A Brief History of Intelligence: Why the Evolution of the Brain Holds the Key to the Future of AI

What makes this book remarkable is how it demystifies AI by rooting it in something we already live with: the biological brain.

Max Bennett maps five evolutionary breakthroughs — from the first nerve cells to the modern neocortex — and shows that the most effective AI techniques aren’t alien inventions. They’re computational solutions evolution discovered over 500 million years of R&D, and we’re now re-discovering in silicon.

Reinforcement learning, the algorithm that powered AlphaGo’s victories? Fish brains invented it half a billion years ago as a simple reward-seeking mechanism. Emotions, one of AI’s hardest challenges to model? They likely began as a navigation solution in ancient worm brains — solving the same problem AI faces when deciding which state to pursue. Hierarchical pattern recognition in deep learning? A mirror of how the neocortex processes sensory input layer by layer. Even common sense, still an open problem in AI, traces back to the mouse brain’s internal model of physical reality.

This reframing changes everything. Suddenly, AI stops feeling like magic and starts looking like applied biology. For engineers building with AI, understanding why these approaches work — through the lens of evolutionary pressure — is far more valuable than just knowing how to call an API.

Who should read it: Engineers and technical leaders who want to understand why certain AI approaches work by connecting them to 500 million years of evolution the human brain already understands.