Artificial intelligence (AI) projects primarily utilize modern programming languages such as C++, Python, and Java, rather than direct binary coding. While these high-level languages are eventually converted to binary through compilers, the focus is on more human-readable forms of coding. AI also heavily relies on mathematical concepts, including statistics, probability, and linear algebra, with different approaches to AI, such as traditional AI and cognitive AI, which emulates brain functions. There is a distinction between "strong AI," often depicted in media, and "weak AI," which is the practical application in use today. The discussion touches on the misconception that AI operates solely on binary logic, emphasizing that while expert systems often use binary predicates, neural networks operate on real-valued functions, addressing complexities beyond simple true/false evaluations. The conversation also highlights the relevance of binary in programming through boolean variables and bit flags, despite a misunderstanding regarding the nature of programming languages versus logic languages.