Attention Mechanism
What attention mechanisms are, how they enable transformers to process sequences, and why they matter for modern AI architectures.
Transformer
Flash Attention
How Flash Attention makes transformer self-attention memory-efficient by restructuring computation to minimize GPU memory reads and writes.
Long-Context Model
How modern architectures handle 100K to 1M+ token contexts through positional encoding advances, memory-efficient attention, and …
Positional Encoding
How transformers represent sequence order using sinusoidal, rotary (RoPE), and ALiBi positional encoding schemes.
Transformer Architecture
What the transformer architecture is, how it differs from prior approaches, and why it dominates modern AI systems.