The Singularity Is Near - Chapter Two: A Theory of Technology Evolution

Chapter Two: A Theory of Technology Evolution

Each stage of biological evolution and technological innovation increases the level of biological or technological order and enables entry into the next stage. Order in this case is defined as how well the form (genetic or physical) suits the given function. For example, a modern car is better suited for transporting human occupants than a Model T because the newer vehicle possesses numerous design improvements the older one lacks.

An increase in order also generally correlates with an increase in complexity. Getting back to the previous example, a modern car has more moving parts than a Model T, and the newer car's parts are also more precisely and elaborately made. Thus, the modern car is more complex. The overall trend towards increasing complexity can also be observed in biology, where genomes of living species have gradually grown in size along with levels of physical diversity and specialization.

Of course, greater order does not necessarily always entail greater complexity. Sometimes, the simpler solution proves superior both in biology and technology, but the general trends in both have been towards more complexity and more order.

The Law of Accelerating Returns states that biological and technological evolution utilize positive feedback, with each improvement building upon the last and enabling the next.

Technological progress in any field consists of a series of "paradigms"—particular methods used to solve certain problems. A given example of a paradigm would be the shrinking of computer transistors to make the computers more powerful. While there are innumerable technological paradigms, all share the same basic life cycles. The advances in the cost-performance of a particular technology, or the Life Cycle of the Paradigm, if graphed, will appear as a sigmoidal S-shape with three distinct phases.

Slow Growth Phase

At this point, the kinks in the technology are still being worked out, and it is still struggling to establish a market base. Growth in price-performance and capabilities is exponential, but still at such an early stage that the growth appears deceptively flat and linear.

Rapid Growth Phase

Begins after the exponential growth passes the "knee of the curve" and explosive growth in the technology's capabilities and user base starts.

Leveling Off Phase

The technology matures as scientists find it increasingly more difficult to make improvements to the same technology in an effort to further address the original need. Growth in usefulness levels off.

Once a technology has reached maturity, it is replaced by a newer, totally different technology, meaning a paradigm shift occurs. This occurred during the 1960s when scientists found it impractical to shrink computer vacuum tubes any further and instead switched to transistors, which were newer and allowed the process of miniaturization to continue.

This process of periodic exponential growth parallels biological evolution in two ways. First, biological evolution also occurs in spurts and, second, some biological innovations make organisms exponentially better or speed up evolution from that point onwards in an exponential manner. For example, the advent of DNA allowed life forms to evolve much higher levels of complexity and order.

Society's acceptance of new technologies is speeding up exponentially

• U.S. Phone company revenues and daily number of American phone calls (increasing exponentially)
• Number of U.S. cell phone subscribers (increasing exponentially)
• Time until major new inventions reach mass use by American consumers (decreasing exponentially)

Technologies experiencing exponential changes:

• Increasing exponentially:
  • Microprocessor clock speeds
  • Transistors per microprocessor
  • Processor performance
  • Dynamic RAM price performance (improving exponentially)
  • Random Access Memory bits per dollar
  • Magnetic data storage bits per dollar
  • Wireless Internet and phone services price performance
  • Number of Internet hosts
  • Bytes of Internet traffic
  • Internet backbone bandwidth (increasing in a very terraced, quasi-exponential manner)
  • Number of scientific citations for nanotechnology research
  • Number of U.S. nanotech patents

• Decreasing exponentially:
  • Average Transistor price
  • Transistor Manufacturing costs
  • Dynamic RAM size (smallest feature sizes decreasing exponentially)
  • Microprocessor costs
  • DNA sequencing costs per base pair
  • Mechanical device sizes

While Gordon Moore first observed in 1965 that the transistor densities of integrated circuits were doubling every two years, an extended analysis shows that computers have been experiencing exponential improvements to their cost-performance (maximum number of calculations per second per $1,000) since at least 1900, when the very first electromechanical computers were invented. This trend in increasing performance has held steady across five computer paradigm shifts (electromechanical, relay-based, vacuum tube, transistor, and integrated circuit) and is now encapsulated by Moore's Law. While integrated circuits will—like all paradigms—ultimately reach the limits of their possible capabilities, the exponentially growing performance trend will likely continue via a paradigm shift to a newer technology like memristors or three-dimensional molecular computing.

Extrapolating this rate of improvement, supercomputers should be capable of the same number of calculations per second as a human brain by 2010, and personal computers should be at this level around the year 2020. The amount of improvement in nanoscience at the same rate also see 2020 as a nexus point.