 Okay, we're rolling. This is so strange. I'm sitting at home in my dining room talking to a computer screen and I'm teaching this year's edition of Beyond Networks, the Beyond Networks lecture. This is my first recording, my first recorded lecture ever, so I'm going to try really hard to act casual as if I was in a classroom and you'll see that it probably feels a little awkward. This is weird for me, this is weird for you, so bear with me, I'll hopefully get better at this over the semester. My name is Jovi Yeager and I'll be your lecturer and I want to start this lecture before I tell you what it's all about in this first module by introducing myself and here's a little map of the earth. I started out in Switzerland where I studied, I'm from the Swiss mountains, where I studied in Zurich and Basel, I studied biology and was trained as a Drosophila geneticist originally. I was rather frustrated with the sort of explanations that were going around in the lab I was working in, so I looked for a completely different experience and on my search I found this place called Schumacher College in the southwest of England in Dartington and Devon where a biologist named Brian Goodwin was teaching at the time, so I did my master's with him in holistic science and this has nothing to do with hand healing but it has something to do with systems biology before it was really called systems biology. I'll tell you more about that as the course goes on. This was a really a head turner for me coming from a traditional genetics lab to see how you could see the world with a completely different perspective and this is going to be a common theme throughout this lecture that you can see the world from different perspectives and they don't compete, they complement each other or they just coexist in the worst case. So after this sort of career defining year in this wonderful place in England I went to the United States to the east coast just outside New York where I did a PhD at the University of Stony Brook and I learned to mathematically model gene networks and the models I was making were based on quantitative data that we were gathering in the lab. So I worked in the lab and taught myself mathematical modeling at that time. After five years there I moved on to the Museum of Zoology housed in this absolutely wonderful brutalist building that's now been beautified the last few years with a whale skeleton here where I did a postdoc trying to use the methods of network modeling to study the evolution of gene networks. So this got me to what was my original sort of drive to get into biology to study the evolution of complex regulatory systems and to my big surprise after two and a half years of that I got an offer to open up my own lab in Barcelona and Catalonia and Spain right at the sea. This is the building we were working in at the Center for Genomic Regulation and I had a research an empirical research group there for seven years that basically continued this work of looking at the evolution of gene regulatory networks with both experimental and sort of modeling approaches. Then came another life-defining change so these are really important here because I got the opportunity to spend a year in Berlin at the Institute for Advanced Study or Wissenschafts Collegium German where I got exposed to all kinds of different views on the sort of topics that I was looking at so from people artists and people from completely different fields philosophers. I also got a job offer during that year to change my career completely and so I moved to the vicinity of Vienna to Gloucester Neuburg where I'm sitting right now recording this where I was the director the scientific director of the Conrad Lorenz Institute for Cognition and Evolution Research for two years and my aim there was to bring together two different perspectives again that of the philosophy of biology with theoretical biology so basically instead of mathematical biology I moved into an area that was more philosophical. The theory doesn't have to be mathematical this is another big topic during this course. Unfortunately I had my differences with the board and the president of the institute I didn't share their vision so I left and have since then been leading a nomadic life as a freelance academic. I've been continuing my collaborations with philosophers in different beautiful places one is the Complexity Science Hub in Vienna. I spent some time in Dresden at the Center for Systems Biology and in Paris at a place called the Center for Interdisciplinary Research where I started to get really interested in the activism and movement towards a more open and less competitive academia and science which is a very interesting important topic to me and you can talk to me about this if you're interested. So at the same time I started giving workshops as a freelancer in philosophy of science for scientists and also on creativity based on a philosophical model of the innovation process which brought me back to Vienna where I'm teaching this class and where I'm working with people at the institute for philosophy on issues of open science innovation and the sort of explanations we use in biology. So I do all of this with the common topic of being interested in how we explain phenomena in biology and this whole course will be coming from that sort of point of view to reflect how what is an explanation? Why do we use certain explanations over others? Why do you use certain experimental strategies and can we say something by comparing different perspectives on life? Can we learn something more about what life really is? Okay and the last thing I've done is I spent I was supposed to spend two months but I only spent a bit less than a month the last few weeks actually in this wonderful place in Stelenbosch in South Africa where I started to write a book about this course on the philosophy of science for scientists that this is not going to be the topic here. I had to return rather precipitously and quick because of the coronavirus situation and so I've been back here in Cluster and I worked for the last three or four weeks preparing these online lectures. So you can see that maybe two things out of this super short biography one is my sort of path has been a path of exploration. I had no idea that I would be where I am right now and so I think this is something that academia is supposed to do. It's supposed to allow us to explore completely new directions and follow those directions when they come up. These these sort of directions are unpredictable you cannot and should not plan your research career completely in advance because this these unexpected turns the unpredictability of your own future is one of the main things that will be driving your research career. But enough about me this was just as a quick introduction the actual topic of this lecture is the following. It tries to sort of refocus us on the fact that we live in an incredibly rich and complex world and I'm going to use throughout the course this metaphor of the jungle of rich and thriving jungle it's it's lush everything's changing all the time and it's a big mess it's very hard to understand this so we live in this sort of jungle that is our world and this is amazingly it's amazingly beautiful and mysterious okay so it's amazing how much there is we don't understand and a lot of people are afraid of this fact but I am fascinated and I'm teaching the sort of philosophy of the unknown in my courses that deal with creativity and innovation so one main theme will be here that we have to focus on questions rather than facts so this course will not necessarily teach you a sort of a set of specific facts but it will hopefully make you wonder and ask questions about the way you do research the kind of questions think about the kind of questions that you can ask and reflect make you reflect on what other people maybe think and why it's good to have different perspectives on perspectives in such a complex reality it is hard to understand it's unpredictable okay things always happen not just in my career but everywhere that you cannot possibly predict this current coronavirus outbreak was not one of these things okay it was very predictable but other events in your private life and in society in general the financial crash of 2007 were hard to predict and people missed the emergence of the internet and so on and so forth okay so the future is open the future is predict unpredictable and this is because the world we live in we haven't even started to understand it properly but what has happened over the last few hundred years is something called modernity okay it's being you know first the scientific revolution the enlightenment and so on and so forth are extremely technologized society today has started to replace this this sort of mystical admiration of nature that we have before with a completely different view and it replaced the complexity of the reality again with a sort of a fake and oversimplified simulacrum okay now what a simulacrum is is a sort of a sketchy representation of the real thing okay maybe a cheap imitation and it doesn't really do the real thing uh justice it's like the simulacrum of a famous statue this is a bad fake okay it's easy to see that it's not real and this is what our view of the world is today so modernity has replaced the actual complexity of the real world with a very simple view that aims at understanding completely and controlling the world so we want to understand the world to manipulate it we only feel at home in our world if we have it figured out i'm like that if i move to a new place which i've done many time in my life i have to figure out the place i have to go sniffing around in all corners until i know my surroundings and then i feel at home okay and this is natural this is what we've done but sometimes we forget that we've done this okay so the view of the world that the scientific revolution has given us is based on metaphors and our main metaphor and this is important is that of a machine okay this started with René Descartes will talk about it a little more during the the course but basically this idea that the entire universe is a mechanism a sort of a clockwork comes up during that early modern time about 400 years ago and has been taking the western world and then the rest of the world like a revolution and so this is a metaphor this is very important we're gonna talk a lot about metaphors my metaphors are important to gain new knowledge their tools to to understand stuff that you don't even have words for but at the same time they are not the real thing they are a simulacrum off the real world okay um we even treat ourselves nowadays uh as machines as clocks you know you you optimize your time you go to the gym it's terrible i hate the gym okay you you uh you don't want to waste any time like what what what does that mean wasting your time you know um the things that i thought were important at any stage in my life turned out to be not the things that really mattered it's really hard um to optimize yourself and we we put ourselves under a lot of pressure i think we're not entirely happy although we have it better than than humanity have has it ever had it ever before um we have lost the ability to just enjoy the mystery and the awesomeness of being alive uh in this amazingly incomprehensible world here's a little book by the way by julien frail de la maitrie which is called l'homme machine and he says and this will also haunt us again later on during the course that organisms are quite easy to figure out uh they're basically just clocks that wind themselves which is true but as you may have noticed there is a lot going into this self winding aspect of the clock and we still have absolutely no idea how organisms actually do that we'll talk more about that later but basically we don't only treat ourselves but all other living beings as machines and that's a problem and has led to atrocious industrial farming um a lack of respect for the living and all kinds of other problems but even worse than that um we treat our social systems our economy as a machine that we can manipulate um you know fiscal and and monetary policy we're trying to um control busts and booms and recessions and then something comes along a little virus and everything goes hey why or why is that that is because we have mistaken this system this complex system by society and our economy for a machine where we can pull a few levers and control its performance this is completely impossible okay this is sort of one of the messages take home messages of this entire course so the worst thing that we do is that we treat the ecosystems on which we helplessly depend as machines okay we exploit them we use them okay we release genetically modified crops into nature without having a clue how they work and how they spread ecosystems are absolutely massively beyond our comprehension so we should use a sort of a cautionary principle here if we don't understand something we do something that is potentially really really harmful we should not do it so this sort of view of the universe as a machine as a clockwork influences a lot of the crisis we have produced in the last a few hundred years so it is exactly because we we consider our world as manipulable in our control it leads to certain hubris we overestimate our capabilities and we screw up and we create crises come back to that in a minute so we helplessly depend on these really complex ecosystems that we're destroying and we are only now slowly finding out what it means that we're destroying them we have no way of replacing such what people with economists call natural services if you're worried about viruses and climate change you should be worried about the massive decline of insect species all over Europe and the rest of the world pollinators all kinds of problems we have no idea how this whole complexity works together and the effects that we're causing are systemic everything is connected it's not like a machine where we can replace parts and manipulate parts and optimize the performance at all so part of this whole movement of modernity this metaphor of the machine is that we build oversimplified models of our world okay the best example and it's always nice to bash on economists of course the dismal science it's called is rational choice theory which is for decades has been the mainstream in economics and it's it's simply these are theories that are based on the assumption that human beings act in a rational way okay they make rational choices that optimize again optimize they perform like machines you know they optimize possible outcomes there's two problems with that first humans obviously aren't rational beings or not entirely so and also often we don't have the information that we would need to optimize a potential outcome so what we're doing is we do this we're decision making with insufficient knowledge and that's what we do in science we don't like it but that's what we do we don't have a clue what's going on we've made a lot of progress over the last 300 years and science is a great thing but we should never underestimate the amount of stuff we don't understand so rational choice theory genetics developmental and evolutionary genetics is another oversimplified model of the world okay so the idea that the genome contains all the information to determine your behavior your phenotype is a complete joke there is no evidence for it there has never been and it's massively oversimplified as we will see in the course of this lecture and completely wrong so why why do we stick to such models like rational choice theory and genetic determinism genetic reductionism why do we stick to them and the reason is maybe twofold these models are powerful tools for manipulation that's one reason okay so genetics works for all kinds of things we have a revolution of CRISPR-Cas9 all over the news we can edit genomes now we have tools again just like with releasing GMOs into the environment we have no idea what we're doing okay even with these specific sort of manipulations the effects of those manipulations large scale are completely unpredictable and unknown to us so lots of ethical problems there but very effective rational choice models allow economists to to suggest policies that politicians implement and they often seem to work although sometimes they don't and we don't know when they don't that's one of the problems with this whole view because if we mistake these models for the real world we start to believe that you know genes determine us we start to believe in those economic models as a sort of a real a representation an accurate representation of our world that's when the problem starts they're not a good representation of the real world we are mistaking the map for the territory here and that has dangerous consequences okay they create a dangerous illusion of knowledge and control we think we know more than we actually do and we start to lack the necessary humility and precaution that we should show when we face a crisis which is beautifully shown right now during this virus coronavirus crisis when people are saying oh we should not stay home it's not going to be that bad the risk that we we run by not staying home is so much larger than the risk that we run if we stay home that there should be absolutely no questions by the economic damage of what we should do and so this again has something to do with decision-making in systems in situations where we have absolutely not insufficient we have absolutely insufficient knowledge and if we think we know what's going on and we can control the situation we're fooling ourselves foolishness is going to be a big topic in this lecture in general so this is the map behind me here a little detail out of this map my kids are teenagers now with a few years back when they were smaller they they drew this massive map of a world where their stuffy stuffies live their stuffed animals and it's a typical example of such an oversimplified vision of the world in this world nothing bad ever happens everything is ordered everything is clearly defined nothing unexpected happened happens it's a safe a safe place okay and somehow humanity has never grown up my boys have now grown out of this space they're facing the real world bravely but but parts of humanity and a large part in every one of us is refusing to sort of grow up from from this fantasy world that we've created but the problem of course is that the world we have built around us the view of the world is simple but it's also extremely fragile and this not only happens in science by the way this is these are political views that we have are absolutely completely inadequate um uh and we see this um this by the way is a piece of art it's called heap of rubble by Christopher Zeeman and so what's happening is those uh illusions that we've created over the last few hundred years are breaking down all around us at the moment um which leads to a bunch of sort of cascading and really pervasive crises that we're suffering right now so on one hand obviously there's an ecological crisis i've already uh uh painted that a little bit there's a socio-economic crisis that's also a political crisis the rise of populism our economy is crashing now just because we don't buy stuff we don't need um this is crazy i mean we've built a system around those models that we have the economy we've built an economy that's optimized for efficiency but it's way too fragile to to sort of survive in the real world of unpredictability complexity and on top of that obviously because our models of the world are failing we have created uh what you could call and John Rovaki has called a meaning crisis we have lost our bearings have lost our meaning uh in this world and that's because our old views are breaking down okay there's a great youtube channel by John Rovaki which is called Awakening from the Meaning um not for the meaning crisis but from the meaning crisis sorry for that um that you should check out if you're interested um post these videos on youtube and we'll provide links um to the sources i site uh below the video so another thing that happens because of this breakdown is that um here is a wonderful quote from the best selling philosophy book of all times Harry Frank for um his essay on bullshit it's very short you can read it in two hours i highly recommend it it's an actual philosophical series of philosophical treaties and he is um saying that one of the most salient features of our culture right now is that there is so much bullshit we'll talk about bullshit especially in science in a bit so instead of facing the complexity of the world changing facing our uncertainty about uncertainty and really being serious about having to change our ways that we have no control but there is no predictability what we're doing is we're retreating more and more uh into a world that is completely removed from the real world and that's the world of bullshit there's a short video linked below on youtube that summarizes Frankfurt's work beautifully as well and features an entry um with him so another source on bullshit is the forthcoming uh book by Carl Bergstrom and Jevin West calling bullshit which is um specifically about data-driven bullshit um that you've surely encountered during your studies already um i highly recommend following Carl uh on twitter and checking out his website um calling bullshit.org the book is not yet out but will be in a few months so these are problems we are deluded we are deluding ourselves and we are refusing a lot of us are refusing to exit the delusion okay we are pretending that the world we live in the world we've created is still adequate and represents the complexity of the real world but so why why do we desperately stick to this simple illusion okay one reason i think is that we see no alternative there is no way out what else is there except to to you know be open to this frightening horrendous uncertainty the world gives us unpredictability to be hopelessly um at you know the the you're not in control okay so this is this is really hard for us deep down to to admit and we have to find a more participative mode of interacting with the world than that of manipulation and control this is something my old teacher uh unfortunately deceased uh brian goodwin he was always stressing back when i was uh studying for my master's in 1999 we have to switch from control to participation we cannot anticipate we can only build systems we can judge when to be careful and when not but we cannot anticipate exactly what's going to happen next so another source that i highly recommend is a is a very sort of funny movie it's a documentary that could you know would profit from a bit of fact checking here and there but it's general message it's it's really clear it's it's called hypernormalization by famous documentary maker adam heard this and it's it's exactly about this situation hypernormalization is a term coined by a soviet anthropologist at the end of the soviet era where he realized that nothing was as it was supposed to be but nobody nobody would believe or buy into the propaganda that nobody saw way out and this is where we are this is the message of the movie at the moment in our what you could call a late free market capitalist consumer capitalist society so we know our model of models of living of understanding the world or breaking down but we can't get out and so we live in this situation hypernormalization we don't see the world as it is but as we see our models as more real than the real world which is a real problem you can watch this movie for free on youtube it's quite long though so we all have a choice okay we don't have to play along it's up to you to make that choice here is morpheus giving you the red pill or the blue pill you really should read john broderias simulacra and simulation which is the philosophy book that inspired the matrix um so what's happening here okay we are refusing to take the red pill but we need the red pill philosopher charles taylor wrote the book called a secular age and he writes about the disappearance of the religious worldview and he said he calls this modernity as the great disembed it so we were embedding embedded before in a mysterious sort of world and it was full of mysticism but on the other hand it wasn't pretending that we understood what was going on so what we need is a great re-embedding at the time we need to at this time we need to sort of see the reality for what it is again and there is no mysticism required you don't have to be religious to do this we as we shall see during this lecture can do it by just looking a bit more uh or the different sort of set of eyes uh than what we usually do so we can take that red pill and i hope um you're going to follow me taking the red pill um into this course during this semester another series of books that i highly recommend is nasim uh nicolas talab's uh in church though series especially start maybe with antifragile or the black swan um and these books talk exactly about the fragility of the systems and the models of the world that we have right now and what we want is antifragility this is not resilience or robustness which merely survives uncredible unpredictable shocks but it's like your immune system something that can improve and learn from such shocks this is the kind of society we should build and actually uh antifragility is extremely important for biology because the systems that we know of that are antifragile those systems are mostly organic unplanned self-organizing um living systems or systems in which living beings cooperate in specific ways so we're going to have a look at that during this course as well so we're going away from the machine metaphor machines are never never antifragile they're always fragile they break down all the time they need maintenance we don't want to look at our economy our ecosystems and organisms like they are machines they are not because they are not fragile like the mechanisms and the machines humanity has built um you can take this even further so Taleb likes the German philosopher Friedrich Nietzsche very much and he has an absolutely brilliant and extremely short passage in this book The Twilight of the Idols that is called The History of an Error and it tells the story of how the real world that is the fake world the ideal world that we've actually built around us finally became a fable Nietzsche talks about religion but we can use it and extend it into modernity it takes five or six steps the first step happens with Plato who comes up with the allegory of the cave we'll talk about this as well in the course and and he says the real world the one you live in that you experience isn't real okay that's just shadows on the wall and to see the real world the which was played out the world of ideal forms you have to be wise later on the church said you have to be pious or virtuous to see reality as it is as a second step in history the real world with Christianity became unattainable for anyone for now but it's promised if your wise pious and birches during your life you will go to heaven so everybody was neglecting real life the real world for something ideal that they thought was more real the third step is the real world becomes unattainable unprovable unpromissable you can't promise anywhere anyone to get there but the mere thought of it helps us to get by consoles us and obliges us to be good people okay which ends up in Kant's categorical imperative and so this is the world an sich as Kant calls it okay but we cannot sense it we never see it we never experiences it's transcendental it's beyond what is important in our everyday lives but it goes further the positivists come along they'll talk about those for sure in the coming lectures they say the real world is not important because you can't attain it it's unknown we don't know what it's about it doesn't give us any consolation no redemption no obligation and what we cannot measure what we cannot experience doesn't even exist okay so this idea is of no further use and all free spirits this is Nietzsche's own view of course let's do away with this ideal world but it went on and on and on 150 years later we still live not in a religious imaginary real world you know this idealized real world but we still have it today and it's our scientific worldview at the moment and mechanistic view of the world but the problem is so now that we have done away with this with this ideal world what is left an apparent world no with the real world we have also done away with the apparent one the apparent one being the scientific the simplified worldview that came with religion a view of certainty and control okay that we have to let go if we want to get out of this current crisis of humanity we have to embrace the world that we live in just like the ancients did but with the information that we have today so the great oversimplification affect science and especially of course biology and the social sciences in physics simplification often works if you're not in condensed matter physics or some other complexity science related part of it um you could even say physics unfairly picked all the problems that were um sort of amenable to simplification right at the beginning of the scientific revolution and left us biologists with all the rest and the approaches of physics like reductionism they just don't work in biology this the central topic of this course so today of course we no longer use clocks as machine metaphors but the cells and organisms have become computers important again to note that all of this is purely purely metaphorical okay there is no reality to it in any sort of sensible interpretation of that term so we think that there are molecular machines in cells that run genetic programs they'll talk about this metaphor of a genetic program a lot genetic genetic programs don't exist and they are no longer useful as a metaphor today except for very limited cases very specialized research organisms become optimized through evolution by natural selection also not true um that's all just a bunch of metaphors that's not real science okay and they're not very good they're failing us right now we need better metaphors we need better concepts and we don't have them yet so one of the problems I'm gonna have here is I'm gonna criticize a lot but um we need to sort of reset the system before we can start developing a new view um which I will do towards the end of the course of course so we need to move away from this idea that organisms are machines because they are not they are not fragile they don't function like machines at all there's many many differences we'll get into those in due time and they're very uh uh essential but nevertheless okay the network that remains our dominant metaphor in system sciences okay and this metaphor again so this we use it for living systems for systems they form part of ecosystems social systems our economy anthropologists work with networks everything is a network nowadays and it makes us feel good we are we are going beyond reductionism we don't only look at the single parts but look at this this is still the machine it has parts connections you can switch the parts around um living systems uh are not networks the network metaphor comes from biology straight from engineering um machine engineering electric electrical engineering and of course mechanistic physics that has been superseded over the last 100 years by other theories like quantum physics and relativity but not in biology we're still stuck in these mechanical sort of metaphors engineering metaphors so the problem is that cells organisms ecosystems societies and economies they are not networks okay and that's what I will try to convince you if you follow me into this course we will explore um organisms living systems and their evolution beyond this metaphor of the network I've worked on networks for a long time in my career and I think they're an extremely useful tool again to model certain aspects of biological systems and their evolution that they are not organisms are not networks they are not machines we want to look at what organisms really are and how evolution really works and how little we understand about that so please join me in this exploration uh in the following it's going to happen in the following sort of 14 modules what I'm going to do this here is I'm I'm going to record this is a long lecture now but for all of the other modules I'm going to record short lectures hopefully 15 20 minutes long about um aspects of these 14 uh different um uh topics here well one is the introduction I should say 13 different topics the introduction includes this video plus a little video about the purpose of my teaching which I will also upload shortly um the following two uh lectures are uh laying the philosophical foundations of what we need and that may appear a little strange it is a lecture about organisms and evolution but before we can get to those topics we need to clarify two philosophical issues and those are uh perspectives that it is when if you have a different perspective from someone else it doesn't mean you contradict them you can and should have multiple perspectives on complex systems in fact complexity is defined by how many perspectives you can have and they're valid on a specific system the more the more complex the system is okay the second aspect is uh the aspect of process thinking everything in evolution and in biology in general is not a thing but a process everything changes all the time so we need to switch perspectives from object-oriented thinking towards process thinking as soon as we have those philosophical foundations laid down we can look at living systems so we'll start again very philosophically by defining what a system really is and how we represent um uh or or not represent systems by models how we study them with models uh we will then get into very specific models nitty-gritty network models and and mechanisms and and what they do and what they don't do for us okay um I will then argue that mechanisms are uh uh processes okay and and I will show you a way of of uh studying those processes using uh concepts like attractors and bifurcations we will then switch gears and look at how um these sort of mechanisms work within more complex systems that are not purely mechanistic okay how causality flows in those complex systems um and then we get to the main point of this part of the lecture a little argument on how causality uh on organisms are not machines okay they have agency and how they are the basic units of biology we will then switch to evolution and have a quick philosophical look at what evolution actually is the metaphysics of evolution we will then compare three different um traditional perspectives on evolution and see how they help us better understand the process um and uh we will then quickly uh intermittently talk about a big bullshit debate about evolutionary synthesis so I will illustrate how bullshit has invaded um uh science not just the rest of society um and uh I will then finish that part by by telling you what network evolution actually does so we start with some concepts like modules robustness and evolvability um but we'll then move into the orange and the red part of the lecture which goes into new territory and will introduce a new notion of modularity and homology as a sort of a foundation for a novel kind of evo-divo and uh will then uh go to sort of a central theme of a processor-oriented biology and that is the dynamic emergent co-origination of pretty much everything in the living domain as I said you will uh be able to download those lectures from Moodle um and watch them please watch them at your leisure on your own um if you have registered for this course um we will then meet twice a week as indicated uh in the use-based system um to discuss those lectures we I will not repeat those lectures but we will uh do question and answers is probably not going to take one and a half hours each but that's the time slot we have please join us it's not mandatory to do so nothing is in the master's course but it will be useful um these discussions will be moderated and I will introduce the sort of etiquette and the technology of that we'll get a link to a zoom meeting by email and you can also find the times and the schedule of that on use-based for everybody else who's watching this on youtube um thank you for watching this without having to uh and uh I will post the future lectures here in this channel um on this playlist uh if you have questions just enter them below or contact me on twitter I'm doing this uh for free so give me time um I am a slow person I hate being hurried um but I will eventually get back to you okay this is the first part of the lectures if you have suggestions comments uh you contact me uh at these different places here um and the next little lecture is just going to introduce my sort of general teaching philosophy it's going to be a bit less long than this one thank you very much for watching this and listening see you back soon