 How your current search algorithm works, if I type something like, and this all got shifted something else. A little tiger should be in the box. Well, I think it got shifted a little bit here. If I go and type in a Google box, something like Bengal Tiger, hit return. Your Google search engine goes off and it's already indexed all of the web pages, 10 million of them. It will be back to me, links to what it thinks are the most relevant, like to talk about Bengal Tigers. And that's all very well and good, but my new idea is substantially better because this new idea is based on Darwinism that we're going to call Google on steroids. It doesn't have to simply limit itself to existing web pages. It can actually search the total space of conceivable web pages, of possible web pages. And so these guys are looking a little bit suspicious across the board and table. And you say, yeah, this is what I'm talking about. It is not limited to existing web pages, maybe 10 million of them. It can look at all possible web pages. You type in Bengal Tiger here, you hit return. And even if there are no sites on planet Earth that talk about Bengal Tigers, this will construct one and send it back to you. And it will be an awesome site on the Bengal Tiger. And they're saying, really? And you say, yeah, but that's not all. That's not all. Well, they say if it can do that, then we shouldn't really call this a search engine. We should call it something like an engine of invention because sites doesn't have to exist and this will go up and create it. And you say, yeah, that's okay. But it's even better than that because this search engine does not limit itself to the space of possible web pages. It actually will reconstruct matters. So if you type in Bengal Tiger and hit return, out comes a Bengal Tiger. And at this point, they're calling security and trying to get you out of there. And you say, hang on. Okay, I'll leave, but it's better than this. Because actually, you don't have to put anything as specific as Bengal Tiger. You should just type optimal fitness. And again, it serves the entire space of material possibilities. And it will produce not only the Tiger, but 100 million other equally remarkable species, actual living things, all simply by typing optimal fitness. And we'll go out there and do the job of finding these different things because they're fit. Well, at this point, they've tied you up and taken you off their campus in disbelief. And I would suggest you that really is what you need to believe if you want to believe a Darwinian story because it is solving problems like that. Now, you might say, well, but it gets a billion years to do it whereas Google has to return its result in a third of a second. But it turns out that if you look at the size of these spaces, even that does not make up for how much more remarkable the Darwinian search engine is than the Google engine. Because these become phenomenally huge when you start looking at possibilities, not just actualities, okay? So what I want to do very quickly is look at the beginner search where we're going from one protein to another that performs a different function, but it's structurally very, very similar. And I want to explain why this is actually more challenging than it looks. And we actually tested this in the lab where we believe that this is more often than not possible even in a billion year time frame by the Darwinian engine. And I'll do a finality. Suppose this is a message that we need to convey. I'll read it. Okay. Read it. Tell Sarah to bring Jeff and meet me at the entrance to Martin Hall at 530. Martin Hall is here on campus in the southwest corner. Suppose that's a message that we need to convey to someone. And suppose that we have access to this message which is not quite right. This one says, how David to bring Jeff and meet me at the entrance to Payton Hall at 430 instead of 530. So different person, different place, and different time. And here are the two places. So in other words, if this is what I want, even though this sentence is structurally very similar, it's not going to do the job because the person will be, it'll be the wrong person in the wrong place at the wrong time, okay? Very similar, but they're significantly different. And in fact, if you line them up, this again got expressed. They're supposed to be totally lined up. But I've colored the characters that differ between these two sentences. And if you count them up, there's a total of 11 letters that are different between the two. Now, a Darwinian search, the equivalent of the Darwinian search for this beginner problem, given this, it will go out and search variations on that theme until it comes up with this. And then your whole priest got the message that you want. And most of it, our intuition tells us that shouldn't be that hard because you only have to change 11 letters the rest of them are correct. Anyone have a guess on how many sequences would need to be searched in order for this to happen? In other words, how many sequences differ from the starting one by the same amount of system? It's phenomenally large. You can calculate it like this, and there's the answer. Five times 10 to the 28th power. That is how many sentences differ from this one by the same amount of that one. And the vast majority of them are Jewish of course, and only a very few of them would do the job of this. So that's the size of the space you have to search to solve a problem like this. And that turns out to be prohibitively difficult, even though this is an easy problem, relatively speaking. If you look at the advanced search where you have to get a new structure, we're now making it vastly more difficult. Here is more akin to this. Suppose this is the sentence that we have and we need something radically different. We need directions to the campus. Here it doesn't even help us to have this because this differs so radically from this, not even a helpful starting point. So basically we have to go back to scratch, we have to reshuffle letters, and just come up with this de novo. It does no good to start from this. In that case, we're searching a phenomenally large search space. This is literally Google. Google is 10 to the 100th power. This is like trillions and trillions of Google. Needless to say, that's not feasible. It's not feasible even on a multi-billion-year time frame. So, I've given it in a non-technical way, but the bottom line is what is claimed here of Darwinism functioning as a search engine if true would be mind-blowing. It should be mind-boggling for anyone to believe it. And if you go and test very carefully the actual numbers and you go to the lab and look at the changes that are needed to accomplish these changes in proteins, you find very clearly that it does not work in the time frame level. And I will wrap up with that simply saying that if there are people here who want the technical material behind these arguments, that there is a growing body of literature now that has it. And here are some of the key references for what I've said here. And I don't want to leave it with that. Paul Nelson has come up next and talked about what we call the developmental mutation problem. And this is probably related not so much to genes and proteins, but a problem related to body plans. And we can define a body plan as a distinctive set and arrangement of body parts, of tissues and organisms. Some different body plans that arose in the Cambrian's examples on the slide. And I'll just hand it up to Otto Falk and he can take it from there with a new and separable independent challenge to neo-Darwinism that comes from the consideration of mutation and what it can do with the level of body language. Paul has been extraordinarily patient. So I'm going to try to move briskly so we can get to Jonathan's talk and then what is, for me, the best part of the evening, which is the questions and answers interacting with you. Because I know what I'm going to say. I've prepared my PowerPoint. You know, I'd like to hear from you. Right side advances. This is a picture. It looks like what you saw in the film. I want you to keep in mind the differences in architecture. All of you have been to the seashore, I imagine. Perhaps some of you here in Texas down in the Houston or Corpus Christi. And you go to each of them and you notice that there are a variety of forms there in the tidal pools at low tide that differ from each other fundamentally in terms of their overall form. Now these groups here, the actual species represented are extinct but we have modern representatives of those groups that we can study today and some of them have provided a tremendous amount of information to biology, to the science of biology. In particular groups are a species from this phylum, from the arthropods but also from the echinoderms and other body plans represented here. So I'm going to talk a little bit tonight about the model system from the phylum Arthropoda to fruit fly Drosophila about which biology has learned in the past 100, 110 years actually a tremendous amount. And I want you to keep in mind not just those different shapes but the neo-Darwinian explanation for how those different architectures arose. Now this is textbook evolutionary theory. My guess is if you went to a evolutionary biology class here on campus and opened the textbook and looked at the explanation there for the origin of the animal phylum. This is what you would see. That the differences in form that we see in the Cambrian explosion arose by the natural selection of randomly arising small scale variation and that these forms share a common ancestor. Now this cartoon here which I've labeled Urbilateria that's the name given to this entity does not represent a real living thing. This is a strictly conceptual entity. We don't actually have any representatives of this. It's what is postulated to lie at the base of the radiation of the animals in the Cambrian explosion. And it's name Ur is a prefix meaning ancient or original. Bilateria these forms to which are extinct all have bilateral symmetry. That's their common ancestor by hypothesis and it's represented here in the cartoon in two forms. This one on the bottom has a little more detail than the one on the top. It kind of looks like a worm but it has its guts and sense organs and so forth. Some complexity represented there. Now my thesis for tonight is that biological research done within the neo-Darwinian framework over the past 30 years has actually shown that framework to be false. And the challenge for the biological community is where do we go from here. So in the next 7 or 8 minutes or so I'll show you why this is the case. Now let's go back to one of the founding documents of what is now the most widely accepted theory of evolution neo-Darwinism. Namely the publication in 1937 by Theodosius Dubjansky a great geneticist who mentored a whole generation of evolutionary biologists including one of my advisers at the University of Chicago. In 1937 he published a book with Columbia called Genetics in the Origin of Species that was one of the founding documents of modern theory. And early in the book this is page 12 so he's laying out his program here and he says we have a fundamental problem with evolution. It seems to require spans of time to which we do not have access time on a geological scale. To bring about the changes that we see in the fossil record requires a lot of time. And we don't have access to that. How can we work on the problem with evolution given that we don't have these long spans of time to observe. Well he says we're going to have to make an equivalence to push the program of evolutionary theory forward and he describes that as a reluctant sign of equality. And the reluctance there stems from Dubjansky's knowledge that many evolutionary biologists even at that time would not have agreed with him. For instance his own mentor in Russian Yuri Fulupchenko a great geneticist who coined the terms micro and macro evolution which were then brought into English by Dubjansky did not think that the mechanisms of micro or small scale evolution could be scaled to a problem like the origin of animal body plans. Dubjansky says that we're going to make any progress we've got to put that sign of equality there and we'll see what we can do with it. So here's a little cartoon showing you in a schematic form what his argument entails. So here's our starting population here with variation distributed let's say for character A around this range. Time is running this way and disparity differences are arising on the horizontal axis. Dubjansky argues what we see in macro evolution is just micro evolution summed over time where the difference that arises is proportional to the amount of time available.