Quantization Effects Simulator
Explore memory-accuracy trade-offs in embedding quantization from float32 to binary representations.
No direct links0 refs
ML Concepts - Page 15
Clear explanations of core machine learning concepts, from foundational ideas to advanced techniques. Understand attention mechanisms, transformers, skip connections, and more.
136
Total Concepts
228
Topics
Page 15
of 23
Concepts - Page 15
Sparse vs Dense Embeddings
Compare lexical (BM25/TF-IDF) and semantic (BERT) retrieval approaches, understanding their trade-offs and hybrid strategies.
No direct links0 refs
Context Windows: The Memory Limits of LLMs
Interactive visualization of context window mechanisms in LLMs - sliding windows, expanding contexts, and attention patterns that define what models can "remember".
No direct links0 refs
Flash Attention: IO-Aware Exact Attention
Interactive visualization of Flash Attention - the breakthrough algorithm that makes attention memory-efficient through tiling, recomputation, and kernel fusion.
No direct links0 refs
KV Cache: The Secret to Fast LLM Inference
Interactive visualization of key-value caching in LLMs - how caching transformer attention states enables efficient text generation without quadratic recomputation.
No direct links0 refs
Tokenization: Converting Text to Numbers
Interactive exploration of tokenization methods in LLMs - BPE, SentencePiece, and WordPiece. Understand how text becomes tokens that models can process.
No direct links0 refs
Showing 85-90 of 136 articles