Books, bodies, and beautiful paintings – these are all emergent systems. As our understanding of these systems grows, so, too, do the questions about how we study them.

Scientific revolutions require the shift of paradigms [1]. According to Thomas Kuhn, a paradigm is more than a current theory and its implications. It’s also combined with a worldview where the theory exists. As an example, classical mechanics does not only consist of Newtonian laws, but also has a deterministic worldview. Kuhn states that when the anomalies and limitations of the current paradigm are encountered in the scientific community, new ideas pour in and thereby a new paradigm is formed. The development of quantum mechanics against classical mechanics is an example of such a paradigm shift. Along with this shift, not only new formulas and theories were developed, but a new worldview – one that was not deterministic – emerged.

In the last century, we witnessed many scientific breakthroughs in the areas of chemistry, computer science, medicine, molecular biology, and physics. Along with the experience and knowledge we gained from them, we still try to understand the secrets of the universe we live in from “very small” to “very big.” However, certain systems, so-called complex systems, push the limits of our scientific theories and the tools used to analyze them. In this article, we will describe such systems, viewing them as candidates for a new paradigm, with their characteristics and their implications to our worldview and science.  

In the existing literature, complex systems are defined as those formed by many elements that correlate and interact with each other somehow. As a result of these correlations and interactions, these systems reveal behaviors and properties that are not obvious in their individual parts. There are numerous examples of complex systems, including biological systems, climate systems, and economic systems.  

The most important feature of complex systems is emergence, which can be deciphered from the below example. When someone moves into a new apartment, the first issue they face is how to decorate their place. Depending on what they have, they put pieces of furniture in certain places within the room and organize them according to their taste. For example, if they decorate a living room, they might put two couches against the walls in such a way that they sit perpendicular to each other. A rug might be laid out before them and a coffee table might be placed on it. Moreover, another table with a lampshade on it might be put in an empty place where the two couches connect. They might put a television stand so that it faces the couches and the café table. In addition, a dining table with a nice tablecloth on its top and six chairs around it might stay in the far corner. A vase with flowers might be put on the middle of the table. In this example, they picture a pattern that emerges in decorating the living room according to one person’s taste. Clearly, someone else could have organized the room differently with the same furniture and thereby another pattern might have emerged.

Let us consider a bit what the aforementioned example tells us. First, the character and the impression we get from the room depends intimately on how it is decorated. Changing the arrangement of furniture leads to the emergence of new patterns which might seem lovely to some people, boring to others. Although the impression might vary from person to person, everybody might agree on a professional’s take of the decoration. Second, the emergence of patterns in the organization of parts is not limited only to the decoration of rooms. It is obvious in many, many systems. For instance, Monet, Picasso, and Renoir made their masterpieces using different colors of oil paint and a canvas. With the same pieces, one can however paint figures with no clear meaning. By the same token, using letters in one language, Shakespeare, Goethe, and Dostoyevsky wrote their masterpieces. However, with the same letters, it is possible to write essays that do not say anything at all. In these examples, we see different patterns emerge by arranging the pieces in different plans.

Now let us ponder on the following question: What is the relationship among individual parts and the pattern that emerges when we arrange these parts in specific ways? In all the examples mentioned above, none of them seem to have a direct relationship with the emergent pattern. In the case of room decoration, just a couch or just a café table does not tell us what kind of living room there will be. In other cases, the lack of relationship is even more obvious. Twenty something letters do not possess any insight into Shakespeare’s Hamlet or Goethe’s Faust. Nor do oil paints have any hidden picture in them related to Monet’s Argeteuil or Renoir’s La Grenouillere. Then, it is clear that patterns emerge according to the knowledge, talent, vision, and plan of whomever is organizing them.

The above examples were chosen from daily life for the sake of simplicity. At this point, let us turn our focus to the scientific aspects of pattern emergent systems due to the interaction of parts. This emergence phenomenon is universal and one of the characteristics of the complex systems that are formed by many parts with different features and characters. Therein, new features that are not obvious in individual parts arise as a result of their interaction. There are numerous examples of such systems such as the internet, stock market, economic systems, and biological systems [2]. As you might see, they interact extensively with our daily lives; therefore, understanding them offers unlimited benefits to us. Furthermore, they challenge us in both scientific and philosophical manners. Let us see how so in the below paragraphs.

The first way we’re challenged are the scientific aspects. Let us see emergence in the following example. Quarks are the most fundamental particles that are experimentally verified in the universe. That is, they cannot break into parts. Their typical features are mass and electric charge. When they come together in certain combinations, they form protons and neutrons that form the nucleus of an atom. Atoms also have electrons around the nucleus; these electrons have different energy levels.

Up to this level, we do not see much difference in behavior emerging from the arrangements of parts aside from some physical details. When atoms come together, they connect by chemical bonds and thereby form molecules and matter. At this level, the chemical bond is a new feature. If we had a single atom, we would not know chemical bonds were possible. Then, a single atom does not have this feature: a chemical bond.

As an example, two hydrogen atoms and one-oxygen atom bonded together form the water molecule. By itself, this molecule does not display very peculiar phenomena. However, when many of them come together, they can be ice, liquid, or vapor depending on the environment’s conditions, e.g. temperature and pressure. Again, these behaviors are completely new and do not appear in a single water molecule.

Another aspect is this. Up to a few molecule levels, quantum mechanics describes what’s going on. However, when the system size reaches a certain level, usually a few centimeters to meters, we use Newton’s laws to describe the system. According to a Noble laureate in Physics, Robert L. Laughlin [3], Newton’s Laws are emergent properties that arise in a sufficiently large scale as a result of the interaction of smaller entities described in the Quantum regime. This point of view differs from the classical reductionist approach in which a complex system might be understood by studying the simpler parts that constitute the system. This is quite opposite to what is described above. Laughlin, as many others, sees the reductionist approach limiting our understanding of complex systems [3].

We would also like to look at examples from biological systems. In contrast to the above example, in this case, there are numerous types of molecules. Additionally, most of them function in the water; thus water is part of the system. Biological molecules are organic and made of a few types of atoms – nitrogen, oxygen, hydrogen, and carbon. In addition, a few ions, such as zinc, sodium, and so on, play crucial roles.

Simple biological molecules are DNA, RNA, and proteins. Even they are made of thousands of atoms. At this point, it is clear that a special arrangement of this many atoms yield very complex molecules. If we go one level up and investigate a system of DNAs, RNAs, and proteins, we will reach the basic unit of living organisms: cells. In a simple bacterial cell, there exist a few million proteins that float in the water. In more complex organisms, this number significantly increases and the cell becomes more complex. However, what emerges keeps us in awe: life. A single DNA or single protein does not have this feature. However, when they are together, they act in harmony, produce, grow, exhume energy, and die. These are very distinct features that do not exist at the level of a single molecule. Biology does not have quantitative theories, such as physics or chemistry. The approach to study such systems is usually to modify a certain gene and to check its effect on the phenotype. Then, this approach can be considered reductionist.

In the above examples, we saw how emergence occurred. Now, let us see how science studies complex systems. There are two approaches to study such systems. One is top-down, or the reductionist approach; the other is a bottom-up, or holistic approach. So far, the former has reigned over science. This is due to various reasons. The most important is that breaking the system into subsystems reduces the complexity. However, this approach is valid only if the system is the sum of its parts. In contrast, in emergent systems, as Aristotle said, “the whole is more than the sum of its parts” [4]. Then, you might expect that the holistic approach might be more useful than reductionism.

However, there are other factors challenging this approach. One is the lack of tools or insufficient availability to study the systems. For example, with the advances in today’s technology, we can simulate and do the necessary calculations to dock a small molecule to a protein structure in a few days using the methods of Molecular Dynamics. In this simulation, there are a few thousand atoms. However, in a cell, there are roughly 10¹⁴ atoms and the simulation of such an environment would take forever.

The philosophical aspects of complex systems are not limited to how we study such systems or the emergence of physical laws. One important question is this: how do parts with no relationship to the emergent pattern know which pattern they will give rise to? In the science community, this question causes a big debate due to its outcomes. As we see in the decoration example, or the painting and literature examples, emergent patterns do depend on how they are arranged and thereby who arranges them. Can we say that many letters come together randomly to form words and later sentences? Are those sentences arranged randomly to give birth to Hamlet? If you adopt these questions to the cellular, then you must ask how life emerges by the arrangement of zillions of atoms. At this point, we are forced to agree with both Aristotle that, “the whole is more than the sum of its parts” [4] and Paul W. Anderson, Noble Laureate in physics: “More is different” [5].

Murat Erdin is a freelance writer living in Massachusetts.

References

1. Kuhn, Thomas. 1962. The Structure of Scientific Revolutions, The University of Chicago Press.
2. Waldrop, M. Mitchell. 1992. Complexity: The Emerging Science at the Edge of Order and Chaos, Simon & Schuster.
3. Laughlin, Robert. 2006. A Different Universe: Reinventing Physics from the Bottom Down, Basic Books.
4. Metaphysics, Aristotle.
5. Anderson, P.W. 1972. “More is different,” Science Vol. 177, No. 4047, 393-96.

It was only a decade ago that a phenomenon called the “Internet” came along and changed the way we communicated, did business and conducted our lives. Now, computer technology has become an essential and significant part of our daily lives. But how did it all start and where is it heading?

I entered the world of computers at an early age. I had an Atari 800 XL, the third version of the Atari introduced in 1983, and I was doing some basic programming. The computer contained a full 64K of memory, 1.8 MHz processing power (CPU), and looked like a bulky keyboard. I enjoyed spending a lot of time with games and programming; however I felt very limited with its capabilities. After more than 20 years, from time to time I still feel the same about my 2.8 GHz eight-core desktop computer with 8 GB of memory. While the computers are getting faster and more powerful, our need for computing power is also increasing just to complete our daily tasks at home and work. I always wondered how it all started and where we are heading with computer technology.

Over forty years ago, Gordon Moore, Intel Co-founder, predicted the number of transistors incorporated in a chip to double every 24 months. This is popularly known as Moore’s law, and used countless times by futurists [1] and science fiction writers. For the last half century, computer’s functionality and performance increased in line with Moore’s law, while costs are decreasing. However, fundamental barriers in semiconductor technology are emerging including the power needs and limits of manufacturing in atomic dimensions. Computer industry is already working on technologies to keep Moore’s Law alive.

Intel is already experimenting with 3D transistors that are smaller, faster and more energy efficient using a 22nm (nanometer, 10-12 m) manufacturing process compared to today’s 32nm systems. This will be a significant step forward to build more transistors onto silicon chips. Another approach will be by replacing the silicone in transistors. In 2010, IBM showcased a graphene transistor running at 100 GHz, with a potential of up to 1000 GHz. A graphene layer is only one atom thick with a honeycomb-like structure of carbon atoms. The graphene has unique electrical, optical, mechanical and thermal properties with promising applications in many industries.

In 1971, a theoretical prediction was made for the missing link in electronics, memristor, a fourth element to supplement resistor, capacitor and inductor, which form the basis of today’s electronic devices. HP’s demonstration in 2010 shows a resistor with memory that remembers the electric voltage applied even when the power is turned off. Requiring very little energy to store information promises to run ten times more power efficient and ten times faster than current counterparts.

In 1994, Leonard Adelman [2] proposed DNA computing to solve the famous, “shortest path problem”. Since then, many approaches have been made to utilize the properties of DNA for computing. In 2010, researchers at California Institute of Technology demonstrated a DNA computer, most advanced to date, which can calculate square roots. This approach could be put in use inside living organisms, and perform vital tasks such as disease detection. The promise of DNA computers depends on the parallel processing capabilities of DNA molecules that can try many possibilities at once with low power requirements [3]. Further advancements in DNA based computers in the coming decades will bring faster and low-powered computers to our daily lives.

In 1981, the famous physicist Richard Feynman speculated the possibility of computers obeying quantum mechanical laws that might best simulate the real-world quantum systems. This is a big challenge even for today’s fastest supercomputers. Since then, researchers are pacing towards building quantum computers that rely on quantum mechanics to conduct operations. Quantum computers can use properties like entanglement [4] and qubits. In entanglement, particles behave identically independent of the distance between them, and qubits act as both memory and state of the entanglement. Shor’s Algorithm, formulated by Peter Shor in 1994 for prime factorization is a powerful example of quantum computing that allows breaking encryption algorithms like RSA encryption more effectively and quickly than today’s super computers. Quantum computers can perform at much higher speeds than traditional computers, and are able to solve more complex problems. Recent developments in quantum computing such as quantum photonic chips [5], and first commercial quantum computer by D-Wave shows that we might be closer than we think to have our very own quantum computer in the coming decades.

While greater shift in computing might stem from the change in underlying technology in processing the information, computer form factors (desktop, laptop, tablet, phone, etc.) have a more direct effect in our daily use of computers. Human computer interaction changed significantly with the introduction of smartphones (e.g. iPhone, Android phones), and tablets (e.g. iPad), moving from keyboards and mouse as the primary input methods towards touch screens.

Today’s touch screens, although providing infinite ways of input structures available on their screens, lack tactile feedback when compared to keyboards. New keyboard designs with small screens on each key opens infinite customization of the input, but are still limited to initial design of the key (e.g. usually cubic). Recent developments in touchscreen designs enable users to feel clicks, vibrations and other tactile input by using “haptic technology”. Haptic technology takes advantage of the user’s sense of touch and provides feedback by applying forces, vibrations, or motions to the user. As seen in early prototypes, flexible screens and electronics will provide a more realistic feel for human computer interaction by shifting their forms to a specific shape (e.g. game pad, key, and wheel) in the coming decades.

Another level in human computer interaction even eliminates user’s touch. Apple introduced Siri, a smart virtual assistant, in 2011 as a part of their iOS operating system for iPhones and iPads. Siri is capable of analyzing user’s complex audio inputs to carry out many tasks including scheduling a meeting, creating a reminder, typing and sending SMS messages, and many other functions available in smart phones. Microsoft introduced Kinect in 2010, a motion-sensing device that enables users to control and interact with the game console using gestures and spoken commands. The Kinect interprets specific gestures by using an infrared projector and camera to track the movement of objects and individuals in three dimensions.

Samsung introduced a 46’’ transparent display using LCD technology in 2010, and demonstrated flexible displays in CES 2011. Transparent and flexible displays will easily find use in wearable electronics such as contact lenses and glasses. An obvious application of transparent display is Augmented Reality (AR) where information is displayed on top of real world images. While today’s smartphones and tablets allows augmented reality by combining information with the real-time video feed from the camera of the device, transparent display eliminates the need of using camera. Current AR technology includes head-mounted displays and virtual retinal displays for visualizing the information. It is widely applied in various areas including entertainment, advertising, game industry, navigation, education, military applications, and information sharing.

While having larger, transparent, and flexible displays in different forms, one direction in display technologies is to reduce the size or even eliminate the display through projection and holograms. Current trends in projectors include 3D projection, synchronization of multiple projections, and pico projectors. The world’s smallest glass lens (1mm x 1mm) introduced in 2011 will help minimize some of the problems of projectors such as size, power and heat, and improve their integration in smartphones and tablets.

Recent prototypes of holographic displays progressed significantly demonstrating 3D and full color animated images, since its first introduction at the MIT Media Lab 1989 [6]. While developments in 3D displays are promising, holography provides the best 3-D experience since it is closest to how we see our environment. A hologram uses an optical effect called “diffraction” to produce the light that would have come from an object, and makes the image of the object appear in front of the viewer. It is possible to view objects from different angles in holographic display by walking around them. Unlike other 3D display systems, holographic displays do not require special glasses for viewing and allows multiple viewers to experience the view from different angles at the same time. Future applications of holography can be implemented in health, entertainment and communication sectors, from 3D movies to telepresence applications.

All of the above examples and trends in computers deal with the computing as a product. Cloud computing can be defined as the delivery of computing as a service where shared resources, software, and information are provided over a network. Cloud computing describes a new delivery and consumption model that allows dynamic scalability and virtualization of resources. Users can dynamically upgrade the storage and computing power from virtualized resources on demand without hardware changes on the base system. Organizations can save from investing on expensive hardware, and human capital.

Many technologies from coming centuries are featured in science fiction books and movies such as Minority Report, Star Trek, and Star Wars. While some of them are already available to consumers, others might require decades to come. Motivation for the advancement in computer technologies usually stems from our needs and desires. At the same time, new technologies significantly impact consumer behavior and increase our dependence on new technologies. Our economy is structured such that all citizens have to consume more and more, even if that means disposing of perfectly good technological devices. Do we really need a new computer or phone every year? Most of us don’t.

Computer technologies are a significant part of our daily lives, and the line between the products and services is becoming thinner with the dependency on computers increasing in every aspect of our life. While improving the quality of our lives by making our daily tasks easier, computers and Internet technologies can affect us in different ways. It has already started to change how we read, write and even communicate with others. Many concerns are raised about the negative effects of the use of technology including Internet addiction, privacy, attention span, concentration, time consumption, anxiety, isolation, depression, digital security, communication disorder and various health issues. The challenge for us is to understand the benefits of the technology, have a balance in dependence and its use, and protect ourselves from its adverse effects.

Acknowledgment: This article is produced at Mergeous [7], an online article and project development service for authors and publishers dedicated to the advancement of technologies in the merging realms of science and religion.

References

1. Kaku, Michio. 2011. Physics of the Future: How Science Will Shape Human Destiny and Our Daily Lives by the Year 2100, Knopf Doubleday Publishing Group.

2. Demir, Halil I. 2011. Super Computers in a Cell, The Fountain, Issue 80, March – April.

3. Adleman, Leonard M. 1994. “Molecular Computation of Solutions to Combinatorial Problems,” Science, 266 (11), 1021–1024.

4. Demir, Halil I. 2011. Quantum Worlds from Entanglement to Telepathy, The Fountain, Issue 84, November – December.

5. Shadbolt, P. J. et al., Generating, manipulating and measuring entanglement and mixture with a reconfigurable photonic circuit, arXiv:1108.3309v1 [quant-ph].

6. Hilaire, P. St., S. A. Benton, M. Lucente, M. L. Jepsen, J. Kollin, H. Yoshikawa and J. Underkoffler. 1990. “Electronic display system for computational holography.”In Practical Holography IV, Proceedings of the SPIE, volume 1212-20, pp. 174-182, Bellingham, WA. 7. Mergeous, Online article and project development platform, http://www.mergeous.com