deployment have become increasingly prohibitive. Modern large language models (LLMs) like GPT-4 and Claude contain hundreds of billions of parameters, requiring substantial hardware resources for both training and inference. Quantization has emerged as one of the most effective […]
