Dr. Richard Wallace traces his AI journey to a 1990 New York Times article about the Loebner Prize, which inspired him to create ALICE—a chatbot that improved upon ELIZA’s simple pattern-matching with thousands of rules and the development of AIML, an XML-based language for structuring responses. His work exemplified supervised learning, contrasting with modern LLMs that rely on unsupervised learning from massive datasets. The discussion explores how both humans and machines use predictable, 'robotic' language patterns, questioning assumptions about human uniqueness. Wallace critiques the Turing Test’s relevance and highlights the 2017 'Attention is All You Need' paper as a pivotal moment in AI. Today, at Franz, he works on neurosymbolic AI—merging symbolic reasoning with neural networks—for applications like medical prediction. This hybrid approach aims to combine the interpretability of rule-based systems with the flexibility of deep learning, addressing ongoing challenges in transparency and machine creativity.