Origin of Living Systems

TRANSCRIPT: Origin of Living Systems. University of Houston: Clear Lake – July 23, 1993 / (121)

[unclear] 

[2:21]

Host:  We are deeply honored to have Dr. Richard Thompson with us this evening. When first I was approached by several people from the local group that were organizing a series of lectures at the temple recently, I was impressed with two basic facts. One was that here is a person with a PhD in mathematics from Cornell who has done extensive work in quantum physics, who has also worked in biophysics, mathematical modeling of biological systems, speaking on a subject which is so complex and so controversial, at the same time, so important, so vital for us to understand.

Dr. Richard Thompson received his PhD in mathematics from Cornell University in 1974. And later he wrote extensively in the field of mathematical biology and biophysics. And some of his work was so important and his ideas so original, that one of the Nobel prize winning physics professors, Brian Josephson, invited him to work with him at Cambridge. Dr. Thompson's work at Cambridge, as well as other universities, also actually at the Bhaktivedanta Institute, has been acclaimed as well as the original work. He has presented clear models as the basis of his research that sometimes the mechanistic science cannot answer. One of the interesting things that we, as scientists, face in the scientific community is: How do we explain the complex processing? How to explain the things that are not within the purview of science?

As a graduate student I was visiting the University of Haifa in Israel some 23 years ago and Professor Alinari [?] was one of the distinguished [unclear] in that country. He gave a wonderful keynote speech and he said to the audience that there were things and questions in life that go beyond science and scientific investigation. Indeed we are fortunate to have Dr. Thompson amongst us to tell us about the evolution of life, his research – the scientific, rigorous, technically detailed research – and other views that will shed light on this important question. Ladies and gentlemen, I have the distinct pleasure of introducing Dr. Thompsonji. Let's give him a big welcome.

[5:02] 

Dr. Richard Thompson:  Well thank you very much for the resounding introduction. So what I'm going to do tonight is talk about some attempts to understand the question of the origin of living systems. So this involves the... both the origin of life, the beginning molecular structures and so forth that we have in living cells, and also the subsequent evolution of these different structures. That's the basic topic that we're going to be dealing with. So the lecture is going to be basically in two parts. First I'm going to give some examples of bio-molecular systems and explain how they show some drawbacks to the standard theory of evolution by mutation and natural selection. And then I'm going to give a more global, mathematical presentation which will lead to some alternative ideas in regard to the origin and... of living organisms and the differentiation of life into different species.

So to begin with, I'll say a little bit about the question of the origin of life. Of course, Darwin himself did not say too much about the origin of life. He began his theory with some primordial living organisms and explained how by physical processes life could differentiate starting with some initial living cells. In a famous letter however, he did refer to the idea that in some warm little pond, just possibly, chemicals could organize together and form an initial living organism. He argued that after all, before life existed, there would be no organisms ready to eat up these basic chemical complexes as they were coming together. So they would be able to freely do that and they might be able to produce life.

So nothing very much happened in the area of studies of the origin of life until the Russian scientist Oparin in the 1930s. Since that time, there have been quite a few attempts to explain the origin of life based on chemical and physical principles. However this has proven to be a very difficult task. I'm not going to review all the various theories that have been proposed. But I'll just mention one theory because it illustrates some of the basic problems. This is the hypercycle theory of Manfred Eigen, a German scientist. Eigen proposed a biochemical system in which you would have certain protein molecules that would catalyze the reproduction of certain RNA molecules that would, in turn, somehow code for the production of those proteins. And this would work in a kind of cycle. And he explained how these cycles could, perhaps, elaborate as a result of mutations, and become gradually more elaborate.

So you have here an initial RNA molecule, and then a primitive cycle, a more elaborate cycle, and so forth. So he explained how these hypercycles could elaborate. But you'll see that the last illustration here in the diagram, is a bacterial cell. So you have the evolutionary elaboration of hypercycles, and then, all of a sudden you've got a bacterial cell which is a completely different entity. So he didn't really explain the origin of life. Perhaps the hypercycles could, in fact, develop, or perhaps not. But we're left with the question of how the bacterial cell actually came into being. Now there are many difficulties in understanding how that could be. I'll just give you a very simple example that illustrates, sort of the crux of the matter. Here we have, sort of cartoon diagrams representing an enzyme which is called DNA Gyrase. So in living cells, of course you know that DNA has the genetic coding for all the different molecules in cells. And the DNA divides into duplicate strands. And these strands have to be separated into opposite ends of the cell. Then a wall is built down the middle and the cell divides, and we now have two cells. That's the basic process.

[10:32] 

So in a bacterial cell, for example, such as E. coli, the DNA strand is much longer than the cell itself. It's many hundreds of times the length of the cell. So therefore it's all tangled up in the cell like a mass of spaghetti, you might say. Now when you produce the duplicate copies, naturally they're both in the same place. And when you try to separate them, there's the problem that they can get tangled. In fact there's a phenomenon known as super coiling which you can demonstrate experimentally by taking two tangled together pieces of string and pulling them apart and you'll see that the tangles become more intense. So the question is: How do the cells manage to reproduce? So it turns out that there's an enzyme which can untie knots in the DNA. And these diagrams represent the function of the enzyme. Of course the enzyme doesn't look like a little machine as shown here. But what we have here are two strands of DNA, one crossing beneath the other. So the enzyme somehow grabs a hold of both strands. Then it cuts one strand and separates the two ends of the strand. Then it pulls the other strand somehow up through the gap, and then joins the strand and reunites it on the other side. So you can see that by doing this, it could untie any possible tangles that would occur in the DNA. This is, in fact, how the cells manage to reproduce. But you can ask the question of how this enzyme originated? Because if it's necessary for cellular reproduction, then you couldn't say that it would evolve by the ordinary Darwinian process because that requires reproduction. You have to have the cells reproducing, mutating, and so forth. So how would this get started? That's the curious question. So that's a simple example.

What I'm going to do is discuss some more complex examples in which the basic theme is, that if you have a mechanism with many interacting parts, which are all interdependent so that one part depends on the other, how do you get that mechanism to come into being? So that's the basic question.

Before I get to that though, I want to say a little bit about some things in the biological realm in which evolution does work. Because indeed, there are situations in which the Darwinian evolutionary process works quite nicely. This is an example which is kind of interesting. It seems that trilobites – these were ancient sea creatures that lived in Cambrian-Ordovician periods – so the eyes, the eye lenses of trilobites, still exist. Because it seems these were made, at least in some species of trilobites, they're made out of a mineral called calcite. And so they're preserved in the rocks and different fossils. So it turns out that the eye lenses of certain trilobites are corrected for spherical aberration. And it's done by a rather ingenious technique which was also invented by Rene Descarte, independently of the trilobites. So the technique is the following: This represents the lens, eye lens of the trilobite. So it has two parts. The upper part, and these are basically spherical surfaces so you get spherical aberration in a lens like this, so the upper part is calcite and it has a certain refractive index. The... There's a lower part which has a slightly different refractive index. And there's a curved interface between the two parts. You see I've drawn the curve, sort of a double-humped curve.

[15:07] 

Well, Descartes and also the Dutch scientist named Huygens figured out that if you have the right curve, you can correct for spherical aberration. And they constructed that curve geometrically. So the question could be raised: Well how did the trilobites get that curve? So it turns out that you can simulate the evolution of this curve and you get interesting results. So here is a diagram in which the... these curves here represent that interface curve in the trilobite eye. And the dotted lines represents ways of mutating the curve. And there are three different ways of doing it which we've tried here. In one you take a complete segment extending out to the edge. And you shift it up and down a little bit and that makes one segment here tilt. For simplicity, one divides the curve up into segments. In the other, you take a central section. Actually the section can be anywhere along here. You take the position at random and you move that group of three points up and down slightly at random. And then the third type of mutation that we tried was: You represent the curve by polynomial, 2nd degree polynomial, and you mutate the coefficient by changing them slightly at random. So then you get a different curve.

So you can start with an initial curve which is just a straight line. And then, using a computer simulation, you can mutate this curve repeatedly, and see if that improves the focus of the lens. And you can use a procedure in which, if the focus of the lens is improved, because on the average more rays go through the focal point, then you preserve that mutation. And if the focus of the lens gets worse, then you reject that mutation. So you have a natural selection process.

So it turns out that you do evolve to the appropriate curve. These diagrams aren't too clear, but this is an initial phase after 100 mutation iterations. And you go through successive phases and gradually it converges to the ideal mathematical curve quite closely. This is using the method where... the first method of mutation, where you take a whole segment and shift it up and down. So the three methods of mutation though, give different results. These curves that you see here, labeled A, B, and C... A corresponds to that first method. The fitness... this is a measure of how far out of focus you are. So the further up you are, the worse the focus is. So in the case of A, you see the fitness is getting better, the focus is getting more precise as you go down like that. Now the B type of mutation in which you move little groups of three at random doesn't work so well. There you're curving down much more slowly. And it turns out that in the C type in which you use the polynomial, you very quickly improve, and then you level off and you don't do so well.

So we can consider why it is that the different methods of mutation give different results. And this has to do with interdependence of parts. If you mutate in the first way, basically your mutations are affecting independent parts, because each mutation basically effects just one segment. I'll go back to the diagram to show that. When we do it the first way... basically here only this segment is being changed. And if you do it over here, then this segment would be changed, and that's a separate segment. So the rays affected by this segment are independent of the rays affected by that segment. So basically you're evolving a series of independent facets of the lens. So that's just like evolving one of them to bring it to the optimum condition, and evolving the other one, and another one, and so forth, all independently of each other. And so it works pretty well. But... and in this case, you're changing two segments, one here and one here. But another one would again change this one, let's say, and the one over here. So you begin to interfere. You get interference between the two types of mutations. So when that happens, the evolution doesn't proceed as well. Interdependence of parts tends to interfere with the evolutionary process. And if you work it through, you'll see that a similar thing happens in the case of the polynomial coefficients. But I won't go into the exact reasons for that right now.

[20:36] 

So that is an illustration of a system in which the Darwinian evolutionary process would work. In general, where you have independence of parts, evolution will work just fine according to the Darwinian principles. So now what I'm going to do is discuss a different case in which we see how very strong interdependence can lead to problems. So what I will do is present some video tape. I have transparencies here to illustrate this case. But I've also made a video in which the pictures are a lot better. What I'll be discussing is a model of a kind of virus called a bacteriophage. A bacteriophage is a virus that attacks bacteria. And basically... well I'll just show you a diagram here very briefly. This is the T4 bacteriophage. This entity consists of a capsule which contains the DNA for the virus. And then there's a hollow syringe that runs down beneath the capsule, and a sort of spring mechanism surrounding the syringe, then a base plate and some legs. So this is a rather diabolical device. What this does is it latches on to the bacterium with it's legs. And when the base plate is in position on the bacterium, the spring contracts, and the tube goes through the wall of the bacterium. And then the DNA goes through the tube and infects the bacterium. And then the bacterial... the viral life cycle proceeds with the systematic development of viral proteins inside the bacterium. Actually the first thing the virus does is it uses the bacterial ribosomes to generate an enzyme that cuts all the bacterial DNA into little pieces. And then the next step is it produces its own proteins. These then assemble together to form new viruses. And finally the cell bursts open and these viruses are released. And this is the life cycle. So what I studied was a... the question of how these processes work bio-physically. So I made some computer simulations of this T4 bacteriophage. So the... that is presented in the video tape. Can everyone see this easily? I hope that...

[unclear chatter, 23:33–23:52]

[Thompson: recorded voice] ... the T4 bacteriophage, an entity that exhibits heredity and reproduction but is much simpler than a full fledged cell. The T4 phage consists of an icosahedral head and a tail segment to which is attached a base plate with tail fibers. The phage operates by attaching to the wall of a bacterium with its tail fibers and then fastening the base plate to the bacterial wall. Once the base plate is attached, the tail contracts and drives a central tube into the bacterium. The phage DNA stored in the head then enters the bacterium through this tube. Once inside the bacterium, the phage DNA takes over the bacterial machinery of protein biosynthesis, phage proteins are generated, and these automatically join together to produce new phages. This process involves the combination of protein subunits in a fixed order along fixed assembly pathways. The subunits making up the T4 phage are protein molecules similar to this one, the enzyme carboxypeptidase. Such a protein consists of a long chain of amino acid molecules. It maintains a specific folded configuration under the influence of molecular forces.

[25:21] 

In these diagrams, the amino acids are color coded. And the sequence of amino acids in the chain is shown at the bottom of the pictures. Although the surfaces of proteins look random, they typically exhibit specifically patterned binding sites which enable proteins to interact or join together in a controlled way. Here, the sites involved in the joining together of alpha and beta hemoglobin are shown. The specific molecular patterns on these sites allow for the joining of these two molecules and no others. It is important to note that a binding site on a protein molecule may consist of widely separated parts of the underlying amino acid chain. Here this is shown for the active site of carboxypeptidase. It is therefore possible that two sites on a protein, shown here in green and blue, will be interconnected by several parts of the chain. Thus there is great interdependence among the parts of a protein, and changes in the structure of one part are likely to affect the whole. In making a model of a bacteriophage, we will abstract from real proteins the features needed to represent phage operation and assembly. A 3-dimensional model can be made by representing proteins as ellipsoids with numerically coded binding sites on their surfaces. We can also consider 2-dimensional models in which proteins are represented by rectangles with similar binding sites.

An important feature of these model proteins is the process of conformational change. In this example, subunits A and B join together. A change is then induced in the upper bond site of B which causes a further change to occur in its lower bond site. This change, in turn, allows B to recognize and join with C which was previously not possible. Available evidence suggests that the rigidly specified order of assembly in the T4 phage is achieved by means of many conformational change linkages of this kind.

Here is a 3-dimensional bacteriophage model. Since the self assembly of the T4 phage head is poorly understood, we have tried here only to simulate the tail and base plate of the T4 phage. The long DNA strand of the real T4 phage is replaced in the model by a short rod which runs from the base to the top of the phage. This DNA rod is surrounded by a coil of subunits which corresponds to the syringe like tube of the real phage. The coil, in turn, is surrounded by a sheathe of subunits which can be triggered to contract and drive the coil through a simulated bacterial cell wall. The self-assembly and operation of the phage are controlled by a network of conformational change linkages. As we can see from these 2-dimensional schematics, this network is quite complex with each protein subunit interacting with several of its neighbors. Here we see the self-assembly of the phage model starting with the DNA rod and randomly positioned phage subunits. Subunits collide randomly to the growing phage and are added to it in an orderly way by the action of conformational change linkages. The operation of the phage model is also based on conformational change linkages which trigger contraction of the sheathe once the phage has attached itself to the simulated cell wall. The wall is modeled to simulate an elastic substance that breaks after being stretched beyond a certain limit. Both the phage and the wall satisfy a principle of free energy minimization similar to that required in real systems by the second law of thermodynamics. What can we say about the evolution…[end video presentation]

[29:53]

[Thompson, live] ... was the bacteriophage model. So I wanted to say a little bit about the implications of all of this. In making this model, I was not trying to make anything overly complicated. In fact, I was trying to make things as simple as possible. Because for one thing, I ran the simulation on an XT computer. But the objective was: Given the way that protein molecules function and, of course, you saw there a description of the conformational change rules of the bond sites, and so forth – that's how proteins are believed to operate in living systems – so given how the proteins function, the question was, how could you put together a model which would work in the way that a bacteriophage actually works? Basically there are two things you have to accomplish: one is, the components have to be able to assemble together properly assuming that they collide at random; and the other is that the completed unit has to function, in this case, by driving the hollow tube through the simulated wall. So taking some guidance from what is known about real bacteriophages, I simply tried to create a system that will do this. 

It turns out, though, that the system that you come up with has to be very complex. Of course... I'll just show you the genetic code for this particular system. This is one page of it. These numbers code for the different bond sites and conformational change rules and so on. In an actual protein molecule, the two bond sites of two different molecules can mesh because there's a sort of lock-and-key effect due to different radicals that stick out in different ways. I used simply integers to represent this. So if the two integers match then those bond sites can match. And if they don't, then the bond sites can't match. So basically these numbers represent the different molecules. And in fact, there are four pages of this – I'll just show a few pages. So it becomes a fairly complex system. So one could raise the question: Let's say we have bacteria living and these phages don't exist. But there are plenty of molecules, you know, being processed in the bacteria and so forth. How do these phages come into being? How did this device originate? In order to make something that even approximates the bacteriophage, you have to come up with a pretty complicated design. And you have to think about it very carefully in order to make it work. If you just throw things together, we will get something that doesn't work. In fact, just like with a computer program, you can have bugs that make the program malfunction. In designing these molecules, if you don't have something just right, there'll be a bug in the self organization of the bacteriophage and it simply won't work. Or the function will not occur properly. In fact, it took a fair amount of trial and error to debug this code. You can say that, in a sense, this is a kind of computer program.

So the question is, how does this originate? This… there are two alternatives. One would be to somehow find a sequence of intermediate models that did somehow function and then led up to this model. Another would be to postulate some other process of organization within nature. One candidate for that would be intelligence. Because we know that this kind of structure can be designed by the application of intelligence. So could there be intelligence operating within nature? One can raise that question. Certainly it's a possibility. So I'm going to give a couple more examples. I specifically worked out a very simple bacteriophage model to see if one could do an actual analysis to show by rigorous mathematics whether evolution of the phage would be possible or not. I won't go into this in detail. But basically this is a very simple structure in which by repulsion between these subunits, it pushes against subunits of a wall. This represents a bacterial cell wall. And breaks through it.

[35:11] 

So here we have a case where the object can break through a wall that's three units thick. But it can't break through a wall that's four units thick because it can't push far enough. But of course, you can easily design one that has one more subunit as shown here. And this one can push through the wall because the extra unit gives greater range for pushing. So you can represent these 2-dimensional phages by a kind of genetic coding which is shown here. This is the code for the first one that I showed which can... that has the three subunits. And you could ask: What would be required to convert this into a phage which has an extra subunit so it can push through the four unit barrier? And since this is a fairly simple system, you can sort of think about it, and try various ways to accomplish that by mutating the code in different places. And you can see what is required. Then you can calculate the probability that those mutations would occur at random assuming that you... assuming that these numbers representing the genetic code are mutated in a random way. What you find out is that a certain number of mutations have to occur simultaneously in order to make the transition from the one structure to the other. And if you assume probabilities for mutations taken from biochemistry textbooks where they measure mutation rates, then you find that the end probability for the transition is about 10^-84,000, if you calculate everything by using combinatorial coefficients and so forth. So therefore, it's not likely that that would happen. So this is a simple case where you can perform that analysis.

Coming closer to the very center of action of living cells, I'll say a little bit about the process of  protein biosynthesis. I also did a simulation of that process. Probably you're familiar with this. You have DNA from which messenger RNA is produced. And the messenger RNA gets threaded through devices called ribosomes. And there's a process whereby transfer RNAs with amino acids linked to them attach to the ribosomes and successively attach amino acids to a growing polypeptide chain. And in this way, proteins are synthesized within cells. And each of these transfer RNA molecules has basically two ends. At one end you have an anticodon which can mesh with a codon on the messenger RNA in a very specific way. At the other end, it will have the amino acid attached, and it has to be the right amino acid corresponding to the anticodon. So the ribosome has a mechanism for making sure that the right anticodon matches up with the proper codon with a very small tolerance for error. So in this way the... a proper amino acid can then be added to the growing polypeptide chain and the protein can be produced in a proper fashion. So this is a very complex process and I'm not going to go into any detail. But basically there are different steps. Here we have a ribosome. This represents the messenger RNA strand. Here we have a polypeptide chain and a transfer RNA in what is called the P-site of the ribosome. Then a new transfer RNA plus amino acid plus a certain enzyme comes in. And that's positioned here with a new amino acid. Then there's a process by which the new amino acid is linked on to the growing chain. Then the old transfer RNA is thrown out and the new transfer RNA switches over from the A-site to the B-site and that brings you back to the beginning of the cycle. So this is the basic cycle in protein biosynthesis.

[40:11] 

So what I did was try to make a model of that. I don't have any video tape for that model but I'll just show you a couple of diagrams to point out the complexity that's involved in making such a model. This is the... In the model that I constructed, this is the active site of the ribosome, and this site contains many different bond sites. In addition, there are diagrams here representing the transfer RNA and two different types of enzymes which are involved in this biosynthesis process. I'll just briefly show the diagrams. Each of these enzymes has quite a number of different bond sites. There are conformational change rules governing the behavior of the enzymes. So the whole system is quite complex. Here's another diagram showing... this is the active site with two transfer RNAs, a certain enzyme called the elongation factor. This is another transfer RNA and this is the polypeptide chain growing here. So the operation of the model is based on chemical rate equations applied to the different bond sites and so forth. So what I did in creating this model was try to come up with the simplest model that I could which would reproduce the function of the ribosome. And it turns out you need to come up with a fairly complicated model. It would take a couple of lectures probably to go into all the details, which I won't do. So here again, the process of protein biosynthesis is essential in cells. If that process doesn't go on, the cells simply can't function. So how did this very complex system originate? If you try to make the simplest system you can come up with, it has to be fairly complex and sophisticated. You need that in order for the basic mechanisms in the cells to function. So there again there's the idea that these could be designed by intelligence. It's hard to see how they could come about by processes of random mutation and so forth.

So what I'll do now... I have some other examples. There are also some interesting additional examples on the videotape which maybe I can show later if you'd like to see them. I'll just mention one briefly because it always intrigued me. There's a ... in the E. coli bacterium, there's a motor which is actually a rotary motor that causes a spiral flagellum to revolve, and this enables the bacterium to swim through the water. The motor is reversible and it can control its motion so that it can travel in the desired direction. For example, if it likes a certain chemical, it can travel to where that's more concentrated, and so on. So for those interested, later I'll show a model showing how this motor works. It's quite a sophisticated mechanism. So you can ask the question: If you have bacteria which don't have this motor by what steps could you evolve to a bacterium that does have the motor? What would be an intermediate step, sort of half way between a motor and no motor at all? What would it be like? And how would it aid the bacterium? Because in this process of evolution by natural selection, each step that takes place has to be beneficial to the organism in some way. This is especially true in bacteria because if a bacterium produces any superfluous molecule, then it's at a disadvantage compared to other bacteria that don't produce that, and it gets wiped out in the competition. So a bacterium isn't going to produce a half motor that doesn't do anything. So how does the motor come about?

[44:49]  

So the next part of the lecture concerns a global approach to the question of origin of life. And I'm going to make use of something called algorithmic information theory. This is a kind of information theory developed by a Russian mathematician named Kolmogorov. And there's another mathematician named Gregory Chaitin who did a lot of work with that. And with modern-day computers, no doubt you're familiar with the idea of information compression. So the information in X... X is... it could be a string of binary digits, something that has information that you'd like to measure. Information of X is the length of the shortest program that computes X. So the shortest program that computes X, that would represent X compressed to the maximum possible degree. And the idea behind this is, if you compress information to the maximum possible degree, then the number of bits you need to represent that is the information content in your string. Also you can have information of X given something else, called F here, and that's the shortest program that computes X, given that it can use F in its computations. So this measure of information content has some curious features. It turns out, for people from a mathematical background, you cannot compute this measure of information content because it's not possible to determine... you can go through all the different programs that might compute something, then select the shortest one. But it has some interesting features.

Here are a couple of examples. If you took, say, a million binary digits of pi. Pi can be defined in a very simple way mathematically, for example, by this infinite series. So by this information theory measure, a million digits of pi would have low information content. You could calculate what it actually is but it would be quite low. However the sequence in pi looks somewhat random. On the other hand, if you'd like to see something with high information content: If you took a million digits with a random event generator based on radioactive decay or something like that, then it's almost guaranteed, a million bits of that would have an information content of about a million. So that's the... a couple of examples illustrating this measure of information content. So it turns out that this information content measure has a key feature which we can use to study the global question of the origin of life. And this is the formula for this.

I won't go into too much detail on all the formulas. Basically here is the situation. Suppose you have a physical system in which life is going to originate. But suppose that the physical system is fairly simple. So the... within this physical system, processes are going to occur in which life is supposedly going to come into being, or perhaps evolve. So what is the probability that this will happen? You can show... Here L(X) represents the probability that a configuration X is going to arise within the system. And M can be computed based on some rules that define this physical system, the laws of physics, and the boundary conditions, and so forth. So we're interested in what the probability is that X will arise. X could stand for an organism. So we take the information content of X, given M. It turns out the probability is bounded by this equation. C is a small constant which we don't have to worry about. Basically what you find is that this information content is large. Then the probability is less than {2 to the minus that value} and that can become an extremely small number, meaning that it's extremely improbable that that X will come into being within that system. That's the basic idea.

[50:02] 

We don't have to talk about a particular X. A particular X might be a particular organism, a particular human being let's say, for example. But you can ask about the probability that you'll get at least one example from a broad class of entities. For example, what is the probability that human beings in general will evolve? That is, that we'll get some representative from the set of all possible human beings. So you can define something called shared information content based on the principle of observation. If we have a function G – this is called an observation function – which looks at each one of these items, say, from the set of all possible human beings, and extracts from them the basic information that characterizes, in this case, a human being; then you can define the shared information of... within X in terms of this observation function and this definition of information content. Basically you would find it to be the information in the... in what you observe, given the observation function. The reason for doing that is this eliminates the possibility that the observation function introduces information into the... into Y. For example, you look at something and you can see something that's not there, so your observation function is giving you faulty information. So by making this measure of information relevant to G, you factor out faulty information basically. So this gives you a measure of shared information content, and you can apply that to computing probabilities. Basically this says that the sum of the probabilities for getting any of these entities, say human beings, within your physical system, will be less than or equal to basically 2 to the minus (the shared information in those entities).

So you can consider the question of what is the probability that, say the human race, will originate in the physical system, or a race of horses or oak trees or whatever it might be. So the first point to make here is that one can raise this question for simple physical systems. A lot of work has been done recently by people in a field that they call Artificial Life. There’s something called the Santa Fe Institute which is doing a lot of work with that. And they do a lot of work with computer simulations in which you have little creatures running around in an environment evolving and developing, accept that these are very simple creatures, not at all like actual living organisms.

So here's one example where you can apply this concept. This is a cellular automaton which was... Cellular automata were first studied by John Von Neumann. And he was interested in whether, in a cellular automaton, you could have a self-reproducing machine. A cellular automaton has a series of cells – it's like a big checkerboard. Each cell has a number in it, and the numbers of the different cells change based on what their neighbors are given a simple rule. A very famous example is something called "The Game of Life." So John Von Neumann asked the question: Can you have a cellular automaton in which you can build a self-reproducing universal computer? So the idea of building a self-reproducing machine is that this would be something like life. Because life, one of the essential features is that living organisms reproduce themselves. And the point of making it a universal computer is that a universal computer or universal Turing machine can compute anything that conceivably can be computed. So that would mean you could have any possible organism if you look at an organism as a kind of automata. And of course, Von Neumann was looking at organisms in that way. And in biology today, that's how people think of organisms, as automata. So you can try this with a cellular automaton. This is the transition function for one cellular automaton invented by a guy named Cobb. He really worked on this a lot. These are just all the rules, that's how it works. And he showed that you can have a self-reproducing universal Turing machine within this system. So now I can raise the following question.

[55:10] 

Suppose you did this. Suppose you put in some numbers at random in a big grid to begin with, and you also add mutation. That is, instead of the fixed rules that he has, you allow random changes to occur also. Now you can ask: Would this universal self-reproducing Turing machine evolve within the system? Well you can compute the probability of that. You can calculate the complexity of all of this. You can estimate it pretty well. About 16,000 bits will do in order to represent all of that. And then you can ask about the complexity of the self-reproducing Turing machine. Now as Cobb described it, it's a very complicated thing. You need a whole book to describe how it works. So the argument would be that, if that... if the complexity or information content of the self-reproducing Turing machine is much higher than 16,000 bits which you have in the automaton, then the probability becomes vanishingly small that that would originate within the system, even if you waited for billions and billions of years, and let the thing run. So that's the basic argument that can be made.

Of course one is interested in actual physics, so I tried a calculation. I took a simple, primordial soup matter model in which you have matter in a box. And you have some radiation to provide energy. And radiation can go away from it so that you have heat flow and you can have chemistry going on. So you could think: Well perhaps life could evolve in that system. And you can assume that the matter operates according to the laws of physics governing electromagnetism which are summed up in the quantum mechanical Hamiltonian here. It's quite a mess but it's not that complicated because we just have a few terms, and that gives you all the quantum mechanics for chemistry. So you can ask: What is the information content of that system? I came up with an estimate in the order of 100,000 bits for representing that. And you can then ask about the probability for the life to evolve in that system. So I'll just mention a couple of points about that, a bit of juggling of numbers. Let's see, at the top here, it's estimated that there are about 300 amino acids in an average protein molecule. In E-coli, there's about 2000-3000 proteins. If you go to a mammalian cell, they're said to be about 20 to 50 times as complex. So let's say you have 20 times 2000 or 40,000 proteins in a mammalian cell.

Now how... What would be the complexity, that of a mammalian cell, the information content? Just to be rough about it, let's assume you only have about 4 bits of information per protein on the average. Well, still that gives you about 160,000 bits of information. And given this rule, with about 100,000 bits for the laws of the system plus some other little book-keeping details to account for those other numbers, that gives you about 2^-60,000 as the probability for this entity to arise within that system. So the probability is quite low. So that's the... a basic observation you can make using this idea of information content. So the... A number of questions come up here. One question of course, has to do with whether, in fact, this estimate of information content would be reasonable. That is, should it be such a high value as this? Well as I said, if you're talking about 40,000 proteins, 4 bits per protein will give you that. 

[59:54] 

There's a rather curious mathematical theorem you could prove about all of this. There's something called the generating function in this information content measure which you can define very simply, simply in terms of computer programs. You define a function called I of X [I(X)] which is simply... If X is a string of digits and X* is an extension of that, more digits, then I(X) is the number of extensions that have information content less than or equal to some big number. So it's a very simple definition. So it's a well defined function. And then you can define... Where did they go? ... Well, where did I put it in my transparencies. Oh here it is. Well, don't bother trying to read all of this. I'll just say what it really says. Using this I(X) function, you can define this F which is called a generating function. Here's what it does: If you divide this long string of bits into chunks, then by applying the generating function to all of the string up to a certain point, you can get the next chunk with the addition of a little number we'll make W here. And you can go chunk by chunk. So what you can show is that basically the size of the numbers W is bounded by the total information content in the whole string. So this has the implication as follows: The average length of these numbers you have to add to get the successive chunks is basically given by this inequality. So if you have 160,000 bits of information, and you have 40,000 proteins, that means you have about 5 bits on the average for each of these W’s. So given that much information, you can generate all the successive proteins, one from the other, just putting in about 5 bits for each protein. 

So to me that suggests that, in fact, this estimate of information content is probably too low, because although I can't prove it, at least it seems remarkable to me that you could have a function which would generate all of these complex protein molecules successively with such a tiny input of information, bit by bit. That's the basic observation. However I can't prove that. But the idea then is that one definite possibility is the information content is quite high, and so the  probability of getting this system of proteins becomes vanishingly small. Now if you apply that measure of shared information content, you can go one step further and ask about the probability of getting any representatives from a whole set of things which have a certain amount of information in common.

So I'll just say a little bit more about the amount of information involved, say in a human being. You can divide this into different levels. For example, if I'm really talking about things on the level of cellular metabolism and morphology of cells and so forth, then you have different tissues, organs and their structure and function, sensory functions, which in... Human sensory capacities are incredible, what your different senses can do. Then psychological functions: I just gave a list of psychological aspects of human beings, a very brief list. One could ask how you could even characterize these in terms of information. Of course, the modern paradigm is that people are automata, so therefore you should characterize all this material here in terms of software, but... according to that idea. And ask how much information you need to specify the software. It's quite a challenge to think of how to do that. But human psychology is incredibly complex. Let's see. I have... Well, here is a diagram. This is an attempt by some people in the field of artificial intelligence to design computer programs that can do things that seem intelligent. This was done at MIT. These are all different modules in the program that interact in a complex way. But this artificially intelligent program is extremely complex. A huge amount of code was needed for it. And actually it wasn't very intelligent.

[1:05:22] 

So this brings us then to the question of how all of this information comes into being. So another way to approach this is to say that we started with a physical system which is characterized by a low amount of information. And we see that it's improbable in the extreme that systems with a high amount of information will arise within that system. So what... However, if the initial system has a large amount of information to begin with, then of course, there's no problem in having different structures develop which contain a large amount of... by which the information is transformed from one form into another. And that can be done. So one way of looking at the... at this whole question is to say that all these different examples that I have given, and the analysis involving the information theory and so on, suggest that the primordial information content of reality may in fact be quite high. In other words, perhaps we're coded into the very nature of reality. And as a result of that primordial coding, the different temporary organic forms can be generated. Certainly if we build, say, a cellular automaton with a transition rule which contained information for different types of organisms and so forth, then those different types of organisms could certainly become manifest within that cellular automata. So the basic idea then is, that to get a large amount of information, you might have primordial information built into the system.

It's interesting, there's one scientist who has approached this from the point of view of physics. This is Walter Elsasser who's a physicist who went into biology. He started from the point of view that physicists have developed, that the laws of nature are simply regularities in observed phenomena. Because there are different ways to look at the laws of nature. You can think of them as some kind of causal principles or something like that. But one way to look at them is they're just patterns of regularity that you have in nature. So Elsasser said that it appears that the basic information patterns that we have in living organisms have the ... Well the way he put it was: They have the same ontological status as the laws of nature. Because there are patterns that we see within nature. We have no concept how those patterns can arise out of simpler patterns such as the laws of chemistry and physics. So basically those are just patterns that are there in nature that we observe. The laws of physics also are patterns that are there in nature that we observe. So they have actually a similar status. This was what he argued. So that's another way of approaching this idea that there is a primordial information content to nature.

So of course, you can then raise the question of: In what form can this information be stored? Because one thing we observe in nature is that transformations of physical substances tend to break down information. That's the basic process. Whenever you see a highly organized physical form, in due course of time, it breaks down, and then disintegrates. So if information was stored in nature simply in perishable physical forms, then one would think that it wouldn't last for very long. Eventually things would break down and you'd just have chaos. And according to these observations that I've been making, if you just had chaos and the laws of nature were fairly simple, then chaos is all you pretty much have, from then on. So this leads to the idea then, that the information that we're postulating which defines living organisms would have to be expressed in some other kind of medium other than just perishable matter, some other energy form which has properties different from those that we see in matter, especially matter that satisfies the second law of thermodynamics, and so forth. So one can consider a postulate like that.

[1:10:33] 

So I'll branch from there to some Vedic ideas. Thus far what I've been saying is quite abstract. And as far as I can understand, pretty much it has to be abstract as long as you simply limit yourself to the different models that are developed within physics and chemistry as we know them today. You can find lines of reasoning and evidence in studying this subject matter which seem to point in the direction of this higher information source that I've been postulating. But it's very hard to find any very concrete idea about what that might be, or how it might work, and so forth, just based upon these abstract considerations.

So I'll mention some other things, though, of an empirical nature. I mentioned... Let's see. The... put this sheet back here... these different psychological functions of human beings. Now some of the items on this list, you can be pretty sure are encoded by DNA. Certainly if you're up here on the list, it's reasonable to say that the information here is encoded in DNA within cells. As you go down the list though, you come to an area where that has never been demonstrated. We don't really know that organs like the eye or the liver are really encoded in DNA, although people think so in biology. When you come down to psychological functions... Of course the modern paradigm in cognitive science would be that the brain is simply a kind of very complex machine that's coded by DNA and it processes data and that generates our behavior. That's the way that people think of it. So this would all have to be software.

But one could ask: Are these things really encoded in DNA? In fact, there's empirical evidence which strongly suggests that that's not so. I'll just mention, for example, there's a psychiatrist connected with the University of Virginia for many years named Ian Stevenson. He has investigated cases of people remembering past lives. So he carried this investigation out in a very rigorous scientific fashion. He focused on young children who at about the time that they learned to speak, immediately tell their parents that they're somebody else, and proceed to give their parents an elaborate story about another life that they have led. In America, we don't hear about things like this very much. But in fact there are many cases like this. Ian Stevenson has collected, I think, in the order of about 3000 case histories of this kind. Typically they tend to come up in countries where people are amenable to the idea of reincarnation. Of course, one way to look at that is to say that, well people believe in this, therefore they make up the stories.

But in the cases that he has studied, there's a pretty good reason to think that no one was making up the story. Another explanation is that in cases where you have a culture in which there's no idea of reincarnation, if a child begins telling stories like this, the parents won't be able to relate to that at all. And the child will very quickly stop saying these things. Because children certainly are very much influenced by their parents. That's probably some factor that's involved in this phenomenon.

In any case, in these studies, typically what you find is that you have a child describing these events in his previous life. And then in some other town, you find that there was a person who died some years before who matches that description. That's called a previous personality in these investigations. In a number of cases, an investigator has discovered the previous personality at a time in which the child and his parents didn't know of the existence of that person. So if one wants to say that there's a hoax involved, then the investigator would have to be the guilty party. You can't say that the parents are involved in, you know, making a collusion with somebody else to tell a story of the nature. So those cases exist.

[1:15:23] 

So the point I was going to make about these cases is that Ian Stevenson observed that not only do memories tend to come across from one life to another in some way, but personality traits also come across, including the kind of personality traits that I've listed here. The person exhibits the same basic sort of personality that was exhibited in the previous life. Also, skills and talents come across. If a person was artistic in a previous life then he may develop artistic talent, you know, as a child growing up in this life also. Stevenson... I can mention by the way that various explanations have been offered to account for this phenomenon. It's definitely not genetic because the previous personality typically belongs to a totally different family who's not in any way closely related to the individual.

Parapsychologists have tried to explain this phenomenon in terms of ESP. Of course, you have to believe in ESP to offer that explanation. The idea is that the child has great ESP power and he picks through the minds of some people and accounts of somebody's life. And then fantasizes that, and presents himself as being that person. Stevenson points out the fact that skills come over tends to contradict that in his view. Because it's one thing just to get some information such as names and places, but to have a skill in which you can do something, it's a little bit... Actually there's not so much ESP evidence indicating that you can pick up a skill from somebody, for one thing. So many different arguments have been brought to bear.

According to the Vedic paradigm, this process of reincarnation, in fact, does have an explanation which is based on the existence of types of energy beyond the types of energy that are studied in modern physics and chemistry. It is explained that there are energies called mind, intelligence, and false ego, called subtle energies, which are different from the gross energies of the sort that you would study in the field of physics. So according to the Vedic understanding... well, in addition to the subtle energies, there's the spirit soul which is the actual conscious being within the living body. So when a person dies, the spirit soul and the subtle body made of mind, intelligence and false ego, transmigrate to a new developing body.

That's the basic idea of reincarnation. So in this case, the information defining these different personality traits is carried by the subtle body. So according to that idea, in fact, it's not carried by the DNA within the developing body. But it's carried by this additional element, mind, intelligence and false ego, that moves in from a previous body. So here you have an example of a kind of medium which can convey information which is different from matter as we know it. So that could be a partial clue to this question of the origin of life. This medium... also the names used to refer to it are significant, namely mind, intelligence and false ego. Because as I was saying before, there are indications obviously that through intelligence one can create these different structures that you have in living organisms. They can all be designed by the application of intelligence. So the subtle material energies also embody intelligence, capacity of thought, memory, and so forth. So... And in this case... well I'll just mention another thing that's kind of interesting in the Ian Stevenson studies – at least it was intriguing to me. It seems that, in a large percentage of these cases, the person died violently in a previous life, a much larger percentage than the rate of violent death in the regular population. And this is perhaps significant in terms of understanding why the person remembers the previous life. At least that's a possibility.

[1:20:16] 

But anyway, in a lot of these cases, in the previous life, the person died violently through some identifiable wound such as a gunshot wound. So Ian Stevenson said he found... he's collected 42 cases (this was in one lecture that I attended) in which you can find medical records describing the cause of death of the previous personality, say from a gunshot wound, and you find that in the present personality, namely the child, there's a birthmark corresponding to the wound. So the position corresponds. One example was, there was a young boy who remembered a previous life in New Delhi as a gunda. So he was a kind of mafia personality. So as is typical of such persons, he eventually died by being shot. In this case, he was shot through the head. The bullet entered one temple and went out through the other. So there was a small wound on this side and a bigger wound on the other. So the boy had a birthmark here, small one, and a bigger irregular one on the other side. So that's an example.

So that's interesting by the way, because it's known that psychological states can modify the body. For example, there are the cases of stigmata which occurred at... well, St Francis of Assisi is a famous example. A Roman Catholic nun or monk will be meditating on the crucifixion of Christ and these wounds will appear on the hands and so forth, and on the feet. So it's hard to understand how that works because there are no nerves that control the cells so that you can cause a certain part of your body to start bleeding as is observed to happen. So that's similar to the birthmarks appearing on the developing child. It would suggest that this mind energy can also affect the physical development of the body. So that's one line of evidence pointing towards this subtle energy.

There are a number of other lines of evidence also that one can discuss but I won't take up too much time, because we're already running late. I'll just mention that according to the Vedic conception, just to give an overview, the subtle material energy also does not have the property of being able to preserve information indefinitely. It also tends to lose information but not at the same rate as with the gross material energy. So the subtle material energy, according to the Vedic understanding, can actually record the details of many past lives. And this information can actually be accessed, in principle. 

So there is a still higher form of energy which you could call spiritual energy, according to the Vedic understanding, which is eternal and which stores absolute data, you might say, for all different possible kinds of life forms. And your coming around then to the idea of God. In the Vedic understanding, God is described as a primordial personality. So I was describing or bringing up the question of where these different features of personality could come from. If we're talking about some kind of enduring, kind of information embedded within the matrix of reality which gives rise to these things, then that would have to be information that tells you about traits of personality. So one simple way of thinking about that is that you could have a primordial Person who eternally exists, and who embodies all these different aspects of personality. In other words, instead of saying that the ultimate basis of reality would be a few simple, impersonal laws, such as you have in modern physics, you could say, perhaps the ultimate basis of reality is primordial Personality. And just as the laws of physics don't change with time – the idea is that the laws of physics are also eternal – so likewise one could postulate that this primordial Personality is eternally existing, does not change with time. But from this primordial Personality, many different temporary manifestations of personality can be generated by the transfer of this primordial information. So this leads one to a concept of the generation of life forms through an eternally existing God or Creator. And I can also mention that in the Vedic conception, these subtle energies also play a role in this.

[1:25:37] 

The basic model is that from the eternally existing spiritual platform, life forms are generated on the level of subtle energy. And then, from the subtle life forms, gross forms are generated. So that's just an outline of some ideas. One might say that this gets entirely into the realm of theology and takes one away from science. And I'll just close with making... by making a couple of comments on that. Of course, some of the things that I've been outlining here, in fact, are in the realm of theology. And they can only be approached by purely spiritual methods. For example, you might learn about God by some process of meditation in which you develop your consciousness and so forth. However some of this material is accessible to scientific study. At least the subtle energies could be studied scientifically. In fact, that's shown by this work of Ian Stevenson. He's collecting basic empirical data. So you can make a comparison, say to the state of the study of electromagnetism from the days of Benjamin Franklin. Back in those days, they had no theory of what electricity really was, but they were collecting a lot of empirical data using laden jars and flying kites out in thunderstorms, and so forth. And eventually when they collected a lot of data, people were able to think about it, and eventually come up with Maxwell's equations and so on and so forth. So similarly, one could progress with this study of these subtle energies, and perhaps learn a great deal. Right now, things are at the stage of initial gathering of empirical data, you might say.

And the final comment I wanted to make was: In the development of modern physics, there's a physicist at Harvard named Georgi who's done a lot of work with unified field theories. And he made an observation that modern physics is also getting away from the area of experimental science and entering the domain of what he called "recreational, mathematical theology." So if I become theological here, I also have good company among the physicists. So... and that, by the way, is a good remark to make in Texas where I hear they're canceling funding for the Superconducting Super Collider. So I'll stop there. So are there any questions or comments? Yes?

Question:  How do people like Dawkins respond to your ideas?

Answer:  Richard Dawkins? Well I've never met Dawkins. I can sort of imagine that he probably wouldn't appreciate these ideas. However, I should mention that this video tape is material that I presented in a lecture in Budapest at a conference of evolutionists. And the chairman of the conference was John Maynard Smith. He's maybe not quite as hard line as Richard Dawkins, but he's... In England, he's known as the pope of Darwinism. So he's a very well established evolutionist. So I presented these arguments there and he appreciated the arguments. I went into a great deal of detail there about the ribosome model, much more than I did here. And of course, I didn't mention much about alternative Vedic concepts. I merely pointed out some of the limitations of the theory of evolution. He said to me that actually, among evolutionists it's known that these problems are there. He said Haldane was pointing out problems like this back, I think even in the 1930s. And in fact, I observed that at that meeting, since these were all evolutionists, they were... quite a number of them were expressing doubts about evolution. saying: Well how do you explain this? And how would you explain that? So... but in more general, public presentations they tend to present a united front, that evolution is a fact, not a theory; they have everything worked out. So...

[1:30:24] 

Q:  Maybe I shouldn't ask this, but do you consider [unclear]?

A:  Well...

Q:  [unclear]

A:  Well yes. It can be extraterrestrial. That is a Vedic idea. Because... Pardon me?

Q:  [unclear]

A:  Yes. According to the Vedic conception, just to fill in additional details, you have the creation of the universe, the differentiation of different elements within the universe. And then a being named... called Brahma is manifested by Lord Visnu. It is said that Brahma emerges from a lotus. But this lotus is the total physical... what it is, as that unfolds, the whole universe becomes manifest, and Brahma is a universal entity. He has control of the whole system of the universe. In Greek philosophy, Plato's philosophy, there's a corresponding idea of the demiurge. You may know, Plato's system was, you have the ideal forms which are eternal, which are part of what he called The Good. And then material things are temporary imitations of the ideal forms. And there's something called the demiurge which takes the ideal forms and manifests the temporary material forms. That's some of the ideas Plato was presenting. So it's a similar concept. So this is done on a universal level. And the different planets are then populated, first starting on a subtle level, and then coming down to a gross level. So that idea is there.

Q:  I have a question. Wasn't it these chemicals that makes it tick?

A:  What? Chemicals that made it tick?

Q: Tick

A: I don't quite follow the question.

Q:  [unclear]

A: Yes.

Q: What is it that makes it [unclear]?

A:  Well, according to the Vedic concept, you have the gross physical body, the subtle body, and the spirit soul, and also there's the Supersoul. The Vedic concept is that God is all-pervading, He's present everywhere, and specifically, He's present within the heart of every individual. By heart it means the citta or consciousness of the individual as the Supersoul. So on all of these levels you have activity. So modern science is telling us about metabolism in organisms based on proteins and RNA and DNA and so on and so forth. So that's all there because the physical functions of the gross body certainly exist, and that's recognized in the Vedic system also. But in addition, there's the subtle body which has its own metabolism you might say, it's own function.

And the subtle body exerts considerable influence on the gross body. In fact, this would be... according to the Vedic concept, this would be the key to a great deal of very practical research in the medical field. Because according to this idea, practically anything can be psychosomatic in the sense that the psyche or the subtle body can influence the gross body in many different ways. It can produce disease and it can also cure disease and exert many different kinds of influences.

So then beyond that there is the soul. The Vedic concept is that when the soul and subtle body are withdrawn from the gross body, then the gross body ceases to function as a living organism. This leads to an interesting question, because if you think of the gross body as simply a bio-physical machine running by quantum mechanics, you could ask: Well suppose we know the quantum mechanical state of the body at one point in time. We've got the complete wave function. And then you could integrate the Schrodinger equation and actually calculate what the body is going to do a little while later, maybe one minute later. What will it do? There are different possibilities. It's not at all obvious that it will keep on living and doing different things. It may immediately die. In other words, the actual prediction of quantum mechanics may be that it begins to break down. We don't actually know because nobody can solve the equations.

[1:35:16] 

Q:  [unclear]

A:  Yes. For a human being.

Q:  [unclear] ...physical matter is superior energy as opposed to subtle energy which is far superior, guiding the gross material energy... [unclear] What is life? If we were to ask the question: What is life? How would you answer it?

A:  Well life...

Q:  [unclear]

A:  Yeah. Right. You see, the modern biological view is life is a bunch of peptides and RNA molecules and so on. That's what it is. The Vedic concept is that life is, well, basically three things. There is the gross body, there's the subtle body, and there's the soul. Ultimately the soul is the most important element because the soul is the actual conscious entity, first of all. I haven't said anything in this lecture about consciousness but that's another whole topic that we could go into.

Q:  [unclear] ...understand the... or can explain the [unclear] ...phenomena we are studying so called scientific... in my mind they aren't scientific because they are very, very gross.  [unclear] ...to say that we can understand so called... these extra normal or paranormal phenomena via the scientific process, I think is silly because... [unclear] ...you can't really explain the material gross phenomena from subtle, subtle energy. This more superior driving force behind. So how can you use the same analogy to explain something which is far beyond?

A: No. What I'm saying is, that there is empirical evidence for the subtle phenomenon. So I'm not saying that you can understand the whole thing by empirical studies. Because I said... part of what I was introducing is indeed theological in the sense that you could only find out about it by a spiritual approach. Short of taking a direct spiritual approach, you can't find out anything about it. You can accept it or reject it, but you can't really find out anything. So part of what I was introducing could be studied, namely the lower stratum.

If you consider the idea that you have spiritual energy, subtle energy – there's some interface between the two which involves the principle of false ego, that's explained – and then you have the subtle energy interfacing with the gross energy. That involves also some additional details. There's the ether, which I haven't mentioned yet, or akash. And that's also not understood in modern science. Then there's what is called prana. There are different types of air, but not air in the sense of oxygen and nitrogen and carbon dioxide. But air in a more subtle sense. So at the level where these things interact with the gross body, you could learn something empirically. And you could probably attain some useful knowledge that way. In other words, the point I'm making for the orthodox scientist would be that there is something here that you can study profitably in this area of subject matter. It's not that it's all just pure theology, or something like that. However, as you go up to higher and higher levels in that study, it's going to become more and more difficult. So that's the idea there.

Q:  [unclear] ...question of reincarnation, is based on belief or is any scientific data that shows scientific proof or disproof... [unclear] ...scientific evidence for... ?

[1:39:52] 

A: Yes. I was pointing out that there is scientific evidence which, in the way of any scientific data, corroborates the idea of reincarnation. You see, you never prove anything with scientific data. That never happens. Because you've got a theory which says certain things will happen. And you find some evidence in which those things seem to happen. That doesn't prove that the theory is right. There could be some other explanation. That's always possible.

Q:  [unclear]

A:  So scientific evidence I mentioned: If you have children who begin to describe in great detail the life of a person who can be shown to have actually lived previously, how did that knowledge get into the child's head? How did that happen? There has to be some process by which the knowledge was... or information was transferred from the previously existing person to the child. That is, short of a hoax explanation, say fraud. But Stevenson has very carefully studied these things from that point of view because everyone will say fraud. So he's very carefully eliminated that in a number of well studied cases. So something has to transfer the information from that previous life or that previous individual, to this child. So that corroborates the idea of reincarnation. Although it doesn't prove it because there's always another explanation. But it gives good evidence because, after all, what could it be? It makes sense. So there is scientific evidence suggesting that reincarnation could be a reality.

Q:  [unclear]

A: Yeah.

Q:  [unclear] ...the Vedic idea of senses… [unclear] For example, if you see the surface of a table just with naked eye, it appears smooth. But if you see it through a high powered microscope, it appears rough.

A:  Right.

Q: What has happened is whether you see through a microscope... [unclear] or with your eye.

A: Right.

Q: You get two different conclusions at the same time.

A: Yes. Your point?

Q: Why is the... Why is the... Why is the sensory perception? How much knowledge can you get?

A: Well, you can get limited knowledge. You can get some knowledge but you can only go so far. Practical conclusion. Our senses are indeed limited. According to the... This leads to some points concerning the Vedic philosophy. According to that philosophical system, our senses are indeed quite limited. But because there is a Supreme Being who has unlimited knowledge, it is possible for us to get knowledge coming from the Supreme Being. This is a possible way of getting knowledge which isn't there if the ultimate basis of the Universe is just atoms and molecules and so on. So the Vedic idea then is that the best source of evidence is what is called sabda, or knowledge descending from a supreme spiritual source. That's the best source of knowledge. So according to the Vedic system, the best sense you have would be your ears, because you can hear. And of course, eyes, by reading, which is... does the same thing.

Whereas if you're trying to find knowledge by looking at things and figuring out how they work and building yourself up inductively, in that way, it would be much more difficult to obtain genuine knowledge. And furthermore, going back to this theological issue, if, to put it very simply... If God exists, and... that is, to learn about God, one way to do it is if God tells you what God is like. Then you can find out. Then of course comes the question of verification. How do you know that God is telling you? And so many different issues. But there are practical theological issues regarding knowledge and so forth. But I don't think I can go into that.

Conference host : It's 9.30. We'd like to close... [Closing words and appreciations – mostly unclear] ...so let’s thank Dr. Thompson...

[1:51:55] 

Dr. Richard Thompson [Informal talk after the lecture]: There are lots of possibilities. According to the Vedic descriptions, there are races of beings in this universe with much greater technology than we have. That's described. The classical example is Maya Danava. Maya Danava, in fact, is expert in building spaceships that can travel all over the universe, and all kinds of other remarkable things. So at least according to Vedic accounts, there are beings with technology that's far far beyond what we have. So it's conceivable that technology can develop. And then of course it's perfectly possible that technology can be lost. It's ...according to Vedic understanding, human beings had higher technology than we have now in an earlier phase of history, but it was a different technology. About... Well, in the period of the Mahabharata, if you look at the descriptions, they had a highly developed subtle technology. They were using bows and arrows so you might say that's primitive. But the arrows were guided by subtle energy which is something we can't do today – we have no idea how to do it. So they developed in a different technological direction than we're going. So there are many possibilities in the area of technology.

Q:  [unclear] ...guided missiles or something? They are trying to say it in terms of arrows or something?

A:  Well there are some interesting things there. In the Mahabharata, when Arjuna was in exile, and then finally he came out of exile just before a big battle with the Kauravas... So he went to get his weapons from a tree where they had been hidden. And it's said that he greeted his weapons and they replied to his greeting, which means there were living entities connected with the weapons. And in fact, these living entities were manipulating subtle energies connected with those weapons. So duplicating arrows... because of course, that's another thing. If Arjuna was firing arrows in the way we would do it, it would have been necessary to have train loads of people carrying arrows... [unclear]  But that's not described. So in fact, there was a system where you could manifest arrows. So how does that work? You have gross energy being manifested from subtle energy. And in fact, according to the Vedic understanding, that's possible. But you have to know how to do it.

Of course, that's partly the whole subject that I was bringing up. Just like the birthmark is produced on that child, the subtle energy is manifesting some gross structure there. So this can be carried even further. So according to the Mahabharata, that subtle technology existed. And if you have that preference in that direction... Well you have Ian Stevenson and a few other people who also do this research. But very few people are interested. So Ian Stevenson has published books on this many years ago. But who reads them? Who then wants to say: Okay, we're going to do further experiments and learn more about this. Very few people take that up, because, as you say, the overwhelming viewpoint in modern science is that everything is mechanical. So we have to look at it mechanically. And if you talk about these other things though: What's that? That's not scientific. And even if one person is interested in investigating these subtle phenomena, then he has his colleagues to worry about. Because he'll lose his reputation, and then, no funding. And then what can you do? So...

[1:56:07] 

Q:  But I think the other point was very well taken... [unclear] 

A:  Yeah. Well the modern scientific viewpoint... you see, it all started with people saying: Well let's look closely at the gross matter and see what we can do by experiment. And they learned that they can do a lot of things. And it was very successful. But then science got carried away with the idea that everything has to be explained in terms of gross matter. So then they come up with the theory of evolution. And they say: Gross matter just operating according to its laws creates everything. But nobody can explain how that's supposed to happen. It's a total mystery to this day, and still they just say evolution. They just wave their hands and... It's really the absence of an explanation. But unfortunately this is blocking progress in further understanding of what's really going on in nature, because we just say evolution. We don't really try to explain because we have no idea how to explain the evolution of these things. And so, no attempt is made to investigate further. But I would suggest that if people did look into this question of the subtle energies and so forth, you could learn a lot which would have great bearing on this whole question of life and its origin.