A popular technique to make AI more efficient has drawbacks | TechCrunch
Briefly

"Quantization is intended to make AI models less demanding mathematically, but studies indicate it may actually degrade performance, especially for models trained on vast datasets."
"At a certain point, it may actually be better to just train a smaller model rather than cook down a big one, challenging the assumptions of industry practices."
Read at TechCrunch
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