What intelligence really is, and how AI’s emergence is a natural consequence of evolution.

Included in the Financial Times's Best Books of 2025: Technology
Included in Bloomberg News's "The 82 Books That Top Business Leaders Couldn’t Put Down"
2026 PROSE Award Winner: Engineering and Technology

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 Ag�era 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.

About the Author

Blaise Ag�era y Arcas is a VP/Fellow at Google, where he is the CTO of Technology & Society, and the founder of Paradigms of Intelligence, an organization dedicated to fundamental AI research. He is the author of Who Are We Now?, and his research has included work on privacy-preserving machine learning, on-device AI, large language models, and human identity.

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