A Single Binary Operator Can Generate Every Elementary Function, Researchers Prove
A new paper shows that one operation — eml(x,y) = exp(x) − ln(y) — can compose to produce sine, cosine, square roots, logarithms, and every other elementary function, with potential implications for neural network design.
Researchers have proven that a single binary operator, defined as eml(x,y) = exp(x) − ln(y), can generate every elementary mathematical function through composition, as detailed by @HowToAI_. The operator was found through exhaustive search rather than intuition, and it unifies sine, cosine, exponential, logarithmic, and root functions under one primitive. The post went viral, with particular interest from the AI community around the implications for neural architecture design.
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