Books like Deep Learning

01

The Master Algorithm

Pedro Domingos · Science

The Master Algorithm is Pedro Domingos's survey of machine learning — the field of computer science that creates algorithms capable of learning from data — organized around a central speculative thesis: that there exists, or may be found, a single master algorithm from which all learning can be derived.

Shares machine learning and artificial intelligence with Deep Learning.

02

Algorithms to Live By: The Computer Science of Human Decisions

Brian Christian and Tom Griffiths · Psychology

Brian Christian is a writer and Tom Griffiths is a cognitive scientist, and together they argue that computer science has worked out rigorous solutions to many of the problems humans face every day — when to stop searching for a better option, how to manage your schedule, how to sort your memory — and that these solutions are both interesting and useful.

A kindred science read.

03

How to Create a Mind

Ray Kurzweil · Science

Ray Kurzweil's central claim in How to Create a Mind is that the neocortex — the part of the brain responsible for higher thought — operates on a single repeating algorithm called the pattern recognition theory of mind.

Both dig into artificial intelligence.

04

Weapons of Math Destruction

Cathy O'Neil · Science

Weapons of Math Destruction is mathematician and data scientist Cathy O'Neil's investigation of how algorithms — statistical models used to make decisions about people's lives — can perpetuate and amplify inequality rather than reduce it.

A kindred science read.

05

Human Compatible: Artificial Intelligence and the Problem of Control

Stuart Russell · Science

Human Compatible is Stuart Russell's argument, from inside mainstream AI research, that the standard model of AI — build a system that optimizes for a fixed objective — is the wrong approach, and that the transition to much more capable AI systems requires a fundamental change in how AI is designed.

Shares machine learning and artificial intelligence with Deep Learning.

06

Superintelligence: Paths, Dangers, Strategies

Nick Bostrom · Science

Superintelligence is Oxford philosopher Nick Bostrom's systematic analysis of what might happen if artificial intelligence systems become more capable than humans — and why that transition might represent one of the most significant risks in human history.

Shares machine learning and artificial intelligence with Deep Learning.

07

The Alignment Problem

Brian Christian · Science

Brian Christian's The Alignment Problem examines a fundamental challenge in machine learning: how do you ensure that an artificial system actually pursues the goals you intend, rather than a close but dangerous approximation?

Shares machine learning and artificial intelligence with Deep Learning.

08

The Emperor's New Mind

Roger Penrose · Science

The Emperor's New Mind is Roger Penrose's argument that human consciousness cannot be reproduced by any computational device — that the mind is not, in the relevant sense, a computer — and that understanding consciousness will require fundamental advances in physics, particularly in reconciling quantum mechanics with general relativity.

Shares artificial intelligence and mathematics with Deep Learning.

09

Atlas of AI

Kate Crawford · Science

Atlas of AI is Kate Crawford's account of what artificial intelligence actually is — not a disembodied intelligence but a physical system built from extracted minerals, underpaid labor, vast energy consumption, and accumulated data taken largely without meaningful consent.

Both dig into artificial intelligence.

10

Chaos: Making a New Science

James Gleick · Science

Chaos: Making a New Science, published in 1987, tells the story of how a loose network of scientists working across meteorology, mathematics, biology, and physics in the 1960s and 1970s developed chaos theory — the study of systems that are deterministic but unpredictable because tiny differences in initial conditions produce wildly different outcomes.

Both dig into mathematics.

11

Fermat's Enigma

Simon Singh · Science

In 1637, Pierre de Fermat scrawled a note in the margin of a mathematics book claiming to have found a proof that no three positive integers can satisfy the equation a^n + b^n = c^n for any integer value of n greater than 2 — but that the margin was too narrow to contain it.

Both dig into mathematics.

12

Gödel, Escher, Bach

Douglas Hofstadter · Science

Douglas Hofstadter's Pulitzer Prize-winning debut, published in 1979, asks how meaning can arise from formal rules — how a biological machine can think, feel, and experience self-awareness.

Both dig into artificial intelligence.