CS4 talk Rene Doursat

thank you very much that was very excited too when you sent me that invitation and I’m very very happy to be here I’ve known some of you for a few years now in fact i was at winchester at the end i should have asked you what was four years ago it was an excellent conference and saliva chisholm richard do and our people at and then we better get into during a key card that there was indeed winner was then market like 12 and so on but it’s the first time here so it was I’m really glad that it finally happens and especially I was in Crete as I told you buy this complexity center here it which is relatively new which is complex systems the salience generally speaking but yet at the same time is also has this I think unique focus on what stimulation is in the name of it and focus on computer science and buttons inspire computer science and data I like the fact that the complex systems center has a focus on artificial life and and trying to bridge to bridge engineering and science of complex systems and I’m going to try to entertain you with thoughts about this these bridges between between looking at complex systems natural complex systems that are standing how they work made of agents interacting locally emergent behavior and so on and on the other hand wondering how we can create our own complex systems and for what purpose and how we can inspired by the way we look at to create new ones or maybe or maybe tamper with the existing ones as instinct that evaluation which is briefly stated here and create hybrid system so this is a back and forth between observing and understanding of the one hand the science of complex systems and and designing or not too much capital design of course the design in a certain way design the agents of complex systems to create new phenomena that not exist to make birds from differently to make bacteria cluster different do things they don’t do to usually end up in fact I like assess most recent work what was my team it was or might be termites two different things and virtual worlds so the life as it could be much the definition of you so without further ado I’m going to dive into this and and the title will become even clearer as I go I’m going to spend some time on some general production and concepts and then i will show you i try to cut down on my productions you not to in size so i will wave my hands above it but then i will i will show you more concrete example studies models i have been doing with my students of the principles I we talked about so in fact let me give you a very brief tour of the of them probably I won’t have enough time to do everything that I first in fact start with a model of biology so by modeling a model of member real Jenny development and biogenesis that is zebrafish value my students reality of course the co supervised by a real apologist developmental biologist many of us he just finished a few weeks ago and defended then how will I will transition to bio-inspired engineering so this is large that this is a la vie for rights and how we have in this is not really emporio zor creatures with fictitious worms this is 3d advil devil or in fact more devil than ever for now but that especially devil robotics creatures that then function in some space same inspiration here except instead of a 3ds is we have a 2 D Prime and this is more inspired by parent growth in that case maybe networks the ID is even in its applications are it far away can we have self organizing self constructing networks for the purposes of technology building and so on so that the space is different from this one but the idea is the same and in fact possibly back to biology but by a different path and back to as i was in tampering with biology synthetic biology of horses the bigger seeing currently i will show our first steps there are immaculate up another time and we haven’t done a lot in that arena yes but to give you also just from picture to be complete so in that case value engineering sorry engineering the biology we come from fire those those inspired so it’s inspirational ideas way

engineering the biology and make make baggage into something different and that we can hybridize as opposed to my forehead me anyway so before that very brief one second archana i want me to dwell on that too much because you are all familiar with complex systems even though definitions vary a lot but let me let me go through these concepts of course i hope you to talk much about this again this is the first portion rebuttal consistent levels of organization word and we all know that what we mean by open systems for even though again those words are really here defying those piece of our eyes and emergent large what is power should graduate seven or network agents and so are totally fine so this is what I mean with complex systems and you kind of already know it depends on the audience I thought I always put this start first to be clear and Pope this is a shame as period about the situation in France I inserted it for you because you are here a center and just wanted to show you that inference we also have now Institutes of complex systems that are kind of popping popping up here and there the first and main one is in Paris that there is also one euro and then recently the past three years there have been a few was also in the province in various cities in France and the one I was part of an i directed for two years have for this partners it’s a complicated structure in front of this is not the point of my talk just to tell you that we also have complex system center and yet at the same time I’m show you this map and with a small let’s see the remark about the fact that the center’s generally are more about the science of complex systems and social systems and physics statistical physics of this and that and so on and that was little or in in terms of engineering performing systems Baumann started here so this is this is why I find stuffington here the very very excited anyway moving on so continuing with complex systems every time that small agency get together what if you storm cells and some organisms and their brains organisms from society’s construction or correct emotion and we specific organisms this species that we are with our technology before more these incredibly complex society phenomena that everybody seemed interested in trying to understand understand and bring solutions to this won’t be our point today but what I am focusing on in this charge so this is the global again for sure inside the brochure what I’m looking at now to the point is this class of systems that exhibit strong architecture is strong morphology strong shape a strong organization whereas is strong what do I mean I have not measured it but I think I that intuitively I hope you really and you can we can talk about it you can of course the press or hand and saying oh we really are not in the Sun but it seems that the this is the epitome you know a multi-city tour organism like this little critter here is the epitome of of an architecture completely self organized system an architecture without an architect all right imagine what a lot of you know creations for freshman spleef of arrogance in fact or still believe but no there was no architect at least not in a sense of putting things together and design and the same goes somewhat at the different scale for for example termite mounds there is no termite is the architect of the trauma team of architect there is a team of construction site managers okay so it’s completely it’s and for always and no one has the board blueprint the whole map of what is going to come up and yet it is very sophisticated in its structure as opposed to flow cat was right on purpose to focus on this but here was an anymore flock at birth the vertical is around because we have workers and variable densities there is no architecture there is no architecture in an Trekkies there’s the architecture in lucema stripes and spots in fact sure rating is quoted or his people think that foreign said although I never really found the exact quote but that he said newspaper 1952 on the chemical basis of

morphogenesis but in fact morphogenesis was a little bit misnomer setting aside effective as a genius of course in many domains and every campus his last word and he also had a stroke of genius and that is to naturally but yet he admitted that he had a stripes you know the famous reaction-diffusion system 418 spontaneous order out of rotations but that didn’t give him the the horse around the stripes under the zebra so I would I would I would really separate Patrick formation in the statistical sense of repetitive uniform even though it’s it’s a fascinating phenomenon that we find everywhere you’ll send you in the brick oven convection cells and all these things beautiful patterns everywhere in nature and Tara books have been published about pattern formation sure fantastic fascinating but this is not more few genetic innocence of morphogenesis creating shape an architecture and what do I mean with that I mean heterogeneity I mean parts modules subparts appendages and so on learned most of our reports usable programmable somewhat so if you run in the program not a very good metaphor of a fertilized egg of the supra you will get another sequel and the same body plan of course in other details you know every single cell that constitute the zebra is not going to be in the same they are going to be the same the same pace from individual to reduce wasn’t sure you don’t have any amount of randomness at the microscopic level but at the measles copic level and macroscopic level with the organs the appendages everything is in place exactly the same from one integral to the next which we will never get with random striking in random spots they are never going to get the same things right with a recent gotten the differences between what I call morphogenetic and gun opportunity assistant Heyman and you know just 200 an a here is an attempt or so intuitive intuitive view of from from the stochastic pattern formation all the way it’s very strong morphological systems and via for example here insects this day a bit of both types so again entries or a network of entries are not stroking morphogenetic however nest especially termite mounds are strong democracy brilliant of morphogenesis very talkative and waiting my hands and in fact i take this again and put it here already told you the differently isn’t that which i just talked about right now hear this case with me is that I think the essential difference and we talked about this adventure with Ophelia is making the agency food here they are seedless or they don’t have enough information to create interesting shapes morphogenesis pathologies and here you can tell them to allow your agents with more information if you went out or if they happen to to be able to contain more information then they can create more architectural system than those randoms the pattern civil rights are just repeating myself for the acting study but this time showing what work relies underneath is the fact that you there is more information the agents are able to make more sophisticated decisions depending on where they are 30 / booth with the interactions among them but there is another way to look at it but I want to extension this is the other way work instead of making self-organization more informed and more more for genetic you do the opposite you make something that is extremely formed an extremely architecture but top down and not that one self-organized you make itself organized okay so this is completely the opposite way but you know this is another way to look at it in the middle anyways morphogenetic engineering self-organized architecture or architecture self-organization it will all end up in the same in the middle where you have a lot of engines and hitchens are sophisticated and they can do various things that you can get then separate systems that are not reading that’s the whole point and there is a natural book about it second Shane is going last one of the put the book with 18 chapters what is it would have contributed just came out a month ago and you have a force a lot of corrective robotics in it people are interested in the constructing with robots 50 robots themselves cling together or the brain rocks and build something you also simulate robotics here here or kiss I a must a nice warm chemistry yes this is

very typical so just that was my sin you make you make enactus Earth’s to give birth difference flocking parameters and you mix different bird species never happens in this guy never have different bird species working together in that is you do here with hero key and utilities very surprising morphologies you will get up quick bursts blue cards with red version ghetto girls program together and they have different speeds different you know alignments and gourds and stuff like that and deform interesting instead of forming those random masses and cluster they formed some shape that’s very very fluent in for some things inspired by development is my consent about it and also generate the assistance rewriting systems based on rockers anyway all that good before name what we could call general is even more for genetic engineering alright earned two more starts about this concepts and then show you examples of my own let’s take a little bit about this going from the science of the engineering it has been done before you could say you know it has been done before with neurons and colony is giving SEO genes of course functionary computation so the sorbonne inspiration doesn’t seem to be you yes at the same time what has happened here is a bit depressing because all these fields here I’ve got straight away from their complex origins now when we also talked about it Seth overloads you know typically machine learning or defect evolutionary computation have really become fields of meta heuristics and optimization and you won’t find a lot of if any system that is being that is being that is learning more that is being involved that remain conferences and that it is still made of the large number of agents you won’t find a lot of that in the machine learning or the emotion recognition community in fact even musician has become something very much of a metal mystics and where is the you know where’s the origins of the fine grain merchant system and so that’s why I think it’s important to kind of go back to this and my let’s get that what I want to do is the same going from the signs to the engineering the bio-inspired engineering but this time i take another Avenue and I want to keep its internal complexity and that Avenue is memorial Genesis or we can collect biological development you can put it 27 or growth and so on in fact there are other communities or families of works that for themselves artificial and royal jelly for example artificially ontogeny or developments or even advil therefore something ever devil robotics exists or artificial level depends on so many many different ways of talking about it but but decided that let’s look at the black boxes of development that has been also in fact neglected interesting you know in biology for many many decades apologies 20 santa rita the big success was the grind synthesis the modern synthesis is stored between genetics and evolution melbourne darling but it has put them together we have now but this modern synthesis has always skipped this step it was always about cooperating genome with the phenotype understanding that things before because the genome has mutated and so on but never really looking at this insanely complex small intermediate stage of it goes through an enormous complex system you know so it’s not a legitimate coding directly for that foot and actual the subject there is a gene that tells you how long’s the pistol then gonna fit or whatever of course them the genies not saying that the G is guiding the source s to in such ways that they are going to form to divide faster to adhere different ways to migrate differently no the emergent result is going to be there live in and so on with different structural but that’s an emergent level it’s not the Iraqi encoded @ eunice than that so this was neglected for a long time in baggage announcer has been reopened and it’s called of course functional appointment but fo devil evolutionary development is really not looking at it more closely before what forest and evolution if you want to understand how evolution comes up with all those innovative structures out seemingly out of nowhere we need to

understand the vet influx of that we cannot just continue with the black box evolution and I’m going to do the same game in my inspiration in engineering too if you want to to kind of bring into engineering those ideas coming for biology we also need to do a modelo in engineering so this is what I’m attempting to do contributing to label and I will show you now a few examples I’ve been too long on Infractions affected agree in fact I’m going to go very fast over this one Julie under his work which is in that case try to be set full to the values try to be erased it’s a 3d too fantastic radiation simulation of different stages not about organism of course that the early stages of yum really development of the zebrafish that we get into it right now and here is in 11 big picture of his word simplify the work of his word and then I’m going to throw you brother slides because I want to get to the other more engineering part and get out far but I still want to show that because it’s beautiful and so for example we we have raw imaging data we have my post-op microscopy days out of the drug in zebrafish and then there is a small image processing side not just union but the whole team that is working on this project is called by local merchants under the supervision of netting value has this developmental biologist I talked about at CMS and anyway so there is this sound she just about extracting information from the raw images and creating a list of coordinates and velocities and so on so this is not a model this is just collecting data making data structure from vessel traffic but then there is the model party hi in fact I want to explain is you want to recalculate with this this is this is just tracking that but this is no calculator X in here right this is this is a complete simulation it’s not tracking anything it’s not try to recreate that even though they don’t look the same of this illustration and the world point is that you won’t know too if you want if your goal is to help the college’s understand each other is bio biology then you want to make sure that your simulation is a resembles the daytime had extracted and you can super in from style and measure some kind of discrepancy and that he did was morally lifeless this is what we are doing it and this is very short big picture what junior did and no we could be very fast so these are the the microscopy images yes from from developing embryos you could look at that you could watch them for hours so fascinating how how they do the formal structure so fast of course it’s a very thin here but still within a few hours developmental stages then then this is the tracking side which is so trippy I myself we were just part of a team it’s so much work on so many mathematical algorithms to do image segmentation and so on anyway so this is what you get and then surely also did his own in fact workflow of image segmentation if it is going to move on yes that’s also there are many ways of extracting again this is he was interested in in vector shapes in displacement vector C because activity he wants to compare his simulated embryo with a red one and what to do this on the basis of Hitler things and see those the trophies are similar reductive see we said vaccinated a real is pretty much like the red one that’s what we wanted to obtain so this is this furry ball this ball of hair is in fact the vector field than forty and four needs and moving dynamically of the movement that says create when they when they start below and getting the the yolk and end rating structure moving on so I just breathe this is impressionistic in a sari and then but i will spend a little more time on this one because it’s really the core of not only in julius border but also the mine work with our students on the bus fares side this this is the core of how I not just me but but basically the way I heard that ended up doing is my network models of

developments how to model developments how to skate is the government’s in a way that can be then programmed Maurice even even though of course it is simplified and for that I rely on America coins book oh he’s not cited here but Enric open water he’s a he’s a pen biologist at where was that Norwich acknowledges and he is a hero to the popular book about development in he called it the art of jeans and and his book is is full with artistic metaphors about how an organism grows memory of forms itself and the main the main the core aspect is this coupling between sketching and painting the embryo is painting itself and starting in step at the same time so what does painting is that mean it refers to the fact that the embryo has a hidden geography hidden because when you just look at a number under the microscope you don’t see the geography don’t see the different regions of Earth what differentiated cells not from different cell types but Margie’s in fact are able to reveal this geography physically by inserting markers chemical markers or regimented markers and can see then you can you can trigger those color domains you can see there is a path through another passion is right you can be can mark and die the embryo in such a way that you can make it reveal those morpho genetic feeds a very cool meaning that patches of sets have started differentiating and expressing other proteins right that’s what differentiating me means that they have started using other genes and expressing other proteins than the neighbors so that’s why they appear rather than the neighbors of your ring so the embryo is painting itself in a corporate way and of course is starting inside there is the mechanics to note says but here we shave themselves my grades and the tissues that if Iran forward and very complicated ways so you have both this painting and 13 going on and it’s artistic metaphor suggested by analytical point i think is debris it’s really summarizes summarizes it’s all war and you can rely on either to do your model d and this is what I do here on the scary side and the babies are you have set mechanics and gene regulation respectively so here’s just a little sample of the many ways you can send mechanics of course that you have to make choices you can be more or less detailed in how your model or set make hair needs it can be just one second here Delta then you have sprint between them is very very coarse and yet this is the fact what what doing most cases it’s already something you can give them more refined and you can say that one side is in fact the domain of pixel this is the famous cellular pots model a little bit so it says in 2 megapixel no fossils in 3d you can attend security here you can look for you buddy it rise many ways of inside mechanics on the side of gene regulation there are not many ways there it’s a bit more standardized in fact mechanics for me the biggest mystery how few cells that are neither sought nor liquid they have a cytoskeleton that depolymerize and then and then take apart they have this memory into the fluid mosaic the board physics of the mechanics of the center that membrane endure their skeleton county extracellular matrix the scaffolding between them is such so difficult to understand for for physicists in chemistry and science it generally is part of that now this is compared to how cheese recreation you could say has almost in being harvested already exaggeration to but this is this is more natori more people have worked on conscience equal solution regulation the fact that gene produce proteins that bind to the 10 and he turn regulates alternative new concepts so that’s why you can have networks with you forgive the proteins and you have networks of gene Purdy’s emerges anyway so but this is the hidden geography here ok those those domains of colors right that we heed proteins and so gene activity and miss the connection eventually have it back to because what is the company making box assets move they will change their neighborhood and

so they will change their contacts and the signals that received and the signals are received into this gene regulation that we are going to modify the dynamics of this and are going to paint that different ok so that’s the whole point and once they are painted differently once the orange cell becomes dark orange storm right you know we starting to sub differentiate the precursor II nervous cells with becoming more peripheral nervous system as opposed to san fran zone then they are going to have different mechanical properties so the color isn’t using different mechanical behavior that in turn is changing color this is the whole point i spent more time on this because it’s simple to rest no Julia’s concerned he continued now his work on on modeling so simple simple force equations where you have some kind of a bad for elastic force if it sells and donated or good something very coarse if it’s very primitive and yet yet it’s already very committed to two it gives a very personal results already so I’m going to be do too much detail about this right now sorry I’m going to skip and this is also a few movies that that obtained oh I’ve seen this one ready this one is meant to show that he also had two in his painting in his case was ad hoc it was by hand that he will be foremost authority painted the said one by one no but he pretty found it he pretty find the cell types they did not emerge from the mechanics that they were scheduled ok you understand so he took a shortcut there and he said they’re here be those they are put the deep-set here and then the entropy layer said and then the yolk inside the yolk is just one big ok and so on so he tried he find his he had 25 Colorado said okay but then they had different mechanical behaviors and that’s how he got he got the whole thing to reproduce somewhat the rain embryo and here is his of this is the methodology again last night about his work what I showed you remembered is comparing the real data with the simulated data by just know simply over happy the two vector fields those movies don’t really show that against the nutrition is a methodological inspiration but this is what he did and typically he has a similar memory of there again he can vary the parameter many particles but one of them in that is the timing of activity what is this doping like that and so he gets differentiated and Rios as disparate or varies ok and then he compares them with the radio data this is the ring the ball of fur so the vector is that were extracted from the raid microscope images after this very complicated right and then he gets for example here there is one parameter that seems to me to be the most realistic or the Middle East very smart efficient aburrio of all this year so what we get son of P consent okay so in that is this part of our seems to be optimal and the most realistic one but then there is the whole question about looking what those 15,000 hundred forty-six mean for the colonists ok so how to transit back your simulation parameters in to integrate a time and space and other physical units for the bungees to to learn something from it so for industry complicated but this is this versus and ever now this was the very early part i wanted to talk about and now moving on to from there moving on to artificial light as search and in fact since i have it already quite a lot about the mechanics and genetic us that we find here again this was much now the board its hands on my own at doing this time artificial in governments that is this creature is nothing real but i wanted to to program a proof of concept of what happens things in the beginning of the seminar which is architecture itself organization which is programmable reproducible shape that is several knives so what is program are the agents that zap organized to for this this this shape is body plan I it has again it’s it’s a bit add mode it’s completely empirical it’s the miracle there is not much method must be hard if any math at

all I will show you how it works look inside but but you know I think this first model school was was kind of achieving the sense that every time I wrote this this is the same movie of course in the inner loop but if i showed you another movie you would see the same thing in fact we were cheating naturally again as I said from the zebra earlier the exact number of ruses won’t be the same from intro to which would of course not and they won’t be exactly where they are because there is noise they cannot jitter around yes what I have hopefully successfully achieved here is that the the region’s the mesoscopic regions here that simple eyes in an artificial boy have not weighed organs tissues and things like that will be at the same place where the overall shape would be the same so that that was like I wanted to have regulated programmable and reproducible morphogenesis so now let me show you what the steps are and the steps are alternating in a bit universe right away I’m authority mechanics and genetics instead of making them get together at the same time there is here a mechanic mechanic by vision than the radiant estate is also important technique spend on on the next I sensitive here and then I will show you the latest progress is so key to my thing my little model here is a gradient so you can you can think of pheromone if the metaphor was insects and that is the metaphor is a few scales lower the data for is sense not insects but the same idea storable you have that is more fortunes or you have molecular signaling messenger second messenger single anyway it has not been very much gratified in the body actually but there must be some way for the cells to communicate to each other where they are and this is key in my story here I need this gradient you can put it brilliant as a shortcut which is completely decentralized peer-to-peer for migration of positional information this is a concept by Lewis Wolpert on the mid 60s that’s in history as the first value vertical the French fragment offset diffuse some kind of signal no distance or short distance and instead of forming drugs as in ration digital deterring the in fact is basically use the information about the relay board of concentrations we have this freezing curbing this if it is between this and that they will turn blue it was between this and that will turn white and otherwise there is very little of it Detroit original red node French Valley reading out the position from the morphogen concentration very simple idea when I same here except exciting that is it’s not really valued decreasing pure exponential new procedure but it’s an integer more in the computer science while hopping from agency to agency agents are trafficking integers it’s also a gossipy it’s a very robust elemental as you can see you could already see many times now but vertical routes on the everyone they can’t for I want to be 52 everyone around me now if I in five and I receive four I will accept it and become four but five five and i receive six i will refuse it because five is better than 60 you know we have two or three simple rules copy debug or rules your right foot or more about trying to set an integer to universe and receiving difference and that’s enough to produce the director gradients given of course a bit of an asymmetry where you have a source said the source of the ordinance which is he nervous and moved on so wrong okay so not everything is experienced serpentine you again I’ve made up of choices but the essential is here and what weight without for them that’s how the painting happens the same painting why am I agree I am great because I received seven from this the North source I receive free from the West store so I have 37 hold and the road inside me tells me that if I have those concerns that econ grade right this is the same painting and the same painting is of course the result of in a physical GRL opportunity to purgatory network you might not recognize the gene regulation network i showed earlier in the scheme of the DNA because this is a force in Russia simplification of it but still there is the idea of grn here gene regulation network wear jeans are going to trigger other genes and so on asian fit for fashion in that case begins not

fair enough the what yarns very often but the ID also here despite for the reservations and the extreme simplification apology there is still the idea that there is erm that is creating the painting i was talking about earlier meaning that sell differentiate the differentiate into right or into blue bar into brain depending on where they are and how do they know what they are with the brain in service right so so this picture this is that is a checkerboard or three by three is in fact you can see that it is still in here and it’s always there so what is program in the ways of these identities of the ways of this job and sexist ambitions okay so they are set painting the swarm is sentencing but not in a random window stripes and spots in erection is usually by reading a program by executing a program that reads the position okay so and the mechanics by the way I didn’t even say the mechanics with simple Springs mask or the case anyway so now this is the 3d version and subjects for the sheer pleasure that’s pretty but because we want to do something with those creature just more fun to you up them that we want to see if we can make them do something in the physics engine that I will show you the site so this was with Carlos such as in Moraga ok so far out save up same thing attitude since same thing as into these so we have we have a series of discs but the sphere is also submerging itself into different regions and different polymers why is it doing that because there are six source of ingredients this is just one thing show right now the south one okay not diffusing the propagating those integer that you see here and this is how says read their self establish position and infer their okay so see value you might US and canada in example you might ask to book a word of the sources come from yes and how are they are they positioned good question also indeed in the beginning we have them already we have the six or so we have we start with board of six things we don’t go all the way down to one but we start with six horses and then the source positioning is also self organized so there are other rules that are specific to dinosaurs and when you have your flat iron source then you need to do other things than when you are not desert and the source kind of pull away from each other so they kind of swim up the gradients but because integers are growing the greatest sense of self is ranking run away from north and west is running away from east ok so the sources are also establishing their own station positions to kind of spy you know stretch and fold like a tent and fold the accordion system alright so it’s already set for tonight yes it’s that kind of changing the symmetry breaking problem a little bit cheating cheating well certainly the fact that we have gradients of different colors that are going to be you know each cell is going to contain six counters is certainly already by definition installing a symmetry because North is going to be somewhere in south somewhere else bench let’s see but I wouldn’t call it cheating it’s because presently this is and is not homogeneous this system ever self has stage four cells dead for says they have different information from the labor they contain those integers that tell them where they are and so necessarily the whole thing is is completely heterogeneous by definition okay anyway so moving on then oh this is the after the body plan you can grow limbs this infected an image from a little coin here so this where only the big areas the main regions of here dear face and then go down into detail this is his one keith was far anyhow never you actually works is but we found little details in the mercy skin way all right at the same time that the canvas is extending so in fact the skins always the same scale of one set but since the canvas is extended in fact this canvas is very small this one’s bigger 11 isn’t there and so it’s completely fractal if you wish but non-citizen it off right anyway so i pried loose in here by now if you are blue or pink then we are going to start a new the jar and program and start having different mechanical

properties if you are blue or green such that or it grow now this kind of nerd life happened age and so we go away from the blood from the disk because now this is where the painting the genetics is influencing the 13 the mechanics the genetics who you are where you are is now feeling back into what you do ok white worn we war is going to affect what you do and what you do is pour it in faster adhering differently with other colors and so on and that’s how you get shaped that’s here that you can shape instead of just browse it where you are and what you are we in France what you do and what you do we take you somewhere of you and your culture offspring because your to die and all that crowd is also going to different do something extensive all right you see the bit the world that one pattern here and gone and this is the 40 know ever since I’ve ever said it I’m not explaining it up again a lot of details and so on instead of it been correctly and complicated i must admit but see I since i’ma show this to biologists innovate they afforded the never consider this to be bad things complete to computer scientists crazed sanity and so on and when I show this to computer scientists that they says way to biological multimedia say I’m always caught in the middle is terrible but first we’ll hear the genome those two says that were kind of pushed you know carbide and have them set divided of compositions bit artificial to say that this and adapt but anyway this isn’t in universities you know they ended up here genomics dates are in exhibition space of their their grn their generation effort they have executive different paths of regulation meaning that this one is a I deliver send that what is the brains okay and they have executed different genes inside the genome you know that the genome the big book that every set is carrying is in fact used I mean the set is using all these tiny bit of it completely for getting so many chapters know so sex as the differentiate start specializing and looking at just a few pages of the big book and forgetting most of its you know most of it is not used by because it they say okay I’m going to be an herbal sensor I’m going to focus on Chapter seven and then Oh Part A and then step biography and so I’m going to go in the you know in dust or debris and so on so so they define our way inside duration space of the journey and that’s how they become different colors and end up in different spaces so anyway so this is the 3d version of it moving on and this is the complete movie of the developments and how much time you have still not Natalie’s started at four and it is now start the past 10 minutes okay thank you yes I we manage all right so this is the 3d and okay so why free now now let’s let’s move on to something something interesting so in 3d this is the developments in virtual pour in the egg or in the world or whatever the metaphor is sorry the movie needs to start again and to click here yeah so this is the 3d version of what I had explained to you in two demos booked so you’ve got it there is a body than there are lives going out evil even we might not have gotten all the details because I didn’t explain all of that but again is that every ever set here is hearing the same genome but executing that you know different inside is the set of parameters and regulation depending on where they are and where they are is the counters they receive from sources written myself fine now we now it is hatched okay and put in the world so it’s not developing in the world develops a party and then it is more and put on the floor or and now we want to test in this physics engine very simple environment there is a hardwood floor there is a rabbit gravitational field maybe there is not checked here okay own and that’s it and the rest is the creature itself which is now also contains the 3d case not just it’s not just actors that also has the mechanical structure it has a skeleton and it has muscles all right so at least of those

will be here too much ammunition it’s in time so what we do here we do to two experiments that the PTA would object to problem we here we dissolve the flesh of the creature and here we go the opposite we spread it off its bones are in fact maybe we have mutated them in somewhere but anyway this is very easy done why is there gone in the first place because the radius says so you learn about the inside it should be proper out there is also some lines that said if you are this is some of the the support axis of the advantage is not exactly but imagine this central axis and the averages also have the radius or worse than east of north and south and since all so if you receive about the same counter from West Indies that you must be bored you must be inside the samp relaxation of radiance you know can can can map everything won’t reproduce so we have decided to differentiate itself that are somewhat in the central axis is that mean that it into bones meaning that their edges are no more to sprint but our sticks now okay so we can do that so the creature is bringing with it those morphological and structural constraints in this world now the rest the other edges and here we were very broad OTE to its knees and because we have several hundreds of cells and thousands of edges it was because was repenting internal sent it to a cluster capital that was really wizard this is this work so all these interpretations you see everywhere okay so these are muscle edges so there are really sprint kind of flexible Springs and these white edges are special measures that differentiated into bone but so now we put the picture in here we remove the fresh by just disconnecting with the you’re saying that for the the muscle edges in fact disappear within us like this and here it has actually how the skeleton is resisting gravitation there is repetition putting it down but it’s self segments sponsors resisting it so that’s a good sign and in fact we have the econ final proof that the skeleton is also necessary if we remove it if we do not differentiate the red edges into what if we keep them more right than all mushy okay so it just it just kind of spread on the floor so we do need the skeleton and that’s that’s just to show you very first steps in having fun with those creatures in a virtual business now now how do they move how do they move here in that case we didn’t do sophisticated in a brain body coevolution or there is not even evolution here we have design that you know by hand by the way this is this is a handmade preacher once handmade is the genome Chris report but we have so far designers you know such that it will have four legs and zone but it’s not nothing I brain body Cody government or bright body coevolution the animation part here is so pretty standard we just say that the Muslim edges that are at the base the roots of each name cancellation shooting in fact according to kind of pig and kind of pirate here also with the pregnancy of the north-south radius will tell you shorty how about it those edges which which just which okay so that’s a contracts will make me the pressure to kind of sure there’s a basic slaves and with collision on the hard floor start moving this acute naturally happens if you issue Ted all I metal you type you put in the genome the fact that if you are a pizza then you should also touch its omission of it what’s up raise it so it’s not moving and then co-writing with this time so far so good and then let me continue so we have a fitness but already sitting one you know fitness for isn’t that that’s about a negated give it I we should do something better after that for example the pressure is a story it just manages to move forward and kind of kind of not not wider problem that just is able to walk and move forward so why not this is can be the fitness but so we now right into problems here I think that little regard here shape or productivity which we have achieved because every time we run this genome we get in safe or I get pretty wrecked by development movement doesn’t mean interesting enough behavioral possibility so we had we were surprised that the twin individual from this one will born you know simulated in another run which are the same structure okay

would walk a little differently and would end up with a different Fitness because we are venturing now in a very difficult day right now which is the fine grain find when complexity can get complexity inside as I was saying the beginning we don’t have this about in evolutionary works or imaginary world when I before that is internally complex and so we are fine grained and yet at the same time any two cars were in because the now the exact placement of the cells of tip of them might matter in how you have troubles or moves around so maybe there is a bit of a chaotic effect here that small variations in the in the granularity of the tips of the name might create bigger effects and how it moves so that’s why we took it to the to the blacksmith and we fitted it horseshoes so now we put little partials here to avoid this kind of cannot feel stochasticity in what exact said is exactly where is going to make the Creator more so we tried with Harsha’s impossible was better so this was without horseshoes try to study also the trains it created on the floor and try to understand what was happening and then resided look if in after that next book horseshoes retractable so rigidify it’s not just fortunate that she moves to me we also will also add it to the genome hey purple cells rigidify you know become become whole okay become or just don’t be most a little more its 22 anyway so we finalize it was better it was more predictive it was more that the same species okay would walk in the same way alright so it was a little better a little better and so like then we were ready to put it in a task that was a little stacking or investing less boring that a flat floor stairs for example and so we pass our picture to agree we have didn’t pass anything just started making its tiny made as usual he does and see what kind of stared you know so a few movies of that the horseshoe creature climbing stairs then these are the first literal steps in exploring after all this tremendous day for exploring parmiter space we don’t even have evolution yet we’re just you know very very beginning of exploring what happens if we vary the links office and by the way very good size only means in that case its developmental or forget it means stopping the proliferation of cells at a certain point I didn’t even tell you how they stop what if you’re writing they do that by sending each other a signal and studying for everything even so its board in the developmental dynamics and that you know that you can regulate in size but it’s an emergent thing but anyway so what if we vary in size indirectly we get maybe something a little better for name of size two end points it looks like those martial arts slightly better at driving stairs what if we modify body cells also we can have the thinner fatter but it is longer or shorter lies you can move from you know daddy long legs to two characters big hunger garbage about dogs around in the Capuchin but this is this is a bit of evolution but quantitative mutations positive you know variations around the same body plan it’s always a for ago today we haven’t done yet more evolution than that I have it 2d a few years ago I skip that order I hope I have Chloe off in effect is here this is just the 2t experiments that we hope to do in 3d next we haven’t done yet we’re in that is mutations are more interesting because the original don’t just you make links thicker or thinner but they add new leaves or the remove these are they they start you know having different body shapes and both body plans you know so we can play always with the same idea of the genome inside of Ariana we can obtain really different architectures this is handmade examples into the handmade the genomes and not the simulation jiangsu me and we want to do this in pretty soon and to also make them to interest instead and see but all that is a big endeavor because this is this is where I think that if this is all exercise and why are we bothering you know doing all this is huge simulation with a lot of little elements and for what for behavior that is not experienced in so far describing stairs but I think that it needs to be investigated further I really believe that the file realistic the internal

complexity of the individual is essential if you want to attain structure in addition start for innovation meaning a new name like that is its fields always have freedom being kind of statement is fun but if you think of weird creatures and where did Hairston formed feathers and scales and the tail and you know I the eye has been rediscover by bhushan many many times of different species you know where do all these structures these organism or structures come from villages and organs and tissues of all kinds they come from the smallest building blocks that are the cells ok there are not before sea or in a tree designed by some designer as we are in the case of Berkshire devices and then parameterize it’s not like there may be a hair here and then symmetrel optimizing event we don’t even know that there is going to be a hairy so new features truly emerge emerged from the smaller building boats understand was any of the pieces of the puzzle that’s why I think it’s extremely important to to to go through this if effort of will find ray going fine grain if you want to break the glass ceiling of evolutionary innovation and and let our machines are designs find their own sub structure of themselves that we have an even thought it’s also poker and evolution but so you don’t have again we don’t have the sticker that you have thought about in advance you don’t even know because those pictures are really emerged that I’ve already invested anyway so this is this is why things effort is still worth trying and every stuff here I will not show synthetic biology sorry and we have done very little anywhere just show Susan’s that needs a vision of her own room size proportion she asked an artist to draw this that we submitted a project to to new york and co you cover a conventional computation we published an abstract about it anyway so this is a business America opportunity engineering that is good bacteria synthetic since synthetically modified but here at all or any other says one day I could could could be you no could roll of this of course they may be like racial horse won’t you talk to me about but but this is restoring the idea that could we steer synthetic biology from just security new substance to form a new structures same ID but instead of simulation instead of physics engine your screen in that is back to the bioware okay back to the by we’re reprogramming really matter so instead of software by or the same IDC money anyway and also wanted to show here this idea about the networks also morphogenesis button that is different space I’m sorry rushing on this because I it’s not pain but instead of 3d and we were now back to 2d and were compared to a super space which is Sarah automatic between the CID has car break-ins being also exchange between those nodes those pixels that from one by one and that is where are we do I brigade in a specific way so this is the pure perfect shape that we want to obtain and to obtain that every takes a little cut they come in one by one but instead of the diffusion limited aggregation you know that if you da one which is random and you get those interesting branching patterns this is programming integration so not for possible that is the not for places are possible account already anywhere you want you can I really funny to wire there is an open open slot and open port and why would one except be open to you and wreck it into it because it has read its gradients and civil casual important and then you’re ready for someone to go okay so that’s how you get programmable aggregation always the idea of programmable cell organization for our motivation here and an interesting thing is that we we experimented here without forget about you taking these words of affirmation and getting this is the white side the perfect shape and a new taser here randomly that is there a strong emotion you’re through mutation and value the other one there was no troll mutation illusion the random imitating the rules that was pixel so that a to agree a to each other and looked in different kinds different species different species that in that case are able what is the charge here the church is not to climb stairs the challenge is to go roll around obstacles this is the challenging role around obstacles those obstacles are written

works so the pure one is not able to grow around them because it’s so pretty hard to wire I mean it once wrote there itself chemical problem now the newsagent wats take the rocks into account and are able to grow long and this is another exercise the more for genetic engineering in that case with the added environment constraints that we didn’t have very much in fact what at all in the growth of the creature we did have an environmental constraints during its world we have there later on when it was moving but here we have environment illustrates why these whirling what it was and we can do a version of that spoken so just a brief and here we go so thank you to Union body bio modeling to Paris for the listing and for us will support with this time she bought a very good zone and obedient Martha we’re working on on these network or listen to thank you for our patients