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Integrated Circuits was not the first, but the fifth paradigm to continue the now one-century-long exponential growth of computing. Each new paradigm came along just when needed. This suggests that exponential growth won’t stop with the end of Moore’s Law. But the answer to our question on the continuation of the exponential growth of computing is critical to our understanding of the twenty-first century. So to gain a deeper understanding of the true nature of this trend, we need to go back to our earlier questions on the exponential nature of time.

THE LAW OF TIME AND CHAOS
     
    Is the flow of time something real, or might our sense of time passing be just an illusion that hides the fact that what is real is only a vast collection of moments?
    —Lee Smolin
     

    Time is nature’s way of preventing everything from happening at once.
    —Graffito
     
     
Things are more like they are now than they ever were before.
    .—Dwight Eisenhower
     
     
    Consider these diverse exponential trends:
    • The exponentially slowing pace that the Universe followed, with three epochs in the first billionth of a second, with later salient events taking billions of years.
    • The exponentially slowing pace in the development of an organism. In the first month after conception, we grow a body, a head, even a tail. We grow a brain in the first couple of months. After leaving our maternal confines, our maturation both physically and mentally is rapid at first. In the first year, we learn basic forms of mobility and communication. We experience milestones every month or so. Later on, key events march ever more slowly, taking years and then decades.
    • The exponentially quickening pace of the evolution of life-forms on Earth.
    • The exponentially quickening pace of the evolution of human-created technology, which picked up the pace from the evolution of life-forms.
    • The exponential growth of computing. Note that exponential growth of a process over time is just another way of expressing an exponentially quickening pace. For example, it took about ninety years to achieve the first MIP (Million Instructions per Second) for a thousand dollars. Now we add an additional MIP per thousand dollars every day. The overall innovation rate is clearly accelerating as well.
    • Moore’s Law on Integrated Circuits. As I noted, this was the fifth paradigm to achieve the exponential growth of computing.
    Many questions come to mind:
    What is the common thread between these varied exponential trends? Why do some of these processes speed up while others slow down? And what does this tell us about the continuation of the exponential growth of computing when Moore’s Law dies?
     
    Is Moore’s Law just a set of industry expectations and goals, as Randy Isaac, head of basic science at IBM, contends? Or is it part of a deeper phenomenon that goes far beyond the photolithography of integrated circuits?
    After thinking about the relationship between these apparently diverse trends for several years, the surprising common theme became apparent to me.
    What determines whether time speeds up or slows down? The consistent answer is that time moves in relation to the amount of chaos. We can state the Law of Time and Chaos as follows:
    The Law of Time and Chaos: In a process, the time interval between salient events (that is, events that change the nature of the process, or significantly affect the future of the process) expands or contracts along with the amount of chaos.
     
    When there is a lot of chaos in a process, it takes more time for significant events to occur. Conversely, as order increases, the time periods between salient events decrease.
    We have to be careful here in our definition of chaos. It refers to the quantity of disordered (that is, random) events that are relevant to the process. If we’re dealing with the random movement of atoms and molecules in a gas or liquid, then heat is an appropriate measure. If we’re dealing with the process