In this high paced language model research,
this website serves the objective of slow-paced and clean learning environment.
Core concepts: Tokenization, Attention, Positional Encoding, Embeddings, and Transformer Internals
Data Scaling Laws, Post-Training Alignment, Systems Efficiency, Evaluation Rigor, and Long-Context Limits
Sub-Quadratic SSMs, Test-Time Compute Scaling, Native Multimodality, 1.58-Bit Compression, and Interpretability