Free What If? by Randall Munroe

thought had happened. She immediately replied, 2 “ Th e kid knocked over the vase and the cat is investigating.”
    She cleverly rejected alternate hypotheses, including:
Th e cat knocked over the vase.
Th e cat jumped out of the vase at the kid.
Th e kid was being chased by the cat and triedto climb up the dresser with a rope to escape.
Th ere’s a wild cat in the house, and someone threw a vase at it.
Th e cat was mummified in the vase, but arose when the kid touched it with a magic rope.
Th e rope holding the vase broke and the cat is trying to put it back together.
Th e vase exploded, attracting a child and a cat. Th e child put on the hat for protection from futureexplosions.
Th e kid and cat are running around trying to catch a snake. Th e kid finally caught it and tied a knot in it.
    All the computers in the world couldn’t figure out the correct answer faster than any one parent could. But that’s because computers haven’t been programmed to figure that kind of thing out, 3 whereas brains have been trained by millions of years of evolution to begood at figuring out what other brains around them are doing and why.
    So we could choose a task to give the humans an advantage, but that’s no fun; computers are limited by our ability to program them, so we’ve got a built-in advantage.
    Instead, let’s see how we compete on their turf.
    The complexity of microchips
    Rather than making up a new task, we’ll simply apply the same benchmarktests to humans that we do to computers. Th ese usually consist of things like floating point math, saving and recalling numbers, manipulating strings of letters, and basic logical calculations.
    According to computer scientist Hans Moravec, a human running through computer chip benchmark calculations by hand, using pencil and paper, can carry out the equivalent of one full instruction everyminute and a half. 4
    By this measure, the processor in a midrange mobile phone could do calculations about 70 times faster than the entire world population. A new high-end desktop PC chip would increase that ratio to 1500.

    So, what year did a single typical desktop computer surpass the combined processing power of humanity?
    1994.
    In 1992, the world population was 5.5 billion people, which means their combined computing power by our benchmark test was about 65 MIPS (million instructions per second).
    Th at same year, Intel released the popular 486DX , which in its default configuration achievedabout 55 or 60 MIPS. By 1994, Intel’s new Pentium chips were achieving benchmark scores in the 70s and 80s, leaving humanity in the dust.
    You might argue that we’re being a little unfair to the computers. After all, these comparisons are one computer against all humans. How do all humans stack up against all computers?
    Th is is tough to calculate. We can easily come up with benchmark scoresfor various types of computers, but how do you measure the instructions per second of, say, the chip in a Furby?

    Most of the transistors in the world are in microchips not designed to run these tests. If we’re assuming that all humans are being modified (trained) to carry out the benchmark calculations, how much effort should we spend to modify each computer chip so it can run the benchmark?
    To avoid this problem, we can instead estimate the aggregate power of all the world’s computingdevices by counting transistors. It turns out that processors from the 1980s and processors from today have a roughly similar ratio of transistors to MIPS — about 30 transistors per instruction per second, give or take an order of magnitude.
    A paper by Gordon Moore (of Moore’s law fame) gives figures for the total number of transistors manufactured per year since the 1950s. It looks somethinglike this:

    Using our ratio, we can convert the number of transistors to a total amount of computing power. Th is tells us that a typical modern laptop, which has a benchmark score in the tens of thousands of MIPS, has more