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AI is undoubtedly one of the hottest topics in the world today. NVIDIA's rise to Nasdaq's top spot, Nobel Prize recognition for AI pioneers, and nations prioritizing AI research all highlight its global importance. Graphics cards are now considered strategic assets, and discussions about AI dominate news, forums, and even casual conversations. Yet, how well do we really understand AI? What does it truly mean, and how does it work?
This project began as a deeply personal journey of discovery, rooted in curiosity and skepticism about the mechanics of neural networks. It has evolved into a comprehensive visualization tool designed to demystify AI, showcasing how simple mathematical operations come together to achieve incredible results.
The project started when I began learning AI with the book "Deep Learning from Scratch". Following its examples, I was both intrigued and skeptical: could a series of matrix multiplications and simple activation functions truly classify handwritten digits? It seemed too simple, so I decided to build everything from scratch, starting with matrix multiplication, to see it for myself.
When the core calculations worked as expected, it was a revelation. Simple arithmetic and elementary functions could indeed power a neural network. It was both humbling and awe-inspiring to realize how such basic building blocks could lead to sophisticated AI systems.
