Unveiling the simple math that powers AI

Don't let math intimidate you — simple math powers complex systems.
As a Java developer without a formal math background, I became curious about the mathematical foundations behind AI and computation. What I discovered was that intelligent systems are often rooted in surprisingly simple mathematical concepts.
In this beginner-friendly talk, we’ll explore how boolean logic drives agent decision trees, why floating-point precision impacts confidence scores, and how vector geometry underlies recommendation systems. And yes, we’ll even revisit the basics of machine-level binary and hexadecimal number representations.
Whether you're new to the field or brushing off old knowledge, this session offers hands-on Java examples that demystify key mathematical concepts. You’ll see that the math behind AI is more relatable than you might think!