How AI Took Over The World

From the first neural networks built with matchboxes and beads to today's AI systems that can reason, create, and understand language, this video reveals how machines learned to think by copying nature's three-layered approach to learning. We'll journey through the key breakthroughs - from simple visual pattern recognition to game-playing AIs that developed "alien" strategies, and finally to language models that can imagine anything we can describe. Along the way, we'll discover how researchers unlocked each layer of intelligence: evolutionary learning that keeps what works, reinforcement learning that adapts within a lifetime, and finally, language learning that allows knowledge to be shared across minds. This is the story of how pattern prediction became pattern generation, and how machines learned to think... one layer at a time.

TIMESTAMPS:
00:45 Nature's Approach to Learning
01:35 The Matchbox Computer
03:00 Abstraction
04:00 Brain-Inspired Networks
07:45 The ImageNet Moment
09:20 From Recognition to Prediction
10:30 Physical AI
12:30 Language: The Final Layer
13:15 Shannon's Insight
15:00 The GPT Revolution
19:19 Beyond Language

Source: https://youtu.be/SN4Z95pvg0Y?si=oBRAC21B5J-JeBjL