Description

How to Solve AI with Our Brain is a bold exploration of the future of artificial intelligence, authored by visionary thinker John Ball. This groundbreaking book exposes the flawed promises of traditional computational AI, highlighting its limitations in delivering on expectations of reliability and certainty. Instead, Ball directs attention to the transformative breakthroughs in cognitive science that can meaningfully propel AI into its next evolutionary stage.

In the book, John Ball explains the Patom Theory (PT), a language model that redefines how AI should process meaning. Using semantic structures such as predicates and referents, PT removes ambiguity from language interpretation and allows machines to convey and understand meaning accurately. Ball demonstrates how his system can successfully operate across multiple languages, providing a scalable solution that reflects how the human brain naturally manages language.

The book provides a critical examination of current AI technologies, such as autonomous vehicles and speech recognition, highlighting their limitations in achieving true human-like language comprehension. Ball argues that by tying AI development to cognitive science, we can build systems capable of understanding language with the precision and nuance that current models lack. His insights make a compelling case for rethinking AI’s future, especially in mission-critical applications.