Quantization is a crucial technique that enables massive AI models to run efficiently on smartphones and other resource-constrained devices. By reducing the precision of the numbers used in neural networks, quantization dramatically shrinks model size and speeds up inference without sacrificing much accuracy. This process converts high-precision floating-point weights to lower-precision integers, allowing AI giants to fit in your pocket.
Quantization is like compressing a high-resolution photo into a smaller file—you lose some detail, but the picture remains recognizable.
For a deeper dive, check out the full AI Learner series on YouTube and the accompanying article.