
Ever searched for a word in a massive book collection?
Image: TenOfAllTrades at English Wikipedia, Public domain, via Wikimedia Commons
Ever searched for a word in a massive book collection?
Imagine you're looking for a specific word in a huge library where books are scattered everywhere.
Think of the library as a map where each word is a landmark. The inverted index is like a guide that tells you exactly where to find each word, making searches quick and efficient.
Example
If you want to find the word "apple," the guide shows you all the books (documents) where "apple" appears, without flipping through every single book.
Remember this
The inverted index is a fast-search guide for finding words in large collections.
Text adapted from Wikipedia, licensed under CC BY-SA 4.0.
paged attention (vLLM) improves serving throughput
Paged attention (vLLM) improves serving throughput by reducing latency through non-contiguous KV-cache pages, enabling faster data retrieval
database sharding does: splits data across machines by a partition key
Why can't you just split a huge library into smaller ones?
Matrix multiplication algorithm
Ever wondered how computers speed up multiplying huge numbers?
RAG does: retrieves relevant documents before generating to reduce hallucination
RAG reduces AI hallucinations
GQA reduces KV-cache memory by the group factor
Ever wondered how websites stay fresh in search results?
The elastic net combines L1 and L2: λ₁|w| + λ₂w² gives both sparsity and stability
Why do we sometimes need both a scalpel and a hammer in surgery?
Swipe through 100 ML concepts daily
Open Pocket Polymath