Quantization techniques are reshaping how large language models run worldwide, cutting inference costs and energy use. By training models directly in low‑precision formats, researchers avoid costly post‑hoc conversion, speeding deployment across data centers and edge devices.
The Signal
Companies like OpenAI and NVIDIA are adopting these methods, promising faster, greener AI for global applications.