**4. The technology triad**

*Synthetic Biology - New Interdisciplinary Science*

**3. DNA is an information molecule**

in terms of algebra.

The language of information now pervades molecular biology—genes are linear sequences of bases (like letters of an alphabet) that carry information (like words) to produce proteins (like sentences). For the process of going from DNA sequences to proteins, we use words like "transcription" and "translation," and of passing genetic "information" from one generation to another. It is rather uncanny that molecular biology can be understood by ignoring chemistry and treating the DNA as a computer program (with enough input data included) in stored memory residing in a computer (the cellular machinery). It is this aspect that bioinformatics exploits. It is analogous to viewing Euclidean geometry not in terms of drawings but

In a sense, in the DNA sequences in our cells, written using an alphabet of only four letters, lies hidden the story of who we are and where we come from. For all we know, it might even tell us where we might be going. Albert Lehninger wrote:

*… living organisms are composed of lifeless molecules … that conform to all the laws of chemistry but interact with each other in accordance with another set of* 

It is this "molecular logic of the living state" that is yet to be completely understood, and therein may lie our ability to understand emotion, cognition, and intelligence. So, in a deep sense, the DNA is the master molecule of life. A marvelous thing about cells is that they are so designed that for many purposes one can totally ignore their chemistry and think just about their logic. The fact that one can get away with this is one of the most elegant aspects of molecular biology. The algorithmic side of molecular biology is bioinformatics, the study of information flows in living matter. Bioinformatics is about the development and application of algorithms and methods to turn biological data into knowledge of biological systems. Of fundamental interest is the organization and control of genes in the DNA sequence, the identification of transcriptional units in the DNA, the prediction of protein structure from sequence, and the analysis of molecular function. If there is mathematical logic in living things, then one naturally seeks to determine the formal mathematical system that governs life, that is, how information in the DNA is stored and used by the rest of the cell's

We already know that a DNA molecule—a genotype—is converted into a physical organism—a phenotype—by a very complex process, involving the manufacture of proteins, the replication of the DNA, the replication of cells, the gradual differentiation of cell types, and so on. This epigenetic process is guided by a set of enormously complex cycles of chemical reactions and feedback loops. By the time the full organism appears, there is no discernible similarity between the physical characteristics of the organism and its genotype. Yet molecular biologists attribute the physical structure of the organism to the information encoded in its DNA, and to that alone. This is because there is overwhelming experimental evidence that only DNA transmits hereditary properties. The genotype and the phenotype are isomorphic. However, this isomorphism is so complex that so far it has not been possible to divide the phenotype and genotype into parts, which can be mapped onto each other directly, unlike as, say, in the case of a music record and a record player where portions of a record's track can be easily mapped to specific musical notes [20]. One hopes that AI and QC together will enable us to find this complex mapping. It is all about information processing. By information we mean the precise determination of sequence, either of bases in the nucleic acid or of amino acid residues in the protein. We gain knowledge of biological systems when we can interpret information in some "meaningful" way

*principles—the molecular logic of the living state. [19]*

machinery to do the myriad of things that it does.

**16**

The time has come for synthetic biology, AI, and QC to join hands and form a purposeful, integrated discipline to further explore the secrets of life, create new life, and find harmonious ways by which *Homo sapiens* can speciate. The main responsibility will fall on the shoulders of the millennials. The technology triad (CRISPR, AI, and QC) share some important properties, the ability to create, share, process, and communicate information in digital form. This means they can be supported and integrated with the full power of mathematics and physics. As Richard Feynman notes:

*Mathematics is a language plus reasoning; it is like a language plus logic. Mathematics is a tool for reasoning. … [I]t is impossible to explain honestly the beauties of the laws of nature in a way that people can feel, without their having some deep understanding of mathematics. [23]*

Mathematics is the *lingua franca* of the physicists because a formal mathematical statement to be of any value is either true or false; it cannot be true to some and false to others. This is the reason why knowledge based on any axiomatic system, that is, a consistent system in which every valid statement or query has a "yes" or "no" answer, can be arithmetized (i.e., translated into arithmetical statements), encoded in a binary string, and processed in a digital computer. Mathematics is the language that binds men and machine together in a rational dialog. In short, axiomatic systems permit men and machines to mutually communicate without ambiguity or confusion. This is the foundation on which artificial intelligence (AI) rests. It is why Pierre Simon Marquis de Laplace did not even acknowledge God as the creator of the Universe in his mathematical magnum opus on celestial mechanics [24]. He famously told Napoleon Bonaparte, "I had no need of that hypothesis" [25].

Creating and advancing rational knowledge, *inter alia*, requires an ability to communicate thoughts concisely, precisely, and accurately apart from refining knowledge by trial and error, that is, by making our conjectures fitter and fitter for survival. Benjamin Lee Whorf (1897–1941) said, "Language shapes the way we think, and determines what we can think about." And Ludwig Wittgenstein (1889–1951) said, "The limits of my language mean the limits of my world." Mathematics provides fewer limitations than any other language known to *Homo sapiens*. The power of mathematics lies in its ability to extract unity from diversity by abstraction, that is, by eliminating unnecessary context; it helps in discovering group properties (abstract or otherwise) common to all members of the group, for example, the DNA of a species.

Both AI and QC are inseparable from mathematics; they are powerful means of processing and interpreting information (e.g., in the DNA) as well as aiding in inventing novel DNA for specific purposes. Both support and are supported by 3D printing that began by making plastic widgets, but now make guns, houses, prosthetic limbs, vehicle parts, etc. from inanimate matter. The day is not far off when it will advance to printing living, breathing, bio-organs, such as hearts [26] and kidneys, using nanotechnology, computer-aided engineering, and inanimate biodegradable or biocompatible materials and chemicals to build stem cells. Replicating and growing cells, say, in petri dishes is well established, and such cells are already in use as bioink in bioprinters. 3D printing offers the possibility of printing an entire organ, along with a system of arteries, capillaries, and veins that can support it [27, 28]. A major issue in developing this technology is to make it immune-system friendly, since the body may reject organs or cells thus produced, something that can occur even when tissue from one area of the body is put into another.

#### **4.1 CRISPR technology connects synthetic biology with information technology**

CRISPR technology has enabled a simple and affordable method of manipulating and editing DNA that has radically changed the ambitions of synthetic biologists. The technology promises to revolutionize how *Homo sapiens* may deal with the world's biggest problems, for example, finding cures for cancer, blindness, and Alzheimer's disease, improving food and eliminating food shortages, fulfilling organ transplant needs, and producing fuel and manufacturing chemicals. Biotechnologists are racing to develop the most efficient, precise, versatile, affordable, and commercially viable genome-editing tools possible. This will be a long and exciting race that may eventually lead to the *Homo sapiens* creating a super species that far exceeds them in the evolutionary path in a controlled manner.

CRISPR is a series of short repeating DNA sequences with "spacers" separating them. The CRISPR technology harnesses an ancient bacteria-based defense system. Bacteria use these genetic sequences to "remember" the viruses that have attacked them by the simple mechanism of incorporating the virus' DNA into their own bacterial genome. The viral DNA thus resides as spacers in the CRISPR sequence as identification tags the bacteria can use to mount an attack if the virus attacks again. Accompanying the CRISPR are locally stationed genes called Cas (**C**rispr-**as**sociated) genes. Once activated, these genes produce enzymes that act as "molecular scissors" that can cut into DNA with specificity. The significance is that in subsequent virus attacks, the bacteria can recall the virus signature and send RNA and Cas to locate and destroy the virus. Among the Cas enzymes derived from bacteria, Cas9 is the best-known molecular scissors enzyme for cutting animal and human DNA. Although the CRISPR sequence was first discovered in 1987, its function was discovered only in 2012.

The ability to cut DNA allows one to either knock out, say, an unwanted diseasecausing gene, or splice a "fixed" version of a gene into the DNA. This is analogous to the "Find & Replace" function in text editing software. Indeed, CRISPR technology has advanced so rapidly beyond the Find & Replace function that by December 2017, the Salk Institute had designed a version of the CRISPR-Cas9 system that could switch on or off a targeted gene without even editing the gene. The basic ingredients of gene editing are (1) a piece of RNA, called the guide RNA, that locates the targeted gene, (2) the scissors (the CRISPR-associated protein 9), and (3) the desired DNA segment for insertion after the break. Once the guide RNA locates the targeted gene, Cas9 makes a double-stranded break in the DNA carrying the targeted gene and replaces it with the desired DNA segment. A quick tutorial on CRISPR is available at [29].

**19**

the positive side,

*chaos. [31]*

links to other genetics resources." http://omim.org/about

*Synthetic Biology, Artificial Intelligence, and Quantum Computing*

toms, and a bibliography of thousands of genetic conditions.4

*behave when we don't know what to do. [30]*

*The true test of intelligence is not how much we know how to do, but how we* 

*There is a paradox in the growth of scientific knowledge. As information accumulates in ever more intimidating quantities, disconnected facts and impenetrable mysteries give way to rational explanations, and simplicity emerges from* 

It is this scientific knowledge ferreted out by a few geniuses among the *Homo sapiens*, which has allowed the species to extend their life span and improve their lifestyle by not just adapting to an environment but also by aiding the environment to adapt to humans. Along the way, Claude Shannon provided a mathematical theory that highlighted an important aspect of how data can be condensed and communicated efficiently in binary bitstreams. This was an important

<sup>4</sup> "OMIM contain information on all known mendelian disorders and over 15,000 genes. OMIM focuses on the relationship between phenotype and genotype. It is updated daily, and the entries contain copious

This behavior is a product of the brain-mind system an individual is born with and the environment it finds itself in. From conception to death, behavior and intelligence evolve through intimate interaction between the individual and the environment where the individual essentially tries to coexist with the environment by exploring networking strategies, *inter alia*, based on its information gathering and processing abilities (see Section 5.2). In the past few decades, in an ongoing process, the *Homo sapiens* using technology they have intelligently developed have already acquired massive amounts of information and placed it in easily accessible public repositories along with some sophisticated automated information processing services. This has happened unexpectedly, suddenly, and on a massive scale at an exponential rate in multiple disciplines (including molecular biology) due to breakthroughs in communication and computing technologies engineered by an exceptionally intelligent group of *Homo sapiens*. This development is well on its way to dwarfing the intellectual abilities of almost all *Homo sapiens*. In comparison, individual human brain capacity to understand, assimilate, create, and deal with knowledge appears pathetic and along with it, its ability to find gainful employment in the future. Machines are rapidly learning to create and deal with knowledge. On

CRISPR-based therapies are still nascent. As expected, single-gene disorders are among the best understood because of their simple inheritance patterns (recessive or dominant) and relatively simple genetic etiology (cause). Such disorders include cystic fibrosis, hemochromatosis, Tay-Sachs, and sickle cell anemia. For example, cure for sickle cell disease (an inherited form of anemia in which distorted red blood cells—rigid, sticky, and shaped like sickles—are present in such numbers as to prevent adequate oxygen supply throughout the body) has gained prominence because it is related to an abnormal hemoglobin molecule, which comes from a wellunderstood genetic mutation. Hence efforts are concentrated on creating therapeutic strategies for fixing the mutated gene. Online Mendelian Inheritance in Man® (OMIM®) provides an Online Catalog of Human Genes and Genetic Disorders, a comprehensive database provides information about the etiology, clinical symp-

*DOI: http://dx.doi.org/10.5772/intechopen.83434*

**4.2 Artificial intelligence (AI)**

*Synthetic Biology, Artificial Intelligence, and Quantum Computing DOI: http://dx.doi.org/10.5772/intechopen.83434*

CRISPR-based therapies are still nascent. As expected, single-gene disorders are among the best understood because of their simple inheritance patterns (recessive or dominant) and relatively simple genetic etiology (cause). Such disorders include cystic fibrosis, hemochromatosis, Tay-Sachs, and sickle cell anemia. For example, cure for sickle cell disease (an inherited form of anemia in which distorted red blood cells—rigid, sticky, and shaped like sickles—are present in such numbers as to prevent adequate oxygen supply throughout the body) has gained prominence because it is related to an abnormal hemoglobin molecule, which comes from a wellunderstood genetic mutation. Hence efforts are concentrated on creating therapeutic strategies for fixing the mutated gene. Online Mendelian Inheritance in Man® (OMIM®) provides an Online Catalog of Human Genes and Genetic Disorders, a comprehensive database provides information about the etiology, clinical symptoms, and a bibliography of thousands of genetic conditions.4

### **4.2 Artificial intelligence (AI)**

*Synthetic Biology - New Interdisciplinary Science*

Both AI and QC are inseparable from mathematics; they are powerful means of processing and interpreting information (e.g., in the DNA) as well as aiding in inventing novel DNA for specific purposes. Both support and are supported by 3D printing that began by making plastic widgets, but now make guns, houses, prosthetic limbs, vehicle parts, etc. from inanimate matter. The day is not far off when it will advance to printing living, breathing, bio-organs, such as hearts [26] and kidneys, using nanotechnology, computer-aided engineering, and inanimate biodegradable or biocompatible materials and chemicals to build stem cells. Replicating and growing cells, say, in petri dishes is well established, and such cells are already in use as bioink in bioprinters. 3D printing offers the possibility of printing an entire organ, along with a system of arteries, capillaries, and veins that can support it [27, 28]. A major issue in developing this technology is to make it immune-system friendly, since the body may reject organs or cells thus produced, something that

can occur even when tissue from one area of the body is put into another.

that far exceeds them in the evolutionary path in a controlled manner.

**4.1 CRISPR technology connects synthetic biology with information technology**

CRISPR technology has enabled a simple and affordable method of manipulating and editing DNA that has radically changed the ambitions of synthetic biologists. The technology promises to revolutionize how *Homo sapiens* may deal with the world's biggest problems, for example, finding cures for cancer, blindness, and Alzheimer's disease, improving food and eliminating food shortages, fulfilling organ transplant needs, and producing fuel and manufacturing chemicals. Biotechnologists are racing to develop the most efficient, precise, versatile, affordable, and commercially viable genome-editing tools possible. This will be a long and exciting race that may eventually lead to the *Homo sapiens* creating a super species

CRISPR is a series of short repeating DNA sequences with "spacers" separating them. The CRISPR technology harnesses an ancient bacteria-based defense system. Bacteria use these genetic sequences to "remember" the viruses that have attacked them by the simple mechanism of incorporating the virus' DNA into their own bacterial genome. The viral DNA thus resides as spacers in the CRISPR sequence as identification tags the bacteria can use to mount an attack if the virus attacks again. Accompanying the CRISPR are locally stationed genes called Cas (**C**rispr-**as**sociated) genes. Once activated, these genes produce enzymes that act as "molecular scissors" that can cut into DNA with specificity. The significance is that in subsequent virus attacks, the bacteria can recall the virus signature and send RNA and Cas to locate and destroy the virus. Among the Cas enzymes derived from bacteria, Cas9 is the best-known molecular scissors enzyme for cutting animal and human DNA. Although the CRISPR sequence was first discovered in 1987, its func-

The ability to cut DNA allows one to either knock out, say, an unwanted diseasecausing gene, or splice a "fixed" version of a gene into the DNA. This is analogous to the "Find & Replace" function in text editing software. Indeed, CRISPR technology has advanced so rapidly beyond the Find & Replace function that by December 2017, the Salk Institute had designed a version of the CRISPR-Cas9 system that could switch on or off a targeted gene without even editing the gene. The basic ingredients of gene editing are (1) a piece of RNA, called the guide RNA, that locates the targeted gene, (2) the scissors (the CRISPR-associated protein 9), and (3) the desired DNA segment for insertion after the break. Once the guide RNA locates the targeted gene, Cas9 makes a double-stranded break in the DNA carrying the targeted gene and replaces it with the desired DNA segment. A quick tutorial on

**18**

tion was discovered only in 2012.

CRISPR is available at [29].

*The true test of intelligence is not how much we know how to do, but how we behave when we don't know what to do. [30]*

This behavior is a product of the brain-mind system an individual is born with and the environment it finds itself in. From conception to death, behavior and intelligence evolve through intimate interaction between the individual and the environment where the individual essentially tries to coexist with the environment by exploring networking strategies, *inter alia*, based on its information gathering and processing abilities (see Section 5.2). In the past few decades, in an ongoing process, the *Homo sapiens* using technology they have intelligently developed have already acquired massive amounts of information and placed it in easily accessible public repositories along with some sophisticated automated information processing services. This has happened unexpectedly, suddenly, and on a massive scale at an exponential rate in multiple disciplines (including molecular biology) due to breakthroughs in communication and computing technologies engineered by an exceptionally intelligent group of *Homo sapiens*. This development is well on its way to dwarfing the intellectual abilities of almost all *Homo sapiens*. In comparison, individual human brain capacity to understand, assimilate, create, and deal with knowledge appears pathetic and along with it, its ability to find gainful employment in the future. Machines are rapidly learning to create and deal with knowledge. On the positive side,

*There is a paradox in the growth of scientific knowledge. As information accumulates in ever more intimidating quantities, disconnected facts and impenetrable mysteries give way to rational explanations, and simplicity emerges from chaos. [31]*

It is this scientific knowledge ferreted out by a few geniuses among the *Homo sapiens*, which has allowed the species to extend their life span and improve their lifestyle by not just adapting to an environment but also by aiding the environment to adapt to humans. Along the way, Claude Shannon provided a mathematical theory that highlighted an important aspect of how data can be condensed and communicated efficiently in binary bitstreams. This was an important

<sup>4</sup> "OMIM contain information on all known mendelian disorders and over 15,000 genes. OMIM focuses on the relationship between phenotype and genotype. It is updated daily, and the entries contain copious links to other genetics resources." http://omim.org/about

step in handling data by finding structure in data to reduce redundancy in data representation [32].

Big data revolution, development and deployment of wearable medical devices, and mobile health applications have provided new powerful tools to the biomedical community for applying AI and machine learning algorithms to vast amount of data. Its impact in predictive analytics, precision medicine, virtual diagnosis, patient monitoring, and drug discovery and delivery is already being felt. More powerful advances are anticipated in the near future. Even at this early stage, AI excels even human experts in certain well but narrowly defined tasks. AI is at a stage where basic building blocks are being built. Soon we will learn to network these blocks and build increasingly powerful systems and subsystems that will solve increasingly complex problems and even create new knowledge. We already have a glimpse of it in Alphabet's AlphaGo Zero's ability to learn complex decision-making from scratch [33, 34]. "Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play. In doing so, it quickly surpassed human level of play and defeated the previously published champion-defeating version of AlphaGo by 100 games to 0" [34]. It acquired this ability within 40 days of self-training in an essentially iterative manner. The key here is the iterative strategy it used. Indeed, *Homo sapiens* too acquire knowledge iteratively but slowly over years and generations, collaboratively across space and time with other *Homo sapiens*, by making conjectures and refutations. It is rather uncanny that the essence of the process and its unusual power is mathematically captured by the Mandelbrot set in fractal geometry (see Section 5.3).

Notwithstanding AlphaGo's success, many real-life problems are still far too difficult not just for current AI systems but also for the vast-vast majority of *Homo sapiens*. The competition is really between two classes of geniuses: *Homo sapiens* who create *ab initio* knowledge and *Homo sapiens* who develop AI. Eventually, the latter is expected to win even if they must create an artificial brain using synthetic biology and place it in a humanoid! The task is enormously complex but not out-ofreach, in principle. What is needed is the ability to automate the task of observing and collecting data about the world and about us, create categories, data structures, and algorithms that would enable the collected data to be condensed into a computer program that can calculate the observations. This necessarily means that the size of the computer program (say, as represented by a binary string) must be as compact as possible (an index of the AI system's intelligence) compared to the collected data (also represented by a binary string). Till this is accomplished, the collected data would remain incomprehensible, that is, algorithmically random, theory-less, unstructured, and irreducible [35]. This is what *Homo sapiens* in the genius class devote themselves to. As Oren Etzioni notes, machine learning is still 99% human work:

*The equation for AI success is to take a set of categories (for example, cats and dogs) and an enormous amount of data (that is labeled as to whether it is a cat or a dog), and then feed those two inputs through an algorithm. That produces the models that do the work for us. All three of those elements—categories, data, algorithm—are created through manual labor. [36]*

The solution to eliminating manual labor may well be the creation of an artificial brain using synthetic biology. For the present, AI serves mainly by "augmenting human intelligence". But then automation too had begun by augmenting brawn (muscle) power to eventually become the superbrawn power during the industrial

**21**

(UTM) [12].

*Synthetic Biology, Artificial Intelligence, and Quantum Computing*

**4.3 Quantum computing will power synthetic biology and AI**

revolution. It only required the *Homo sapiens* to intelligently harness and control steam by first connecting water, heat, and work and then creating the thermodynamics, the science that would allow machines to make human brawn power look insignificant. Today's augmented intelligence appears destined to become superintelligence. We have learnt to harness and control reasoning by first connecting logic, axiomatic systems and theorem proving. We are now advancing rapidly into understanding information theory so that quantum computers can become information engines to do intelligent work. It is interesting that the concept of entropy appears fundamental both in thermodynamics and information theory. Both are offsprings of rational thought in physics, and both are intimately related.5

Quantum mechanics deals with the world inhabited by photons, electrons, protons, atoms, molecules, etc. and how they interact among themselves to create larger matter entities. It is an incredibly mysterious world understood only in the language of advanced mathematics. This is the part of physics that tells us how atoms congregate into molecules by adjusting the electrons they carry into configurations that we call chemical bonds, how strong or weak those bonds will be or whether they will bond at all, what a congregation's physical and chemical properties will be. It has led to many technical innovations and many more are expected, for example, in synthetic biology. The success of quantum mechanics in using mathematical abstractions is such that to a lay person it appears mystical, which even religious mystics cannot understand! Its remarkable success comes even though we still do not know what is meant by measurement in the quantum world and how the measurement process captures the information it outputs and why it releases information in a randomized way. Yet its success is undeniably visible:

*Quantum mechanics is an immensely successful theory. Not only have all its predictions been experimentally confirmed to an unprecedented level of accuracy, allowing for a detailed understanding of the atomic and subatomic aspects of matter; the theory also lies at the heart of many of the technological advances shaping modern society – not least the transistor and therefore all of the electronic equipment that* 

Understanding quantum mechanics is out of reach except for a few thousand people in the world at any given time! This should immediately alert us to the fact that human intelligence needed to cope with AI-QC combination in the future will be very high and successor species of the *Homo sapiens* must evolve in the direction of better and smarter brains rather than any other physical trait. Computation, comprehension, and cognition are all a part of the brain's activity, and we may assume that a sharper brain will come with a sharper mind. And we may further assume that comprehension and cognition are driven by computation in addition to using intuition, serendipity, flashes of inspiration, and inputs from the environment, etc. The keys are computation, problem-solving algorithms, and rational decision-making processes. These can be simulated by a classical computer, which itself has an abstract mathematical description we call the universal Turing machine

Computing technology has now advanced to a stage where quantum computers can do everything that a UTM can do, and some more. A quantum computer's phenomenal computing power comes from the extraordinary laws of quantum

<sup>5</sup> This we know from the explanation of the Maxwell's demon paradox in thermodynamics. See, e.g., [37].

*DOI: http://dx.doi.org/10.5772/intechopen.83434*

*surrounds us. [38, 39]*

*Synthetic Biology, Artificial Intelligence, and Quantum Computing DOI: http://dx.doi.org/10.5772/intechopen.83434*

*Synthetic Biology - New Interdisciplinary Science*

representation [32].

geometry (see Section 5.3).

99% human work:

step in handling data by finding structure in data to reduce redundancy in data

Notwithstanding AlphaGo's success, many real-life problems are still far too difficult not just for current AI systems but also for the vast-vast majority of *Homo sapiens*. The competition is really between two classes of geniuses: *Homo sapiens* who create *ab initio* knowledge and *Homo sapiens* who develop AI. Eventually, the latter is expected to win even if they must create an artificial brain using synthetic biology and place it in a humanoid! The task is enormously complex but not out-ofreach, in principle. What is needed is the ability to automate the task of observing and collecting data about the world and about us, create categories, data structures, and algorithms that would enable the collected data to be condensed into a computer program that can calculate the observations. This necessarily means that the size of the computer program (say, as represented by a binary string) must be as compact as possible (an index of the AI system's intelligence) compared to the collected data (also represented by a binary string). Till this is accomplished, the collected data would remain incomprehensible, that is, algorithmically random, theory-less, unstructured, and irreducible [35]. This is what *Homo sapiens* in the genius class devote themselves to. As Oren Etzioni notes, machine learning is still

*The equation for AI success is to take a set of categories (for example, cats and dogs) and an enormous amount of data (that is labeled as to whether it is a cat or a dog), and then feed those two inputs through an algorithm. That produces the models that do the work for us. All three of those elements—categories, data,* 

The solution to eliminating manual labor may well be the creation of an artificial brain using synthetic biology. For the present, AI serves mainly by "augmenting human intelligence". But then automation too had begun by augmenting brawn (muscle) power to eventually become the superbrawn power during the industrial

*algorithm—are created through manual labor. [36]*

Big data revolution, development and deployment of wearable medical devices, and mobile health applications have provided new powerful tools to the biomedical community for applying AI and machine learning algorithms to vast amount of data. Its impact in predictive analytics, precision medicine, virtual diagnosis, patient monitoring, and drug discovery and delivery is already being felt. More powerful advances are anticipated in the near future. Even at this early stage, AI excels even human experts in certain well but narrowly defined tasks. AI is at a stage where basic building blocks are being built. Soon we will learn to network these blocks and build increasingly powerful systems and subsystems that will solve increasingly complex problems and even create new knowledge. We already have a glimpse of it in Alphabet's AlphaGo Zero's ability to learn complex decision-making from scratch [33, 34]. "Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play. In doing so, it quickly surpassed human level of play and defeated the previously published champion-defeating version of AlphaGo by 100 games to 0" [34]. It acquired this ability within 40 days of self-training in an essentially iterative manner. The key here is the iterative strategy it used. Indeed, *Homo sapiens* too acquire knowledge iteratively but slowly over years and generations, collaboratively across space and time with other *Homo sapiens*, by making conjectures and refutations. It is rather uncanny that the essence of the process and its unusual power is mathematically captured by the Mandelbrot set in fractal

**20**

revolution. It only required the *Homo sapiens* to intelligently harness and control steam by first connecting water, heat, and work and then creating the thermodynamics, the science that would allow machines to make human brawn power look insignificant. Today's augmented intelligence appears destined to become superintelligence. We have learnt to harness and control reasoning by first connecting logic, axiomatic systems and theorem proving. We are now advancing rapidly into understanding information theory so that quantum computers can become information engines to do intelligent work. It is interesting that the concept of entropy appears fundamental both in thermodynamics and information theory. Both are offsprings of rational thought in physics, and both are intimately related.5

### **4.3 Quantum computing will power synthetic biology and AI**

Quantum mechanics deals with the world inhabited by photons, electrons, protons, atoms, molecules, etc. and how they interact among themselves to create larger matter entities. It is an incredibly mysterious world understood only in the language of advanced mathematics. This is the part of physics that tells us how atoms congregate into molecules by adjusting the electrons they carry into configurations that we call chemical bonds, how strong or weak those bonds will be or whether they will bond at all, what a congregation's physical and chemical properties will be. It has led to many technical innovations and many more are expected, for example, in synthetic biology. The success of quantum mechanics in using mathematical abstractions is such that to a lay person it appears mystical, which even religious mystics cannot understand! Its remarkable success comes even though we still do not know what is meant by measurement in the quantum world and how the measurement process captures the information it outputs and why it releases information in a randomized way. Yet its success is undeniably visible:

*Quantum mechanics is an immensely successful theory. Not only have all its predictions been experimentally confirmed to an unprecedented level of accuracy, allowing for a detailed understanding of the atomic and subatomic aspects of matter; the theory also lies at the heart of many of the technological advances shaping modern society – not least the transistor and therefore all of the electronic equipment that surrounds us. [38, 39]*

Understanding quantum mechanics is out of reach except for a few thousand people in the world at any given time! This should immediately alert us to the fact that human intelligence needed to cope with AI-QC combination in the future will be very high and successor species of the *Homo sapiens* must evolve in the direction of better and smarter brains rather than any other physical trait. Computation, comprehension, and cognition are all a part of the brain's activity, and we may assume that a sharper brain will come with a sharper mind. And we may further assume that comprehension and cognition are driven by computation in addition to using intuition, serendipity, flashes of inspiration, and inputs from the environment, etc. The keys are computation, problem-solving algorithms, and rational decision-making processes. These can be simulated by a classical computer, which itself has an abstract mathematical description we call the universal Turing machine (UTM) [12].

Computing technology has now advanced to a stage where quantum computers can do everything that a UTM can do, and some more. A quantum computer's phenomenal computing power comes from the extraordinary laws of quantum

<sup>5</sup> This we know from the explanation of the Maxwell's demon paradox in thermodynamics. See, e.g., [37].

mechanics that include such esoteric concepts as superposition of quantum states, entanglement ("spooky action at a distance"), and tunneling through insulating walls, which, though highly counterintuitive, play extremely useful roles in understanding Nature at subatomic levels. However, it is not clear if these concepts can be ignored in biology and living processes in the way they are ignored in the design of cars and airplanes. May be not because there are areas in biology where quantum effects have been found, for example, in protein-pigment (or ligand) complex systems [40]. Thus, while the role of quantum mechanics is clear in quantum computing and hence in advancing both AI and synthetic biology research, it is not yet known if in the design of DNA, knowledge of quantum mechanics is required or that natural selection favors quantum-optimized processes. Essentially, we do not know if any cellular DNA maintains or can maintain sustained entangled quantum states between different parts of the DNA (even if it involves only atoms in a nucleotide). But we cannot rule out the possibility that sporadic random entanglements do occur that result in biological mutations or that researchers will not be able to achieve it in the laboratory and find novel uses for it in synthetic biology [41]. For example, in principle, it is possible to design molecular quantum computers, insert them in cells that can observe cellular activity, and activate select chemical pathways in the cell in a programmed manner. There is increasing speculation that some brain activity, for example, cognition, may be quantum mechanical [42].
