Large language models function as universal translators by embedding all training data in a high-dimensional space where similar concepts cluster together, enabling them to translate between any input and output modalities. The author describes building personal translation tools for a Spanish-language conference in Argentina and explores how LLMs could democratize translation while fostering human connection through accessibility.