IBM Technology: What Is Quantization? How AI Models Get Smaller & Faster

Learn more about Quantization here → https://ibm.biz/~NdqpU881V



Huge AI models come with huge memory requirements.Grace Ableidinger explains how quantization compresses LLMs using lower-precision formats like INT8 and INT4. Learn how model size, GPU memory, speed, and accuracy trade off during AI inference.



00:00 – Understand What Quantization Does

00:23 – See Why LLMs Need Quantization

00:51 – Connect AI Parameters to Memory Requirements

01:31 – Calculate the Memory Cost of a 70B LLM

02:13 – See How Quantization Reduces Precision

02:53 – Follow Quantization Layer by Layer

04:21 – Compare FP16, FP8, INT8 & INT4

05:34 – Balance Memory Savings with Model Accuracy

06:33 – Compare PTQ vs Quantization-Aware Training

07:17 – Choose the Right Quantization Tradeoff



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AI was used in the creation of the transcript and metadata for this video.



#llm #aimodels #aiinference #machinelearning #aiengineering



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