This dire prediction is a large leap, one that many are hesitant to make. But it follows from a careful understanding of the ramifications of Moore's law and how it has been baked into almost every facet of society.
What is Moore's Law
Moore's Law is not a law at all. It was an observation made in 1965 by Gordon Moore, co-founder of Intel, that the number of transistors on a computer chip doubles every 18 months. The number of transistors on a computer chip is loosely correlated to the speed of a chip. A computer chip with double the number of transistors, can often do roughly twice as much as the previous chip.
Thus, Moore's Law implied that computer performance would grow exponentially. Roughly every 18 months, computer chips would double in performance. Moore did not provide much reason why this was the case, he just noticed an existing trend.
What made this Law famous and well known, is that for 50 years, it turned out to be true. For decades since this "Law" or more precisely "prediction" was made, computer chip performance has indeed improved exponentially.
For the last 50 years, this prediction has been working, but now it is
Many suspected that this doubling every 18 months could not continue indefinitely.
What is Exponential Growth
Exponential growth is something increases in size as a percentage of its current size. These curves grow exceedingly quickly, and while it's possible that they can exist over a certain period of time, they are inherently unsustainable. One of the better known examples of the extreme growth of exponential curves was illustrated by a 1000 year old wheat and chessboard problem.
Many centuries ago, a chess player challenged a king at a game of chess. If the challenger won, all he would ask for is a single grain of race on the day that he won, and that every day after he would get double the previous day, for as many days as there are on a chess board. The first day, he would get a single grain, the second day he would receive 2, the third day 4, the fourth day 8, and so one. The King, rich by controlling large fields rice, laughed at the challenger, believing that the he could easily pay such a wager.
As the story goes, the challenger won, and the King was obliged to pay. The first handful of days, paying the challenger was a triviality. However, the King foolishly underestimated the power of exponential growth, doubling over a fixed period of time. After just a few weeks, those handful of grains would turn into thousands of tons of rice. After the full 64 days, it word turn many billions of tons of rice, bankrupting the king.
The moral of this well known story is two fold: First, exponential growth is exceedingly fast, faster than most people can intuitively comprehend. The second, is that it is unsustainable. Had the wager continued for 100 days instead of just 64, the King would need to give the challenger enough rice to equal the weight of the entire planet earth.
Exponential Growth in Computer Chips is Not Just about Computer Chips
Anyone who has lived through the years 1960 to roughly 2010 has experienced exponential growth. For many decades, society has marveled at the speed of innovation. Though everyone would grumble about having to replace their computer ever two years because their previous one had become obsolete, these complaints had an element of pride that technology was improving rapidly.
However, the exponential growth in computing power through the latter half of the 20th century was not just about appeasing computer enthusiasts marveling at the wonders of technology, it had significant real-world impact.
Computers have fundamentally changed how companies do business. Obvious examples are spreadsheet applications, which fundamentally changed accounting. However, computers effected every industry in existence. Airlines could become far more efficient by finding ways to pack more people on to a plane. Customer support operators could handle far more requests by more efficiently routing questions. Farmers could better predict crop outcomes using more advanced computer intensive weather models. Brands could create global reach almost instantly, in what would have previously been a major labor intensive effort.
In short, computer chips affected almost every facet of commercial business. A single person could do much more with a computer in front of them than on their own, they could be far more efficient.
Why Efficiency Matters
A common measure of the power and wealth of a country is its Gross Domestic Product. One way of calculating a country's GDP is multiplying the number of people in a country with the average amount that they produce, often approximated by their take-home pay.
Thus, a country's GDP can be increased by either increasing the population, or by causing each person to produce more on average. Short term variations, i.e., 10 years, can occur due to cyclical credit cycles, but averaged out over decades, productivity and population largely determine GDP.
The growth of the U.S. economy in the latter half of the 20th century is largely attributed to these two factors: the population increased, and the output per person also increased.
The growth of the U.S. economy in the latter half of the 20th century is largely attributed to these two factors: the population increased, and the output per person also increased.
There aren't too many ways to make an individual output more. Sure, they can either work longer hours, but more commonly, they can use tools that allow them to do more in the same amount of time. A mechanic with a power drill can get things done much faster than one with a screw driver. An accountant with a spreadsheet can work much more quickly than one using pencil and paper.
What has Historically Driven Increased Efficiency
Two events have dramatically improved worker productivity over the last 150 years: the industrial and information revolution. Trains allowed the same number of humans to move far more goods than guides on horseback. Instant global communications have allowed businesses to react far more quickly than relying on postal mail.
Both the industrial revolution, which occurred roughly from 1850 to 1950, and the information revolution, which occurred roughly from 1960 to 2010, are called revolutions precisely because change occurred at an exponential rate.
Coming Up:
Both the industrial revolution, which occurred roughly from 1850 to 1950, and the information revolution, which occurred roughly from 1960 to 2010, are called revolutions precisely because change occurred at an exponential rate.
Coming Up:
- Why exponential improvements allow everyone to improve;
- Why exponential improvements to computer chips were the bedrock of increased efficiencies over the last 50 years;
- Why these improvements are hitting a wall;
- How the market has responded to this wall;
- How capital and labor are affected to the end of exponential productivity growth;
- How developing countries are affected by the end of exponential growth, and what it means ofr the U.S.
- What does all this mean for long term human development.
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