Pedro Domingos: The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

Statistical algorithms, 8

Statistical learning, 37, 228, 297, 300, 307

Statistical modeling, 8. See also Machine learning

Statistical relational learning, 227-233, 254, 309

Statistical significance tests, 76-77

Statistics, Master Algorithm and, 31-32

Stock market predictions, neural networks and, 112, 302

Stream mining, 258

String theory, 46-47

Structure mapping, 199-200, 254, 307

Succession, rule of, 145-146

The Sun Also Rises (Hemingway), 106

Supervised learning, 209, 214, 220, 222, 226

Support vector machines (SVMs), 53, 179, 190-196, 240, 242, 244, 245, 254, 307

Support vectors, 191-193, 196, 243-244

Surfaces and Essences (Hofstadter & Sander), 200

Survival of the fittest programs, 131-134

Sutton, Rich, 221, 223

SVMs. See Support vector machines (SVMs)

Symbolists/symbolism, 51, 52, 54, 57-91

accuracy and, 75-79

Alchemy and, 251-252

analogizers vs., 200-202

assumptions and, 64

conjunctive concepts, 65-68

connectionists vs., 91, 94-95

decision tree induction, 85-89

further reading, 300-302

hill climbing and, 135

Hume and, 58-59

induction and, 80-83

intelligence and, 52, 89

inverse deduction and, 52, 82-85, 91

Master Algorithm and, 240-241, 242-243

nature and, 141

“no free lunch” theorem, 62-65

overfitting, 70-75

probability and, 173

problem of induction, 59-62

sets of rules, 68-70

Taleb, Nassim, 38, 158

Tamagotchi, 285

Technology

machine learning as, 236-237

sex and evolution of, 136-137

trends in, 21-22

Terrorists, data mining to catch, 232-233

Test set accuracy, 75-76, 78-79

Tetris, 32-33

Text classification, support vector machines and, 195-196

Thalamus, 27

Theory, defined, 46

Theory of cognition, 226

Theory of everything, Master Algorithm and, 46-48

Theory of intelligence, 35

Theory of problem solving, 225

Thinking, Fast and Slow (Kahneman), 141

Thorndike, Edward, 218

Through the Looking Glass (Carroll), 135

Tic-tac-toe, algorithm for, 3-4

Time, as principal component of memory, 217

Time complexity, 5

The Tipping Point (Gladwell), 105-106

Tolstoy, Leo, 66

Training set accuracy, 75-76, 79

Transistors, 1-2

Treaty banning robot warfare, 281

Truth, Bayesians and, 167

Turing, Alan, 34, 35, 286

Turing Award, 75, 156

Turing machine, 34, 250

Turing point, Singularity and, 286, 288

Turing test, 133-134

“Turning the Bayesian crank,” 149

UCI repository of data sets, 76

Uncertainty, 52, 90, 143-175

Unconstrained optimization, 193-194. See also Gradient descent

Underwood, Ben, 26, 299

Unemployment, machine learning and, 278-279

Unified inference algorithm, 256

United Nations, 281

US Patent and Trademark Office, 133

Universal learning algorithm. See Master Algorithm

Universal Turing machine, 34

Uplift modeling, 309

Valiant, Leslie, 75

Value of states, 219-221

Vapnik, Vladimir, 190, 192, 193, 195

Variance, 78-79

Variational inference, 164, 170

Venter, Craig, 289

Vinge, Vernor, 286

Virtual machines, 236

Visual cortex, 26

Viterbi algorithm, 165, 305

Voronoi diagrams, 181, 183

Wake-sleep algorithm, 103-104

Walmart, 11, 69-70

War, cyber-, 19-21, 279-282, 299, 310

War of the Worlds (radio program), 156

Watkins, Chris, 221, 223

Watson, James, 122, 236

Watson, Thomas J., Sr., 219

Watson (computer), 37, 42-43, 219, 237, 238

Wave equation, 30

Web 2.0, 21

Web advertising, 10-11, 160, 305

Weighted k -nearest-neighbor algorithm, 183-185, 190

Weights

attribute, 189

backpropagation and, 111

Master Algorithm and, 242

meta-learning and, 237-238

perceptron’s, 97-99

relational learning and, 229

of support vectors, 192-193

Welles, Orson, 156

Werbos, Paul, 113

Wigner, Eugene, 29

Will, George F., 276

Williams, Ronald, 112

Wilson, E. O., 31

Windows, 12, 133, 224

Wired (magazine), 265

Wizard of Oz problem, 285

Wolpert, David, 62, 238

Word of mouth, 231

Xbox Live, 160-161

XOR. See Exclusive-OR function (XOR)

Yahoo, 10

Yelp, 271, 277

YouTube, 266

Zuckerberg, Mark, 55

PEDRO DOMINGOSis a professor of computer science at the University of Washington. He is a winner of the SIGKDD Innovation Award, the highest honor in data science. A fellow of the Association for the Advancement of Artificial Intelligence, he lives near Seattle.