·Artificial Intelligence
Module 5 Lesson 3: Layers and Depth
Why does an LLM need 96 layers? In this lesson, we explore how stacking attention blocks creates a hierarchy of meaning, moving from basic letters to complex abstract logic.
neural-networks
4 articles
·Artificial Intelligence
Module 5 Lesson 2: Attention Mechanism (Intuitive Explanation)
Why is 'Self-Attention' the most important invention in AI history? In this lesson, we use a simple library analogy to explain how LLMs decide what to focus on.
·AI Security
Module 6 Lesson 4: Robustness Limitations
Why we can't just 'Patch' AI. Explore the fundamental reasons why deep neural networks are inherently fragile and vulnerable to adversarial noise.
·Artificial Intelligence
Neural Networks: How they work and why they are so powerful (with code examples)
A deep dive into the architecture of neural networks, exploring layers, activation functions, and why they dominate modern AI.