·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.
deep-learning
7 articles
·Artificial Intelligence
Module 5 Lesson 1: Why Transformers Replaced Earlier Models
Before-Transformer (B.T.) and After-Transformer (A.T.). In this lesson, we learn about the architectural breakthrough that allowed AI to finally understand context at scale.
·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.
·AI Business
Module 1 Lesson 2: AI vs ML vs DL vs GenAI
Understand the 'AI Layer Cake'. Learn the technical differences and business implications of Machine Learning, Deep Learning, and the latest Generative AI wave.
·Generative AI
Module 1 Lesson 2: The AI Hierarchy
Understanding how Generative AI sits within the broader fields of Machine Learning and Deep Learning.
·AI & LLMs
Module 4 Lesson 1: Transformer Architecture Overview
The engine under the hood. A non-math guide to the Transformer architecture that powers all modern LLMs.
·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.