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Chapter 17.5 - Scaling Speedups (MoE KV Caching)

Overview

We've reached the final boss of AI architecture! To make models like GPT-4 insanely smart and fast, we use two ultimate tricks: MoE (Mixture of Experts) and KV Caching.

🎯 Why we do it​

Rationale
  • KV Caching: When an AI generates a sentence, it shouldn't have to re-read the whole sentence for every new word. KV Caching saves the old words so it only has to think about the new one!
  • MoE: Instead of one giant AI brain doing all the work, MoE splits the brain into tiny "Experts". One expert is great at Math, one is great at French.

🛠️ How we do it​

Methodology

For MoE, a "Router" looks at the word and decides which expert to send it to. The AI has 8 experts, but only uses 2 at a time! This means the AI is 8 times smarter, but runs just as fast as a small AI.

# A simple Router for Mixture of Experts!
word = "Bonjour"

if word == "Bonjour":
    print("Routing to the French Expert!")
elif word == "2+2":
    print("Routing to the Math Expert!")
else:
    print("Routing to the General Expert!")