Books like Kluge by Gary Marcus

Daniel Kahneman's "Thinking, Fast and Slow" explains how two distinct mental systems shape our judgments and decisions, offering insights into the biases that influence everyday choices.

Nick Bostrom explores the risks and possibilities of future machine superintelligence, examining how human dominance could shift if artificial minds surpass us, and considering strategies for a survivable transition.

Kurzweil explores the coming fusion of human minds with advanced machines, predicting that integrated intelligence will surpass current human capacity, shaping future society.

Pedro Domingos unveils the quest for a universal learning algorithm that could extract any knowledge from data, exploring how such a machine—the Master Algorithm—might reshape business, science, and society.

Deep Learning is a comprehensive textbook that equips students and practitioners with the foundational knowledge and practical skills needed to enter the fields of machine learning and deep learning.

Louise Barrett argues that intelligent animal behavior relies less on brain size and more on the interplay between body, environment, and evolution.

Anjan Chatterjee blends neuroscience and evolutionary psychology to explain how pleasure shapes our perception of beauty and art, exploring questions about the universality of aesthetic experience and the evolutionary roots of artistic instinct.

How deep learning-from Google Translate to driverless cars to personal cognitive assistants-is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

David J. Chalmers explores the mystery of consciousness, arguing that a reductive, purely materialist account is insufficient and outlining a possible fundamental theory linking physical processes and subjective experience.