This article breaks down the key mathematical concepts behind neural networks, including weights, biases, and activations, with an example of handwritten digit recognition.

Take a detour before diving into transformers and explore sub-word tokenization techniques like Byte-Pair Encoding, WordPiece, and Unigram models. Learn how they handle rare words, reduce vocabulary size, and make models more efficient!

Decoding N-Grams: The Heart of Large Language Models

Why am I writing these AI blogs? Discover my journey into AI and LLMs!