Read: 2026-05-24
Recommend: 6/10
The book uses many intuitive examples to explain complex concepts in computer science algorithms.
Here are some text that I highlighted in the book:
Hofstadter’s terror was in response to something entirely different. It was not about AI becoming too smart, too invasive, too malicious, or even too useful. Instead, he was terrified that intelligence, creativity, emotions, and maybe even consciousness itself would be too easy to produce—that what he valued most in humanity would end up being nothing more than a “bag of tricks,” that a superficial set of brute-force algorithms could explain the human spirit.
An Exponential Fable For a simple illustration of exponential growth, I’ll recount an old fable. Long ago, a renowned sage from a poor and starving village visited a distant and rich kingdom where the king challenged him to a game of chess. The sage was reluctant to accept, but the king insisted, offering the sage a reward “of anything you desire, if you are able to defeat me in a game.” For the sake of his village, the sage finally accepted and (as sages usually do) won the game. The king asked the sage to name his reward. The sage, who enjoyed mathematics, said, “All I ask for is that you take this chessboard, put two grains of rice on the first square, four grains on the second square, eight grains on the third, and so on, doubling the number of grains on each successive square. After you complete each row, package up the rice on that row and ship it to my village.”
Kurzweil points out that if the trends continue (as he believes they will), a $1,000 computer will “achieve human brain capability (1016 calculations per second) … around the year 2023.”28 At that point, in Kurzweil’s view, human-level AI will just be a matter of reverse engineering the brain.
because you’re using information from the test set to change your program, you’ve now destroyed the ability to use the test set to see if your program generalizes well. It would be like allowing students to take a final exam many times, each time getting back a single grade, but using that single grade to try to improve their performance the next time around. Then, at the end, the students submit the version of their answers that got them the best score. This is no longer a good measure of how well the students have learned the subject, just a measure of how they adapted their answers to particular test questions.