Activation Functions and Loss Functions: The Engines of Neural Network Learning Introduction If the perceptron is the brick of artificial intelligence, then activation functions and loss functions are the mortar and the blueprint. A neural network without an activation function is merely a glorified linear regression model. A network without a loss function is a…
Introduction Before 2017, language models struggled with long-range dependencies. Words far apart in a sentence would lose their relationship. Then came the paper “Attention Is All You Need”—and everything changed. The core innovation? Self-attention and multi-head attention. Today, every major AI model (GPT, BERT, Gemini, Llama) uses these mechanisms. In this post, we’ll break down: No advanced math. Just…
If you have heard of ChatGPT or BERT, you have already met the two most important families of language models: auto-regressive (AR) models and masked language models (MLM). They learn language in completely different ways, and that difference shapes what they can and cannot do. In this post, I will explain everything in plain English:…