Neural Networks Unveiled: From Perceptrons to Transformers

Welcome to Neural Networks Unveiled, the podcast where we break down the intricate world of artificial intelligence, one layer at a time. In this episode, we take you on a journey through the evolution of neural networks, from the fundamental concept of perceptrons to the cutting-edge transformer architectures that power today’s AI marvels.

We explore how neural networks mimic the structure of the human brain to tackle complex problems, diving into key components such as neurons, layers, weights, biases, and activation functions like ReLU and sigmoid. We also unravel the mechanics of training a network, from cost functions and gradient descent to the powerful process of backpropagation. But that’s not all—we’ll also shed light on the transformer architecture, the backbone of models like ChatGPT, explaining how attention mechanisms, multi-headed attention, and token embeddings make AI smarter than ever. Whether you’re a curious beginner or an AI enthusiast, this episode will equip you with a deep understanding of how machines learn, adapt, and transform the way we interact with technology.