Information is in life.
From “WHAT IS LIFE”
Paul Nurse, the author of this book, saw a butterfly fluttering into his garden one early spring day. He felt that the butterfly, though very different from himself, was unmistakably alive, just like himself, able to move, feel, and react, and moving toward his “purpose,” and wondered “What on earth does it mean to be alive? What does it mean to be alive?
WHAT IS LIFE” is a tribute to the physicist Erwin Schrodinger’s “What is Life?
Schrodinger became a famous physicist when he discovered the Schrodinger equation (also described in “The Equation Linking Time and Space” and “Quantum Mechanics, Artificial Intelligence, and Natural Language Processing“), which is familiar to those who study physics. In his book, he correctly recognized that it is a great problem how living things can maintain such a wonderful order and uniformity over generations in an entire universe that is constantly moving toward disorder and chaos according to the second law of thermodynamics. He believed that the key was to understand “heredity,” which is faithfully passed down from one generation to the next, and described it in “What is Life?
Like Schrodinger, What Is Life describes the origins of living organisms from the perspective of heredity, but at the end of the book there is a chapter on “Life as Information.”
Life as Information” is an approach that attempts to understand the existence and evolution of life from the perspective of information. From this perspective, life is seen not as a mere collection of matter, but as defined by processes such as information processing and gene transmission.
Life is characterized by the fact that it inherits information through genes and continues to change during evolution. Since genes encode the traits and functions of organisms, they can be viewed as a medium for information, and organisms can be thought of as having the ability to gather information from their environment and respond to it.
This information-centered perspective has led to the intersection of multiple disciplines, including biology, evolutionary biology, and information science, to form the idea of “life as information,” in which organisms are viewed as systems of information processing, and in this view, for example, evolution is said to be driven by processes such as information replication and mutation In this view, for example, evolution is driven by processes such as information replication and mutation.
This “life as information” begins with the following statement.
Why do butterflies fly in the city? There is no way to explain why butterflies behave the way they do, but what we can say for sure is that they interact with the world around them, and to do so, they manage information.
Information is at the heart of the butterfly’s existence and at the heart of all life. For an organism to function effectively as an organized and complex system, it must continually gather and use information about the state of both the outer world in which it lives and the inner world of the body. Because the inner and outer worlds change, living organisms need a way to detect and react to these changes. Otherwise, it would not be able to live very long.
In the case of butterflies, as they fly around, they use their senses to build up a detailed picture of the scene. Its eyes detect light, its sense of touch gathers the various chemical molecules in the area, its body hairs sense air vibrations, and it gathers a vast amount of information, from which it immediately puts together its actions into useful “knowledge.
This knowledge may have detected the shadow of a bird or curious child, and recognized the scent of honey wafting from its nose. This leads to an orderly series of wing movements that lead the butterfly to either avoid the bird or perch on a flower to suck nectar. The butterfly combines many different sources of information and uses them to make decisions that will improve its future.
This reliance on information is closely related to the organism’s purposeful behavior. The information that the butterfly gathers has some “meaning,” and the butterfly uses it to decide what to do next in order to achieve a particular goal. In other words, we can say that the butterfly was acting with a purpose.
In biology, it is not considered very strange to discuss purpose. In physics, on the other hand, we do not ask about the purpose of rivers, comets, or gravitational waves. But it makes sense to ask about the purpose of the cdc2 gene in yeast or the purpose of a butterfly flying.
Every living organism sustains itself, organizes itself, grows, and multiplies. These will be the purposes for which the organism has developed to achieve its basic purpose, which is to perpetuate itself and its offspring.”
Here it is stated that the difference between life and non-life is that it has a “purpose”. This “purpose” gives “meaning” to the information around life, which in turn determines what to do next, according to the statement.
“Biological Objectives” and “Information Meaning.”
Let us now consider a little more the relationship between the purpose of living organisms and the meaning of information.
In “Introduction to Philosophy” by Kazuhisa Todayama, which was previously mentioned in “What is Meaning (1): An Introduction to Philosophy” the term “purpose-measure inference” is used.
Purpose-measure reasoning” means that humans can act with purpose and can think (reason) about which means to choose in order to achieve a certain goal, and this purpose-measure reasoning makes it possible to strive for dreams and goals (in other words, objectives) that cannot be achieved right now. In the “Introduction to Philosophy,” it is stated that the difference between humans and other animals is that humans are able to have such an elaborate way of thinking.
A further consideration of the ends and means is the evolution of the cognitive design of living creatures as conceived by David Papineau. According to Papineau, there are several stages in the cognitive design of living creatures, beginning with the monotomata, followed by the opportunisy, and then the deeder.
The “monotomata” are the simplest design, creatures that obey only the command, “R.” In other words, these creatures always do only the same thing. In other words, this creature always does the same thing. For example, it will randomly rummage around with its mouth open, digesting and nourishing whatever comes into it.
In computer programming terms, this creature can be described as a simple procedural algorithm.
The next “opportunisy” is an organism that acts according to “If C, then R.” It can adapt its action R to the environmental condition C. Given the conditions under which R works as C, it will only do R if R works, thus saving energy and eliminating waste. This would be, for example, like a frog that only when a small black thing (usually a fly) appears in front of it, extends its tongue and eats it.
In programming terms, this is an if-then branch, like the expert systems described in “Rule Bases, Knowledge Bases, Expert Systems, and Relational Data. A more advanced algorithm would be one that uses robust matching of conditions using machine learning, as described in “Similarity in Machine Learning.
The third stage, “deeder,” is an organism that follows the command “if C and D, then R.” This means that the behavior R is only as good as the external environment C, and the behavior C is only as good as the external environment D. This is defined as an organism whose behavior R depends not only on the external environment C, but also on the internal environment of the organism at that time, i.e., its needs D. This would be, for example, a creature that would not eat an insect even if it sees one when it does not need nourishment.
In the programming world, this is the automaton described in “Outline and Implementation of Automata Theory, Reference Book“, the FSM described in “Outline and Implementation of Finite State Machines (FSM), Reference Book“, or the Petri Net described in “Outline of Petri Net Technology, Combination with Artificial Intelligence Technology, and Various Implementations” and the aforementioned branching, resulting in more complex algorithms.
In the “opportunisy,” external information is converted into information C (symbolization of information) that can be operated by the internal conditional branching algorithm. The “deeder” symbolizes the external information in the same way.
This external information in an internally available form C is called “meaning,” and the symbolized internal state that drives the action leads to what is called “purpose.
As described in “Abstract and Concrete from the Perspective of Natural Language” the meaning of words is found in an abstract world that is far removed from actual things, and as described in “Artificial Ineptitude in Zen and Buddabuddha,” that world is an infinite “empty” world. What brings order to this world is “purpose,” and the existence of this purpose is what makes living things what they are.
The discussion of “purpose” and “meaning” leads to Ruth Garrett Millikan’s pushmi-pullyu representations and James Gibson’s discussion of affordances, which I will discuss next time.
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