Part 7/10:
A significant aspect of running large AI models is memory: not just the amount, but how effectively it is utilized. Quantization techniques can affect the size and performance of AI models, allowing them to run on consumer-grade GPUs by reducing their size while attempting to maintain accuracy. The creator details several methods of quantization, noting that these techniques can enable models to operate within the RAM limitations of Macs.
By comparing the available processing power and memory, the creator attempted to push the limits of what five Mac Studios could accomplish. The use of MLX (Machine Learning Acceleration) on Mac was employed for better performance, but the bottlenecks in memory throughput remained a challenge.