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What Is Intelligence?: Lessons from AI About Evolution, Computing, and Minds
What intelligence really is, and how AI’s emergence is a natural consequence of evolution.
It has come as a shock to some AI researchers that a large neural net that predicts next words seems to produce a system with general intelligence. Yet this is consistent with a long-held view among some neuroscientists that the brain evolved precisely to predict the future—the “predictive brain” hypothesis.
In What Is Intelligence?, Blaise Agüera y Arcas takes up this idea—that prediction is fundamental not only to intelligence and the brain but to life itself—and explores the wide-ranging implications. These include radical new perspectives on the computational properties of living systems, the evolutionary and social origins of intelligence, the relationship between models and reality, entropy and the nature of time, the meaning of free will, the problem of consciousness, and the ethics of machine intelligence.
The book offers a unified picture of intelligence from molecules to organisms, societies, and AI, drawing from a wide array of literature in many fields, including computer science and machine learning, biology, physics, and neuroscience. It also adds recent and novel findings from the author, his research team, and colleagues. Combining technical rigor and deep up-to-the-minute knowledge about AI development, the natural sciences (especially neuroscience), and philosophical literacy, What Is Intelligence? argues—quite against the grain—that certain modern AI systems do indeed have a claim to intelligence, consciousness, and free will.
It has come as a shock to some AI researchers that a large neural net that predicts next words seems to produce a system with general intelligence. Yet this is consistent with a long-held view among some neuroscientists that the brain evolved precisely to predict the future—the “predictive brain” hypothesis.
In What Is Intelligence?, Blaise Agüera y Arcas takes up this idea—that prediction is fundamental not only to intelligence and the brain but to life itself—and explores the wide-ranging implications. These include radical new perspectives on the computational properties of living systems, the evolutionary and social origins of intelligence, the relationship between models and reality, entropy and the nature of time, the meaning of free will, the problem of consciousness, and the ethics of machine intelligence.
The book offers a unified picture of intelligence from molecules to organisms, societies, and AI, drawing from a wide array of literature in many fields, including computer science and machine learning, biology, physics, and neuroscience. It also adds recent and novel findings from the author, his research team, and colleagues. Combining technical rigor and deep up-to-the-minute knowledge about AI development, the natural sciences (especially neuroscience), and philosophical literacy, What Is Intelligence? argues—quite against the grain—that certain modern AI systems do indeed have a claim to intelligence, consciousness, and free will.
625 pages, Kindle Edition
Published November 15, 2025
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March 2, 2026
What Is Intelligence? is a wonderfully written book that draws on evolutionary biology, neuroscience, and computer science to argue that prediction is the fundamental thread connecting biological life and artificial intelligence. Once you see the connection, it's hard to unsee.
The book builds its case progressively through multiple fields of knowledge, but as a reader you don't need a background in any particular area because the author explains each concept and each progression in simple terms. I am a software engineer, and even as someone already familiar with the math equations of the Attention and Transformer concepts in AI, I found the explanations here notably better at connecting-the-dots than anywhere else I've seen.
I bought both the audiobook and the print one. I've never done that before, and it has been worthwhile for me to have this particular book in both formats. The audiobook has been a pleasant listening experience because the author's natural enthusiasm for his work comes through in his voice. The print, along with its diagrams, have been useful for deeper studying of the ideas.
The book is thought-provoking, and I recommend it to anyone with a curious mind. If you are hungry for intellectually stimulating material, I am sure you will enjoy this book as much as I did.
The book builds its case progressively through multiple fields of knowledge, but as a reader you don't need a background in any particular area because the author explains each concept and each progression in simple terms. I am a software engineer, and even as someone already familiar with the math equations of the Attention and Transformer concepts in AI, I found the explanations here notably better at connecting-the-dots than anywhere else I've seen.
I bought both the audiobook and the print one. I've never done that before, and it has been worthwhile for me to have this particular book in both formats. The audiobook has been a pleasant listening experience because the author's natural enthusiasm for his work comes through in his voice. The print, along with its diagrams, have been useful for deeper studying of the ideas.
The book is thought-provoking, and I recommend it to anyone with a curious mind. If you are hungry for intellectually stimulating material, I am sure you will enjoy this book as much as I did.
Displaying 1 of 1 review