Can We Build Technologies
That Can Learn How To Make Their Own Decisions?

Disclosure Note from Margi Wilson: Before you read this, please note that I do not have a PhD in quantum physics or computer science. That means that you don't need to take anything that you read here seriously. Like most people, I was born with a desire to know things. This is written simply with the possibility that you may want to think along with others about the future of technology.

These days anyone can learn anything from anywhere. All that is needed is the desire to know and a computer, or even just a human brain. Even from within ourselves. It seems brain researchers are discovering the ability of the human physiology to pick up billions of bits of information from many different environmental sources, near and far, without us being consciously aware of all the information we are picking up. On top of that, our DNA has been storing useful information for billions of years.

So if you like to put together puzzles, and if you have curiosity and the ability to access information, you can put the bits and pieces together and come up with some interesting things to think about.

Adaptive Self Organizing Criticality: How Nature Makes Decisions Spontaneously Following the Law of Least Action

What has enamored me lately is looking at how nature organizes itself so spontaneously. Nature is making decisions all the time; where should I put this leaf, how hard should I make this stem. If there is a fence in the way, I need to adapt and grow around the fence.

From what I have learned from my "mentors"... there is one law that all the known laws of nature have in common. And this one law is very important for us to look at for its practical applications in technology.  That one golden law is the law of least action.

The law of least action, it seems, is the law that is responsible for the economy that we see in nature.

• Please note that the word "economy" as found in nature, does not mean sub standard or deprived. As we can see, there is abundance in nature. At the same time nothing is wasted. This is the sense that we can understand the word economy - nothing is wasted. The mango tree has thousands of mangoes and even if most of them fall on the ground and rot, they are not wasted as they nourish the soil.

How did natural systems get to this point of mastery over the law of least action? Can we apply this law to artificial systems to make them more economical?

When asking these questions, I remembered when I was a little girl, my father brought home from his work some computer modules for us to play with. It was all about ones and zeros. And I realized the computer didn't really know anything. We had to tell it what to do. If this... then you do this. If this... then this. We told it how to decide everything. Imagine a parent having to tell a teenager how to make every decision.... "if this happens then I want you to do this, but if this happens, then you should do this...."

Instead we release the teenagers into the world and they learn how to make their own decisions. Will modern technology get to the point where computers can learn to make their own decisions?

What is the state of artificial intelligence today? Even after decades and billions of hours of programming, computers still have a hard time recognizing patterns, and their decision making skills still leave a lot to be desired. But from what I have gathered from listening to wise inventors, and youtube physicists, people are beginning to glimpse how choices are made in natural systems, and they are getting some ideas how this same approach can be applied to help our computers be more intelligent at decision making.

They are discovering that at every critical decision making point, if the law of least action is followed, every variable is automatically taken into account and the final choice is invariably the most economical choice. The optimal answer is computed automatically when the law of least action is mastered. Mastering or optimizing of the law of least action requires that we structure adaptability into the electronic design.

This video gives some great examples of nature using the law of least action to accomplish its goals and overcome problems: Biomimicry in action

In order to be completely successful at uncovering the underlying blueprints that are used by nature and applying those blueprints to allow computers to make decisions, we must first discover how to use the automatic computation and measurement system that natural systems use. Otherwise our creations will still be out of phase, or out of sync with nature, and will not be sustainable. They will continue to create unintended consequences.

The following video gives some nice insights into how nature measures things.

"...Simple rules that are repeated without end." Benoit Mandelbrot on Fractals 

Measurement is both accuracy and precision together.

Precision has to do with repeatability. 

Understanding how opposite values are integrated is essential for perfect repeatability. How do we integrate the classical and quantum realms?

The following seven minute video gives an idea of the pulsating nature of things on the quantum level. Without an intuitive understanding of what is happening on these very fine levels of the material world, decision making can become confusing. Uncertainty takes over. And repeatability is more a matter of luck.

But when we understand what is happening, that the particles are not fixed, that the material world on a quantum mechanical level is more like a living breathing thing, predictability becomes more accessible. This video helps us see that everything follows the laws of quantum mechanics... Aaron O Connell Making sense of a visible quantum object

Perfect predictability and repeatability are not possible without exact measurement.

Exact measurement is not possible without fully optimizing the law of least action. Fully optimizing the law of least action is how nature accomplishes exact measurement. Here's an example how using the law of least action, by allowing some flexibility, can help accomplish more exact measurement: metronomes ...this can happen because the table is allowed to move. The metronomes are too rigid to do this without the table being flexible. Natural time is more flexible than a metronome.

Whenever you have opposite values, you have a point where the opposite values are in a state of perfect balance, where activity is at its least excited state. This is what we can call a critical point, where a decision can be made.

Think of a pendulum as it swings. There are points where the pendulum is not moving. In that critical point it has the possibility, if it is not restricted, of adapting to the environment. There is really no choice to be made.. or we could say that the choice is so obvious, it is not really a choice. There is only one way to move, which is in accord with the law of least action, taking into account all variables in the near and far environment. This is accomplished automatically and spontaneously in natural systems. It is in this sense that we can see how optimizing the law of least action facilitates creating computers that can make intelligent decisions.