This is my first lecture in module 6 that is test for influential observations and here is the content of this module test for influential observations. First we will be talking about detection of a leverage point using H i i, where H i i is the ith diagonal element of the hat matrix H and then we will be talking about detection of influential observations using you know Cooke's D statistic and then D F F i t s that is you know difference of fits and this is D F beta's that is the difference of beta values. So, the objective of this module is to present you know different techniques to detect influential observation. So, we have learned about the leverage point and the influential observation in the previous module. Again I will just repeat those things one will recall those things once more. Here is the definition for leverage point. So, I you have several observations like you know x i y i for i equal to 1 to n and here is the scatter plot for the observations and the point. So, these are the points you know in the scatter plot and as you can see the point A here has unusual x coordinate from the rest of the observations. So, this is this point A is called leverage point. So, it could be so not necessarily that you know if you fit a model to the given data or if the this point is exactly lying on the fitted model, but not necessarily I mean this is also a leverage point for example, you know. So, what I want to say is that it is the point is on the is lying on the trend of the observation, but this has unusual x coordinate. So, this type of points are called a leverage point and next we will be talking about influential observation. So, here is an example of influential observation. So, look at this point A here again you know this is the scatter plot for the given observation x i y i and the point A here is this has you know moderately unusual x coordinate and also it has moderately unusual y coordinate. So, this point is has moderately unusual x coordinate and also it is not in the general trend of the data. So, this point is called an influential observation. So, what we learned is that if a point has unusual x coordinate then the point is, but it may lie on the general trend of the data then the point is called a leverage point and if a point has moderately unusual x coordinate and also unusual y coordinate then the point is called influential observation and the influential observation has a significant effect on the model regression coefficients. So, what we will do in this module today is that we will be talking about several techniques to detect a leverage point and influential point. So, first I will be talking about one technique which can detect a leverage point. So, test for leverage point. So, what I will do is that first I will again recall the multiple linear regression model and in matrix form here is the model y equal to x beta plus epsilon and you know the least square estimate of this regression coefficient beta. So, this is a vector you know that this is a vector with k regression coefficients. So, beta hat is equal to x prime x inverse x prime y. So, the fitted model is the fitted model is y hat which is equal to x beta hat. So, this is equal to x beta hat equal to x prime x inverse x prime y and this we can write as h y. Now, we talked about all these things in the previous module but just I am recalling here the same thing again. So, where h is equal to x x prime x inverse x prime and this matrix is called the hat matrix and this is called hat matrix because this matrix maps y to y hat. So, this hat matrix plays an important role in identifying leverage point. So, I told that you know in fact you know the i th diagonal element of this hat matrix that is h i i. So, h i i is the i th diagonal element of this hat matrix and this has an important role to check whether the i th observation is a leverage point or not. So, let me write what is this h i i. So, h matrix is equal to h is equal to x x prime x inverse x prime then what is h i i h i i is the i th diagonal element of hat matrix. So, x is n cross k matrix and let me just write that the n rows n rows are say for example, x 1 prime x 2 prime x n prime are the n rows of this x matrix then in terms of in terms of x i the i th row I can write h i i h i i equal to x i prime x prime x inverse x i. So, you know this part is independent of i I mean whatever the value of the i this does not change. So, what does this measure is that this h i i is this one is a standardized measure of the distance of i th observation from the center of x coordinate. Well, so what we have observed is that you know the i th diagonal element of the hat matrix h i i this one measures the standardized distance of the i th point from the center of x coordinate. So, and we call a point leverage point if it has unusual x coordinate. So, then obviously you know if h i i is large for a particular i then that indicates the i th point is a leverage point. So, the conclusion here is that you know the criteria for i to be a leverage point is that you know. So, usually the high h i value h i i value indicates i th observation is a leverage point. So, and I said that you know of well. So, let me just compute the average value of h. So, I said that if the value of h i i is large then that indicates that the i th observation is a leverage point. So, what I am trying to do is that I am trying to find the average value of h and if for a particular i h i i is very larger may be the double more than the double of the average value then we say that the point i is a leverage point. So, h bar is equal to h i i i equal to 1 to n by n. So, this one is nothing but the trace of the h matrix trace means the sum of the diagonal elements. So, trace of h by n and for this matrix h the trace of h is equal to rank h by n and the rank h this matrix is k. So, the average value of h is k by n. So, as a general rule h i i greater than 2 times k by n indicates i th observation is a possible leverage point. So, next we will be talking about some technique to detect influential observation. So, in case of see in case of leverage point a point is said to be leverage point if it has unusual x coordinate and h i i measure the distance of the point i th point from the center of x coordinate. So, then obviously, if the h i i value is large then that indicates the i th point is a leverage point. But in case of influential observation recall the definition of influential observation that it has a point is said to be influential observation if it has moderately unusual x coordinate as well as moderately unusual y coordinate. So, here we need to take care of both the x coordinate and the y coordinate and cook has suggested a statistic to do this. So, we will be talking next we will be talking about cook statistic to detect influential observation. So, detection of influential observation. So, we will be talking about cook statistic and it is denoted by D. So, it is a distance between two thing. So, what this cook statistic does is that it measures the distance between the fitted response value obtained using all the observations that is the usual fitted. I mean I am talking about the cook statistics for the i th observation. So, what it does is that it measures the distance between fitted observation obtained using all the data. For all the observations and the fitted response obtained without using the i th observation. I mean using all the observations except the i th observation. So, let me write down the cook statistics formally. So, cook statistic for i th observation is based on on the difference between predicted response we call it y hat obtained. I mean this is obtained using all the observations predicted response y i. So, this one is the predicted response which is obtained using all the observations except the i th observation obtained. So, this one is obtained without observation. So, what I want to say is that what the cook statistics does is that suppose you want to compute the cook statistic for the observation a here. That means we call it d a. So, what that d a is that. So, d i is the cook statistic for the i th observation. So, d a is the cook statistics for the for observation a. First you compute the distance I mean you have to compute the Euclidean distance between between y hat and y a hat. So, y hat is the fitted response based on all the observations. So, if you consider all the observations then the model will get influenced by this observation and the fitted model may be look like this. Now, so this is what the y hat you know once you have this fitted model you can get y 1 hat, y 2 hat, y 3 hat, y n hat everything and this is the vector and vector of fitted observation fitted response values. Now, you compute y a hat. So, this is the fitted or predicted response value obtained without using observation a, but using all the other observations. So, if I do not use this observation then my model will look like this fitted model will look like this. So, from here I will get y 1 a hat and y 2 hat and all these things y n a hat. So, this is a vector this is a vector you find the Euclidean distance between these two vectors that can be obtained using this way this is y hat minus y a. So, this is what I want to mean by the distance of I mean the this cook statistic measured the distance between the predicted response obtained using all the observations and the predicted response based on all the observations except the ith observation. So, this is how we get the cook statistic for the ith observation and similarly you do it for all the observations. So, you will get d 1 d 2 d n well. So, this is how we get the d i the cook statistic for the ith observation d i is equal to y i hat it does not matter which one you are writing first y hat prime y i hat. So, you need to understand that you know this is a vector. So, this y hat is nothing but y y 1 hat y 2 hat and y n hat and y n hat. So, this is what I want to mean by the distance and you need to understand that y i hat is the predicted observation obtained using all the data except the ith observation. So, this vector is you know I may write it in this form y i 1 hat y i 2 hat y i 2 hat y i 1 hat y i 2 hat y i 2 hat y i 2 hat y i 2 hat y like that y i n hat. So, if you write you know then this can be also written as this is equal to y i maybe let me use j here minus hat minus y j hat square. Not difficult to understand by K M S residual. Well, so this is the cook statistic for the ith observation and this can be also you know treated as the square Euclidean distance between the vector of vector of fitted values and and vector of fitted I mean response values when ith observation is deleted. Well, and the ith observation is deleted. And the rule to say that one observation is an inferential observation is that the value of d i. So, say you know see you need to calculate all this d 1 d 1 stands for the cook distance for the first observation d 2 like up to d n. So, the value of d i much bigger than others indicate that ith observation may be highly influential. So, this is not difficult to understand that if the d i is is is going to be large for the influential observation. If i is not an influential observation is not going to be much difference between the fitted value using all the observations and the fitted value without considering the ith observation. So, next we will be talking about one more two more statistic to to detect the difference influential observation. So, the next one is the next one is called d f f i t s. So, this is also called you know difference between fits statistic. So, this one investigates deletion influence of the ith observation observation on the fitted values. So, this is the next one. So, so cook statistics also does the same thing you know it it it investigate the deletion influence of the ith observation on the fitted values, but here the statistic is different. So, for the ith observation for the ith observation this statistic is is is defined as d f difference between fits i which is equal to y i hat minus y i hat and we make it standardized by MS residual i h i i. So, here you are only considering the ith observation I mean difference between. So, what is this? This is this y i hat is the is the fitted value of y i obtained using all the observations and this guy this y i bracket hat is the fitted value of y i obtained without using the ith observation. So, this is y i hat where y i hat is the ith observation. The fitted value of y i obtained without the use of ith observation. So, here yeah. So, this is using without using the ith observation means using all the observations except the ith observation. And similarly we have one new term I need to introduce this notation that MS residual MS residual i is also is the estimated I mean is the predicted value of predicted value of MS residual obtained without the use of ith observation. So, here also you know generally MS residual estimates sigma square which is sigma square is variance of epsilon which is unknown, but here the MS residual bracket i is the MS residual only that is obtained using all the observations except the ith observation that is the difference between MS residual and MS residual i. And of course, you know if ith observation is going to be an inferential observation then this quantity is large. Let me just try to explain this one using this example might be. So, well what I told is that my this difference of fits i. So, I am doing it for a for example here. So, what is this? This is I said that y a hat this is based on all the observations minus y a bracket hat and it has been standardized in some way. So, what is y a hat here? That means this is using the fit using all the data. So, this is my y a hat I mean this distance this height is y a hat this is the point x a y a hat and what is y bracket a hat is that. So, this is the fit you know using all the observations except the observation a. So, this is the point you know x a this is the point x a y a bracket hat and this is the point x a y a hat. The difference is this much and this difference is going to be large if the point is influential quite clear because you take any other point and compute the d f fits for that point it is not going to be so large. Well, now the testing criteria is that a possible a possible high influential observation is indicated by if this statistic value for some observation I different difference of fits f i t s i if this quantity is greater than 2 times k by n I am not going into the detail of you know how to get this critical value, but just is enough to know that if the if the if the if the if d f fits statistic for the i th observation is greater than this quantity for some observation then the observation can be treated as influential observation. So, next we will be talking about one more statistic that also this new statistic you know that also measure the deletion influence sorry the influence of deleting the i th observation from the data set. So, this one is called difference between the data set and the data set. And the betas and here it measures you know instead of measuring the difference of fits I mean the difference of 2 fitted values it measures the difference of 2 I mean the estimated value of the regression coefficient beta j. So, here we what we compute is that we compute how much the regression coefficient beta j hat changes if if the i th observation if the i th observation is deleted. So, instead of looking at the difference in fitted values here this d f betas it looks the change in regression coefficient beta j. So, this d f betas for the i th observation and for the j th regression i j is equal to beta j hat minus beta j hat i and it has been standardised using this m s residual i. So, this is the and you know what is this and x prime x inverse j j just let me tell what is this beta j beta j is the least square estimate of beta j hat is the least square estimate of beta j obtained using all the observations. And this beta j hat i this beta j hat i this beta j hat i is the j th regression coefficient computed computed without use of i th observation. So, what you have to do here is that you know and what is this is the you know what is x prime x inverse and j j means is the j th diagonal element of x prime x inverse. And so, this difference or difference of betas I mean d f betas is calculated for each i and for each j. So, here i runs from 1 to n and also j runs from 1 to n and also 0 to k minus 1 and as general rule as a general rule a possible high influential observation is indicated by d f difference of betas i j if this value is the difference is greater than 2 by root and again I am not going into the detail of how to how to get this critical point. So, these are the different techniques to different techniques to detect influential observation or the leverage point. And next we will be talking about you know once an influential observation is detected then whether this influential observation should be discarded or not. So, what we will do after detecting an influential observation in the given set of data? The question is should influential observation be discarded? So, here you know the recommendation is that you know we need to take care of the influential observation I mean first we need to check whether there is any error in measurement for that particular observation and if you see that you know if you see that there is an error in recording the observation then the discarding the observation is appropriate otherwise you know if you see you know if your analysis reveal that there is the observation is a is a valid observation then the observation is a valid and there is no justification of discarding the discarding of valid observation only we need to take you know special care of that influential observation. So, that is all about the influential observation or you know how to detect and how to take care of the I mean if there is an influential observation what to do with that influential observation and in the last module because of the time constraint you know I could not talk about one thing that is called the press statistic. So, this is not a part of this module, but I have some time today. So, what I want is that I just want to talk about the press statistic now and then I will stop. So, the press statistic so note that this is not a part of this module the press statistic. So, this is one thing I wanted to talk in the previous module that is in module in module adequacy checking. Let me just recall know the ith press residual is E i which is equal to I already talked about this y i hat. So, you know that you know this is the observed value and this is the fitted value of y i obtained without the use of ith observation and of course, here large press residual are useful in identifying observations where the module does not fit the data well. Large press residual are useful in identifying observations where the module does not fit the data well. So, if you can recall the ninth observation in the that you know delivery time data there E 9 was very large E 9 was something like 14.7 and. So, this indicates that you know this fitted module does not I mean the module does not fit the ninth observation well. And anyway so the press statistic is the pure press which is equal to E i square 1 to n. So, this is nothing but y i minus y i hat square from 1 to n and this also can be written as we learned in the previous module this can be written as E i by 1 minus h i i square. So, what this measure is that it measures how well a regression model perform in predicting new data. So, this is the this is how the press statistic is used and just I want to recall the previous example that delivery time data there you can check that the press value is equal to E i square i equal to I think 1 to 25 that is 457.4 and see the press is the counter part of s s residual when you consider all the data. So, this is some just E i square i equal to 1 to 25 which is equal to 233.4 7 and as I told you that for the ninth observation in that example E bracket 9 was 14.7. So, E 9 square is almost the half of this press value. So, the higher press value indicates that the model cannot perform very well in predicting the new data. So, especially for the data where the regression values are large. So, this indicate so this indicate fitted model is not likely to predict new observation with large x 1 and x 2 value well because I do not have the example with me at this moment yeah I have it. So, this is the ninth observation this is the ninth observation. So, you can see that you know for here the x 1 value and the x 2 values are very large and that is why the E 9 value is not likely to predict the new data. So, this indicates that and the E 9 value is very large. So, this indicates that that you know the fitted model is not likely to predict new observations with large x 1 and x 2 value well. So, this is what about the press statistics and also I know as I told this is not the part of this module. So, in this module we have learned about how to detect an influential observation and once the influential observation has been detected what to do with that observation and I have to stop now. Thank you.


What's up everyone, welcome to Simulation. I'm your host Alan Sackian. Pumped to be talking about the computational renaissance. We have Tristan Tyler Blake joining us on the show. Hi Tristan. It's a pleasure to see you again brother. It's been a long time and we've spent so much time together on the phone and just discussing these incredible ideas. So really good time to be here and thank you so much. I look forward to this discussion man. I'm so pumped and yeah your background is so epic for this conversation we're about to have. Tristan Tyler Blake is the founder of Machine Learning Society and the Co-Network which are custom engineered social networks for the acceleration of science, technology and culture. You can find the links in the bio below to the computational renaissance page as well as innovationhyphenlabs.co and Tristan's LinkedIn profile. Yeah we've been going back and forth for quite some time now on ideation around the future and what the best social fabric is that's going to be the most optimal design and architecture of the protocols that manifest the abundant prosperous future that we're all seeking. Let's start with a couple of our more spiritually inclined questions. Sure. Are we really all one? You know as a person who loves history and literature I believe we need to rescue a lot of words from mediocrity and I think in the spiritual realm I often see that people use the words like quantum and the words that are dedicated to science and have a true legitimate meaning and I feel like they're competing with the scientific one where actually they're just trying to say the same thing from two or even three different perspectives. So are we all one? Do we have a collective consciousness? I actually think we have collective emotions, a new class of emotions that might be emerging could be from social media, could be from the internet but there are emotions that come from within internally and then if you have the type of radar that picks that up, an ecosystem intelligence something that I believe that our species is evolving then you could pick up external emotions and experiences that are collective to us all and if the two misalign well you get yourself a little bit of just friction and so it's important to have your external emotions or the collective ones and the internal ones be compatible and that's really I think the key to happiness. Would you say that everything is interconnected? Absolutely, yes and I often think in different sciences kind of so you're driving down this road and you look down the mountain and you see the sky and you see the trees and that is all an ecosystem and it has its own computational intelligence behind it and there are sciences or fields of exploration inquiry that we don't even know how to ask about or how to question or analyze but the trees are related to the sky and related to the mountains and the relationships are difficult to identify because there's so many of them and it's about asking the question in the right way and as we talked a little earlier every life has 2.5 billion heartbeats, not four billion so all those thousands of people that I told before it's 2.5 actually. 2.5 billion if you live until you're 82. There you go, so every life has 2.5 billion heartbeats and I believe a million questions and what I find as a person that is passionate about data science and algorithms is that it's actually the order in which you ask questions that really defines the outcome. So if you ask one question before the other you get a non-answer or you just didn't ask the question appropriately and I think this moment in time, this computational renaissance, this period, this epic period actually it's about asking questions, the right questions in the right order that counts. We'll dive into that in a little bit more detail in a little bit, I wanna ask you also what do you think is the purpose of this reality? You know, I love the suggestion that there is a purpose but when I look into the stars and into the sky I just feel like the stars are really, the purpose is for stars to live and die and for the universe to live and die. Everything lives and dies so it's the purpose is to understand what life is I think or just to experience life as much as possible every flavor, every type of experience good and bad and I often have these experiences at home I tell my friends about this but I'll be reading history or writing something and it's as if something takes over and I experienced these I used to have kidney stones a couple of years ago and just terrible pain like eight out of 10 pain but these things you go down just as hard on your knees except these are eights of pleasure or of clarity so I call them seizures of clarity because you go down and you see the world and you experience it and you just the types of things that truly enable that kind of experience is to think about numbers or sizes that are overwhelming that's when I'm triggered so how many stars in the galaxy or in the universe try to think about that and that will, that simulation attempt will literally blow your mind and you could experience what is a billion stars when people think of, when I say the word billion think of a billion stars you're actually thinking about 20,000 50,000 probably now multiply and multiply and multiply that so when I look at a swimming pool I see a trillion atoms of water and water, just the molecules interacting so there's kind of a big data way of seeing the world a perspective and then there's the actual reality so I believe, yeah, the purpose is to see the world from all of the different angles and perspectives Yes, very eloquent I love the way of being able to see from these different perspectives adding into more clear and true it's kind of like the purpose of it is to see it from all of these different beautiful angles to have these profound moments of awakening that that feeling is exactly what this beckons this reality beckons for you to feel for you to be dropped to your knees of mind-blowingness over and over again, every day mind-blowingness I love that I found that when you... so beauty is kind of like a bunny rabbit it's so fast, they're always so fast and beauty, if sometimes you see a bunny pop out and you try to get your phone to capture a picture but the moment you have it ready the bunny is gone, long gone and beauty is just like that when something beautiful is in front of you you almost don't have time to appreciate it or even identify, truly examine it and I think some of the new technologies of perception that we have and subconscious kind of, you know tweaking or understanding your subconscious and actually experiencing it you can now capture reality in real time and explore beauty and then effectively understand the patterns of it so that when you're walking around you can actually see aspects of that beauty that you captured maybe it could be culture it could be a sound, it could be a shape it could be a geometry and then you could apply that to this new beauty and you see it all over again because you've learned to recognize it in the past so it's kind of funny the more beauty you see the more you see it everywhere Yeah, another one of the feelings for me actually tying in all of the previous questions that I've asked are these feelings of the most deep profound interconnectedness to all that is and when I experience that feeling it feels like the... first of all that this is my next question actually to you have you experienced ego death before and give us the experiences? So I left my ego on the airplane in one of the kind of compartments and then I forgot to pick it up on the way out it was actually when I came to San Diego I sort of, I forgot, I left it on the flight you know I was coming from New York like Wall Street style you know kind of doing this thing and I just realized that that's just not what makes me happy what makes me happy is learning about the nature of reality in the universe investigating the conversations between plants you know investigating the size of stars and their relative sizes to each other these things are just much more interesting to me than I guess making money or kind of you know those aspects so yeah that's I experienced ego death a couple of times and it's when I meet extraordinary people with profound intelligences and just kind of humanity that if you have ego you are missing the opportunity to explore their geometry it kind of it's a blocker it's a filter on your reality your ego and actually I've been telling my team my amazing team that's sitting over there I'd love to talk a little bit about them later but when you kind of just experience reality as if it was a touch screen right here now imagine there's a finger behind somewhere so what if you were just to go back a little bit now look at the screen and you start to understand when you know my work is in computer vision and artificial intelligence the machine learning society I try to look at the world through the lens of a child's eyes like a like a toddler what are the learning patterns um how is the interpret information being interpreted and then you go and you say wait a robot needs to understand what is a person what is a microphone what is a computer what what what am I potentially later yes yes yes so you could start to understand how a robot interprets the world and that allows you to go wait a minute we are very neuromorphic so if you just look at your own lens if you zoom out you could see all the red and blue circles and indicators and well you could actually then decide this indicator goes off and it's red negative but you might enjoy that or you might actually like it but your actual character or your build your architecture um your scaffolding it doesn't permit for you to experience that with clarity without some noise being introduced by your body so I listen to my um my mind rather than my body and my and your body is the one that typically adds layers of perception it goes I like this or I don't like that whereas I go no no no what do I actually like and it's like that touch screen that you could modify your own weights so I have up your your site so let's jump into this there's a couple things that I want to explore here you started us into this computational um renaissance um so we have we have um this is innovation hyphen labs dot co this is magnetizing intelligence where we started giving us these ideas of of patterns pattern recognition from a from the perspective of a child when they're born into the world how do they see the world do they what inputs are they starting to take and how are they starting to understand the patterns same thing with robots same thing with perception found curiosity profound curiosity and starting to structure what is most relevant for them like what are they uniquely blueprinted for to do in this world and then how do they then ask questions about the reality to help them bring what's blueprinted in them fourth into the world so so let's have you walk us through a couple of these things there's there's um the ml society co-network um I want you to to walk us through there's there's one more thing that I want to showcase as well which is uh the computational uh renaissance as well so let's show this so this is on that page when you click computational renaissance you dive here so teach us about the difference between ml society co-network um computational and teach us walk us through all the shorts so uh you know when when I first came to san diego I I didn't really know um what my future would be there I sort of came almost to get warm so that I could head off to sf you know over here with you guys but um the moment I touched down I just recognized that there was this transformative period this revolution going on and and I was always very nostalgic about missing the Einstein Neil Bohr period where they were uh kind of cutting the nature of the atom they were splitting it and understanding it and I felt like I had lost an opportunity to be part of an epic period but the moment I touched down in in san diego I truly experienced this like revival you know just this awakening of of curiosity and and um an opportunity so I started to explore and I wanted to go to UCSD to the data science program because I just knew AI was that I knew machine learning was a answer to many questions that we didn't even know how to ask yet and but my grades were just horrendous uh you know when I was younger I had to deal with certain uh experiences that didn't allow me to focus on my grades or you know a lot of other things for that matter so in san diego I realized that I wouldn't be able to join any program but no school should take me really uh but I but I still need to learn you know I still need to be around uh this these people and to absorb their and understand their um culture and their civilization that they've engineered so I started hosting these groups the machine learning society there's this moment where you know I launched it in the third day there were 60 people that were on the on the group and I was like oh my god now I have this responsibility to host to do something to create value for them otherwise I'm wasting their time so I started hosting these events and and it started with like these Kaggle competitions these data science competitions um you know for engineers to kind of collaborate on on solving um the computer vision problems and natural language processing problems and I was just learning through that you know uh in real time the the other thing is we would host I just saw that the academic world wasn't really providing a lot of um experiences for their sciences that allowed them to actually connect so I started hosting hikes with a data scientist you know where people can walk and talk about everything including bioinformatics and physics and genomics and all these incredible things and it was very successful so I started to scale my ambitions you know as you do as you start to see elements of success and I started hosting larger and larger events until you know to our community today we have about 30 000 impressions you know social media with our email campaigns and our actual physical community in New York, Boston, San Diego and one that's growing in the Bay Area so it it's just about when you have all these people and all of their attention how do you actually concentrate it towards outcomes that that benefit them and create ROI and that's I think that's um return on inspiration yeah yeah I love it so there was this deep passion from you to get involved in this computational renaissance you're coming to San Diego this very Silicon Beach SoCal-esque LA and San Diego have so much of the cutting edge that's happening this is very important to keep in mind as a lot of people are just looking at Silicon Valley okay so then actually it was gravity it was gravity gravity get pulling you to and I really mean that when I say gravity I've been exploring this this external emotion as we were mentioning earlier I've really been feeling gravity and and something that I kind of just saw was consciousness is gravity consciousness is gravitational it pulls and it can push to going towards solving these big problems in NLP or computer vision and trying to gather the consciousness to focus on the big problems and to advance the frontier of AI I like this a lot so then let's let's start wandering into you know you're throwing you're throwing these events you're throwing these competitions you're seeing how you can focus consciousness on tackling the big challenges now you have communities that have popped up around the world so let's walk us through the then the differences between ML society co-network your computational renaissance and we'll showcase them as as you go so from today's lens you know it takes time to truly understand context and to put things into the proper boxes right to contextualize them in the in the past the machine learning society was just this this instrument for attracting intelligent people so they can collaborate it was very effective but then I hit this scalability function this this kind of I was looking at the machine learning society as a community and I really didn't know how I could scale that until it was actually a dream and it was a vision it was just this moment and I remember when it happened when I started thinking wait a minute wait a minute this is not a community anymore we've just transitioned we've just moved into a network and the moment I started seeing this from a network perspective it fundamentally changed the the transition towards a network allows for scalability and that's borrowing from data science and complexity theory and all of these new sciences that are profoundly transforming the human condition and our experience of it so the moment I saw it was a network it freed me to actually scale it pretty much infinitely using the infrastructure of a network so the machine learning society is a community at the time and then I understood I started meeting other groups that had a machine learning society class problems so if you think of a community as an egg right with a with you know some sort of embryo inside I started thinking what would an egg carton look like or or something that could incubate these communities and turn them maybe into networks when they hatch so the egg carton would be co-network which is essentially an infrastructure for network design for networks to operate and they if you think of it almost any community or network as a brain you start to see each one of them requires communications infrastructure event management jobs and security like that storytelling right yeah just culture right culture is a technology so all of these different aspects are absolutely necessary for any healthy community to to exist and to continue to you know operate flourish and and that's what co-network was for me it was this kind of how do I build a templated infrastructure for any community to expand and to operate on this new paradigm of just connectivity collaboration communication so yeah I love that I love being able to like you said focus in consciousness on tackling the big challenges especially around the future of artificial intelligence and then you went and gave us this example of how you need all of these different pillars I like your brain more I like your brain now I'm gonna use that I'm gonna borrow that I love this a lot yeah because there's all these different pillars of the network design and the environment for the community that can maximize the flourishing of it I love that a lot it's a system think of things as systems every system requires certain parts and if you could systematize almost anything and that's a technology that we're developing now we're going to be you know releasing shortly to the general public but if you can create systems that that capture these patterns and and replicate them pretty much infinitely right AWS I mean that's what it is it it's design a pattern and then scale it as much as your ambition allows so yeah the there's a certain I guess what people need to appreciate is there's a if you put enough energy and infrastructure behind something there's kind of a tipping point towards inevitability and you need to know how to understand and simulate that so I think your simulation storytelling is actually a lot in line with that theory yeah yeah so a lot of it actually does have to do with like you said this building out this this this network design to maximize the focus of consciousness on tackling the problems and then one of the big pillars is yeah the story why are people doing it how can we optimize the galvanizing process of people's spirits in order to get them going towards a given goal you sent me over computational renaissance so after you go to on the innovation hyphen labs co once you get here you click computational renaissance on the left and then it takes you over to the computational renaissance page so when you were explaining this to me it was really beautiful because I started seeing things structured data basically I was like structured data and like you look at the column on the left and there's uh hello world curiosity tracks master takes cities events lectures books podcast institutes boot camps jobs initiative signals videos etc and when you click through those you can find incredible events based on machine learning in san diego or in boston or whatever there's so many different ways to categorically parse and find the data that you're looking for and i love this so teach us about what you're doing here with this computational renaissance platform and in a sense it's like a really beautiful way to structure data and make it easy accessible so it's actually a really funny story behind this i am in my apartment in san diego i call it the habitat and i effectively invite people to just call me up and go i'm in town and i want to tell you something i want to tell you i want to share something and i'm like okay i keep this antenna open for interesting fascinating people uh and and it worked you know one some some gentleman he he called me and he's like hey i'm i'm in san diego and i was told i should meet you and you know you do this a lot as well so uh and he just came over and we started chatting we you know we hung out and i shared with him my one note document that organized all of my dreams and stories and memories and kind of all this stuff and he's like dude this would look great on this software suite coda actually and coda.io and i'm like all right what you know what is that kind of so i wrote it down i i make sure that every opportunity that flies by i have a way to capture it right like that bunny yes you need to be ready for the bunny the beauty you need to be prepared to capture it right away and examine it so you could see it everywhere so i wrote it down right away and you know that the moment that i did it i was standing at my standing table and it was just a profound experience and i wish people can go through a similar experience you know i think it's a it's fundamental it's probably the same feeling you get the first time you use google maybe even the first time you're going to ask a ai a question and it's going to give you an answer that is coming from something from a brain right everybody hopefully is going to experience that one day uh soon but uh you know i was standing there at my standing table and it felt when i started using the software i saw the future in front of me that just this incredible visual you know this reverie and the moment that i saw everything i felt like the ground had just collapsed under my feet it left it disappeared and i felt like i was flying no ground just flying and i realized right there that a lot of people who are i guess from a depressive disposition um you know or the kind of those types of repertoires they would experience like they're falling but i felt like i'm flying and i simply realized that flying is simply falling forward in physics and that was kind of the the experience and i wish people experienced that flying feeling of just weightlessness and and momentum pushing them towards uh uh you know their passion or their just what is calling them that gravity so yeah that's yeah to be able to capture the profundity of ideas or of beauty and then be able to organize it in a way that can recall or they can share with other people is so critical and so yeah go ahead go ahead so this system uh i'm so my halloween costume going forward is going to be database man hmm i really love databases i think they're beautiful they have all this like starfish databases are different designs and there's exotic formats and if you organize data a certain way you really get a incredible kind of clarity and insight into this information and you can you can see it from different perspectives and um you know so this system that you saw over there that's i needed for myself i built it for me in order to have an ecosystem intelligence to see every company in uh in the in north america china and europe and south america a little bit i needed to see that right so that i could by tag understand what are the what's the opportunity matrix some of the other distributions that i've designed have been for personal kind of management of my reveries or my memories my thoughts my experiences my writing almost like a four-dimensional book for data and you could jump in you could write something tag it up and then you could fly around in your thoughts it's a powerful experience and uh and i think a necessary one to truly understand the tags that hold the your information your ideas there's certain buckets and and templates and themes that you're constantly cycling through and if you could let them out externalize your uh ideas and the things that swirl around you actually get to see them for what they are and examine them and and use them with context and and uh and the social network that we were mentioning earlier the co-network uh that's actually also an externalization or a um digitization of my personal relationship network so it's i guess there's a theme here right it's digitizing and externalizing your experiences and emotions and uh networks and relationships in order to truly uh interpret them understand them and leverage them to create and and um and inspire yeah when when i hear you talking about like being in love with databases being in love with the visualization of of data and the process of structuring it and making it relatable externalizing my consciousness into some sort of a visual that i can go and recall more easily the most profound things of course we were talking about this beforehand but there's so many ways to do this this is with your big network of contacts this is with all of your ideas and your execution roadmap there's all different ways to do this and so you know how do we optimize that process of taking in that data structuring it visualizing and creating a feedback loop of your process of actualizing your your vision into the world this is extremely important to figure out i'm so glad that you're super um focused on this and this is actually you were using this word data metabolism which i really like because we've been using also data refining and i think they're so so similar um the process of now that data silos are no longer they're breaking down and in many ways decentralization is is moving forward there's so many good ways to be able to find like right now just take this example of your data that's in your google calendar data that's in your google contacts data that's in your ever note or one note or keep or whatever you're using for your note taking service there's no harmonization between that data is for you to further be able to gain profound insights visualize even in your networks like you have all these you know your facebook twitters instagrams linkedins etc the the ownership of the data being on their end and the limit of when do you ever get a beautiful data visualization of your own network and the people that you can get in touch with that will help you accelerate what you're doing all this type of stuff these are things that we're super passionate about seeing in the future of the data renaissance and the computational renaissance so data metabolism uh you know i've been using that word too i've been seeing a phenomenon i'm as an anthropologist uh self-trained uh i would say um obsessively i'm an obsessive uh anthropologist so i didn't go to school for it i just want to kind of make sure everybody knows that but i have another training it's called obsession for culture and civilization anthropology um i started noticing that a lot of my friends and a lot of the people around me were flooded with data too much too much information tmi and they were unable to self actualize because there was just so much data to process on a daily basis like so many texts and this and that and you got to do this and that and people started to almost slow down rather than speed up i just saw a tremendous drop in productivity and i was like wait a minute this phenomenon i i i need to i need to jump over it and experience it first so that i could create templates for others to use it's so interesting that becoming more interconnected actually could decrease productivity if we're not careful about how i right yeah so that data metabolism i mean that's a maturity it requires maturity that the most important word of the 21st century by the way um so that maturity with data really like using your cell phone as a as a tool and a vehicle to achieve your uh uh you know dreams rather than just being this um attention kind of gathering thing i believe in not in attention economies but concentration economies where you focus and habits and focus or technology in my opinion and that's something that some of the networks that we're building are designed to amplify and you know really target kind of what do you want to do and and send you towards that uh at with with momentum so yeah data metabolism you know you really need to be kind of careful to get rid of all of the dings and pings and make sure all of this information that you're gathering uh is being used and relevant so it's really as a you need everybody needs to become a data scientist yeah in order not to be overwhelmed with data that's potentially unnecessary interesting everyone becomes a data scientist so that you can manage the fire hose of data that's being shot into your face every single day some of us have better data metabolism than others like i can remember almost everybody i've ever met and i can recall people and faces and all that stuff uh but my memory is very different you're parsing for signal for your personal blueprint yeah absolutely so you could engineer these data centers for your personalized data centers essentially to recall almost anything and i often tell people why remember anything when you could remember everything and the way you do that is you externalize your memory and you leave so much space inside to actually compute rather than hold RAM and there's just a yeah i mean it's been called an existential technology by some people it really allows us a single person to organize complexity it's so funny when i'm in a conversation i go hold on a second i need to get my computer and then i go and i offload all of the profound things i've been capturing onto in off of RAM into long-term storage and then i just go right back into focusing on trying to make the profound connections with the other person and not focusing so much on the storage as well of the data right you know uh yeah we're in this period right now where this form factor of the phone it's like your attention has to be diverted and uh you're you're always have to be kind of going to your computer to truly capture the context but some of my friends and some of the things that i'm working on are going to allow you to be present and to truly just be while this thing is ambiently collecting your information good luck with finding what's most profound to that person you have to know that person's personal blueprint you have to know what they want to parse for and then you ambiently have to capture it but this is all possible it's of course all possible that's so my exercise was a really big risk i took like three months to experiment and do this and it was at great risk because that was a very valuable time period where i need my data kind of prepared or else my business and my relationships are gonna you know suffer and but i took this this leap of faith to basically go i'm gonna try a totally alternative approach just unconventional all together in order to see if there's a unfair advantage that i can get through technology and then once i've templated it and given it to all of my friends i can then reproduce it for the rest of the world and one of the things that people should appreciate right now is just with even social networks the one that we're building you can actually architect a single master kind of template and then you could infinitely replicate it yeah and you could actually focus that network's attention on people that love bicycling or podcasting right and you could tweak the parameters and the actually the the culture and anthropology you could reverse engineer anthropology so when most people go to Burning Man or one of these events you know i go to them but as an event organizer i actually i'm experiencing them in order to reverse engineer some of the cultural perspectives that i see there and some of the anthropology that i see and i can apply that culture or applied anthropology so this is uh the people that are involved in humanities and civilization and art and all that stuff this is really where they turn on and if they could just understand how you use databases they can create incredible resource systems for their communities and for their families and their friends and they could basically just scale which is their consciousness there's all of these uh yeah applications of these personalized ways to focus consciousness on these given tasks and all you have to have all these pillars that you're talking about earlier that help you know you've given this one recently this um this understanding of anthropology and culture and the dynamics there to help push along that focused consciousness i love your push on that and it's so interesting too there's all of these different um focuses on these on these little like butterfly protocoled consciousness focuses genomics iot autonomous cars 5g technology superintelligence blockchain all different aspects of this it's just it's endless just mentioned some of my favorite buzzwords exactly and it's just and these are the things that you can you're creating these little pockets of that are happening around the world in different areas yeah you know um i just think right now this period this computational renaissance is a moment to ask bigger questions and these periods these epic periods actually um they arise when there's an existential risk to a species so i'm a big kind of i'm a very passionate about ancient greek history and roman mythology and all this stuff and i find that these epic periods are really just for humans we transition in those periods yeah and we ask bigger questions because we finally have reached a point where we now have the ability to answer it and and uh you know the 1970s were and before we used to understand and manage capital the years after that the next 10 20 years uh google came through and it was able to manage information uh i think amazon has just arrived on the scene to manage computation you know and and now we've just solved that problem and i think the next few questions are really going to be about consciousness understanding that this we're all leading to the same point that same intersection we're just asking in a very different languages and accents and but we're all leading to that very fundamental question which i think you asked in the beginning kind of are we all one uh consciousness i think we're all engineering a single consciousness and we're transitioning almost the same way that hunter-gatherers you know uh hunt went to kind of farm and living you know in these small villages and then these villages transformed into towns and then towns went into cities and then super cities and then megalopolis and now our first summit in san diego not our first summit but our q1 summit is called synthetic infrastructure and that's about turning a city into an organism a brain that manages all the infrastructure and the water and you know resilience for earthquakes and fires this is really a thinking system a city that thinks and communicates a networked city and i mean you know between you and me i believe that san diego is small enough to prototype these solutions and then rapidly propagate them to other cities around the world i think there's a city to city c to c model uh happening right now where you want to buy a port sure we can sell you this usb stick you want to buy an airport same thing it's on another usb stick if it fits right so you can now understand infrastructure and template it again getting back to that templating one-time template and then iterating or improving upon that template uh over and over and over again until you have a finished version this is 3d printing uh but of scaffolding ideas it's it's quite a remarkable technology and i encourage everyone to try so the synthetic infrastructure summit that's coming up in the q1 of 2020 yeah march 12th and 13th march 12th 13th to 2020 in san diego you're basically identifying all of the different data that's happening inside of a city and you're structuring data turning it into an actual brain an actual more functional brain that's able to produce what san diego's goals are what denver's goals are what london's goals are televives goals are that is consciousness from a city perspective a city can be conscious if you give it a brain if you give it a brain a nervous system and the nervous system is the iot and the edge computing the edge computing yeah so we recently came from a meeting with intel we were actually um doing a video podcast so i hope to have that up in a couple of weeks we're producing a cool screening but you know they really talked about some fascinating kind of approaches to engineering edge computing and just to describe what that really means it's actually the paradigm before was this cloud model where you would ask a question or a car would see a camera you know the camera would see something i'll go i see something it would go up the wire and into the cloud and then the big computer somewhere some supercomputer some data center would answer that question computationally and it would send an answer back and just like the brain i mean wow that's a lot of time spent transfer from here to here even though it's a small distance um when it comes to uh neuroscience or when it comes to biology and the nervous system these split seconds are the difference between life and death difference between an accident or just a shift in in traffic a calib recalibration so this new move towards edge computing is is really founded on this understanding of the brain and and neuroscience and and neuromorphic computing you know so actually sandigo has uh some of the leading research at the salt institute uh on on brains and uh i guess that's really i don't know one of the most exciting areas if you're if you're into um neuroscience and cognitive sciences that's you're really positioning yourself to not only understand but to explore and pass through this world in a way that you can actually experience it just just just a new way you really get to see the world in a profound way and that's our second conference uh our summit q2 um 50 shades of gray matter you got it okay the shades of gray matter yes uh computational neuroscience behavioral psychology uh i fundamentally believe that we're transitioning again again hunter gather you know to to this farm to the city to this biological structure this megalopolis turned into an organism with the nervous system as the highways and the tunnels and the sewers being reinforced with the new technology well synthetic as 50 shades of gray matter is really our mind and the wiring behind that uh with some of these new softwares you're really able to go into your subconscious and understand how your neurons are are firing you could feel it you can go in you can control the screen the touchscreen behind the screen and you could add your own weights again if you're if you're building a machine that can interpret the world through computer vision just apply it to yourself and now you have a mathematical logic layer you can see the world in math or in waves you can see it in particles you could see it in uh in colors you could you could really choose which focus you want and which kind of vision you want and you could apply that and there you go it's human vision computer vision so it's it's quite astounding so 50 shades of gray matter i you've all know a horari if you're listening to this please please please come and speak there uh you know these are yeah i i love that guy um i think is one of the best of our time yeah yeah please read that sapiens 20 21 questions for the 24 yeah just know that if you know that you're on the right track so um and some of these speakers that are going to be there and some of the questions we're asking i mean you know what is the future of of our species and how do our brains evolve from here how do we make that decision collectively because i don't want to leave people behind i mean it's necessary to adapt but uh but you will be left behind if you're not able to uh to re to to tweak your brain and to create kind of new ways of seeing things and to be adaptive and to be hyper you know just just to see opportunity and beauty and everything is is is a superpower and and i i think it's necessary to understand yourself self reflect and then to understand others and to learn how to find beauty in others so and that's why i continue to hang out with you because this tremendous beauty inside of you and i and i see it you know so much that it's it's it's radiating so thank you thank you likewise and so then what would you recommend then given all of the computational renaissance that you just listed what would you recommend as a skill for young people and adults going into this computational renaissance era you know i'm i feel really so this trip right now i'm on a trip with my team to uh to san francisco and we we hit up some of the major companies out here to have these awesome conversations about how we can collaborate and you know all of that is going very well but i came here personally my trip plan my goal for this trip was to conquer a fear a single fear every trip every journey must conquer one fear so a lot of viewers or you might think that i'm very comfortable in front of the camera and today i am but this is at a very different uh i used to have a lot of stage fright like a lot and i mean um a nervous response that would constrict a throat and would create this kind of i was too afraid to raise my hand in class a long time ago and it just to move from there to there on all these fears to fear everything at least once everything from ghosts to the dark to relationships to women everything was a fear at one point i've kind of become an expert at overcoming fears so this particular trip is about overcoming the fear of cold i came here and i walked around the redwood forest with shorts on it was fucking freezing but i came here to win against the cold and to experience it and to use my own weights i i know what my body feels about the cold wim hoffett yeah exactly i know what my body feels i feel you but i said wait a minute let my um let me make my own heuristics so let me tweak my own parameters so that was this journey and i think every single journey every relationship every uh expedition and i think you should take expeditions today um is about conquering a certain fear so my goal for every podcast and every media and content that i produce is to push a single person out there one person push them towards their goal and help them remove a blocker and just overcome a single fear that's holding them back from whatever it is that they decided to do that's you know dude just one person if i can get you know let's go yeah yeah so so can we inspire people can we awaken them can we help them get towards their goals yeah yeah just push a single person and that person will push 10 others over time butterfly effect baby so yeah i love it what are your thoughts on free will do we have it is this all determined gotta ask sam harris about that you know free will that's a good question and my team has taught me to answer i don't know over this last trip am i free to do what i'm doing i think your architecture um your neural architecture decides kind of what you're probabilistically going to do and then it's your choice to choose out of the billions of little subconscious kind of things coming up bubbling up your experience and training and and history will decide on which three or four probably the best options and then you i guess decide which one of those three you'll take you'll you know apply but i think you always i think we actually experience a million different desires at the same time and then our consciousness or subconscious in our subconscious and then somewhere in the city of the mind you know that all bubbles up i guess really the thing that i look at this and when i look at kind of that neuron uh there's a way to most people's brains and subconscious they treat it as if it's a um surveillance system their consciousness is a surveillance system of their subconscious hey you where do i find the answer give it to me now so i just tried to answer that question and i went into my subconscious with my consciousness and i went you better give me an answer and i scanned the entire neuron city for answers and some tried as hard as they could like here here you go here you go but it's really about knowing where to look inside that architecture that always gives you the best answers which part of your subconscious always gives you the best experiences and emotions and feelings and that's where you got to look for answers so do we have a free will i think we have the freedom to select which part of our consciousness or subconscious provides the answer okay and then do you think that humanity is a biological bootloader for digital superintelligence meaning are we here in order to bring on the next thing well you know i think that i think that we are just designed in a way architected in a way uh through evolution to always continue to ask deeper questions it's always push kind of chip the rock a little further to see what's behind it so if i told you that behind this huge stone there is you know a something hidden there inside the rock i i guess people obsession people with obsession like me have to keep chipping at the rock in order to see what's behind it and i'll spend my whole life on it and you don't even have to pay me to do that i'll actually just do it on my own time you know i'll just keep chipping away and if ai is behind that then so be it um but i think i think you need to have maturity to chip at the right rocks yeah you said this was the most important word of the 21st century i thought this was interesting yeah maturity you know i guess maturity that's what that's what levels you up like when you have a maturity towards a certain concept or subject or like even public speaking there's a maturity that comes with practice and with doing it so it's a maturity with building super intelligence there's a maturity with building super intelligence and this thing could answer all of our questions one day or could bring about our greatest nightmares one day um and it's really about i think giving the people that have shown the most responsibility in the past and that have the highest levels of maturity and politics and science and technology the people that have demonstrated true leadership and courage they're the ones that should be given the freedom to chip away and to stop when it's necessary and to choose the rocks that we chip or to choose the kind of you know that medium that whatever's behind there the way that we birthed out of the egg yolk that is the planet yeah the way that the tree grows out of the planet yeah i think we need to be more a lot more selective on the people that are that we hold responsible um get rid of the deep state listen you know conspiracy conspiracy how do you feel about that is there global ruling elite tristan um most likely but but but uh but i so actually i mean i've met a lot of these people um the answer is no they're not in control because i understand the limits of some of their uh perspectives and intelligences so i've evaluated some of these people i personally don't think that uh they're they have that capability technically um even financially they kind of can't control everything like that um and also in order to do that you truly need to be a super anthropologist or a i anthropologist to truly be able to control because there's so much complexity in the system so many dynamic moving parts that the fact that one person or a group of people could truly model out all of the different complexities that happen as a result of tiny changes in the emergent you know tiny changes create extraordinary emergent properties that would you're assuming that what they do outcomes the way that they want it the way that they expect it and that's almost never happens just to give you an idea of the assets that people own um these are such as the um pasuer family the Rothschild family Rockefeller family Astor family DuPont family etc all these different bloodlines of the ancient um lineages of the planet let's give um these assets let's give their assets just to give you an idea of what is in control like a big game of monopoly railways banks cotton sewing machines electric and power gold and silver iron and steel motor vehicle companies insurance companies tobacco companies watch companies land and real estate companies food and household goods and that's only a very small portion of what is actually owned and that's not even getting into the actual nuance of the names of all the assets in those categories but just to give you an idea of when you do kind of own a vast majority of the resources and of the exactly what's going on on the planet yeah that's just a food for thought you know it's funny i mean um i i so i used to work in the family office space and helping family offices acquire all these real estates and uh companies and all that stuff that's part of my background and i attend these events so often times and i meet these people and honestly they're sweet incredible people that manage just massive fortunes um they're just people they're human they don't really have this i mean they don't have this conspiratorial kind of spirit to them they want sex and love and and of course there's a little bit of power involved but more important than how much money you have is how did you earn that money i think so did you step on people's backs and shoulders and throw its along the way or did you bring some sort of a very powerful value to the world that actually inspired more people's blueprints to be actualized and that's a very thin and hard line to parse and understand um but to do it with the most purity and the highest intention um of the maximization of prosperity on the planet that's a very important first principle to have otherwise you have so many of the root issues do you think that one of the root issues of all of the things that are going on in the world is our lack of of interconnectedness the fact that we feel so separate from each other and from nature and from reality from all that is i think it's a lack of maturity i think as a species we just haven't matured collectively yet i mean we're still having wars and stuff over really um not important things honestly it's just there's better ways to collaborate uh most people have this paradigm of competition it's kind of one of my little um when i think of silicon valley i think of competition and uh but my um i i believe the new approach to competition is actually competing to collaborate if there's almost like the super colony approach to that um i study ants and all these other species and super colonies are a very effective form of competition that's competing to collaborate uh that's the dynamic that i'm most inspired by and the one that i operate on yeah and it's almost like instead of being a shark you're a jellyfish swarm you know so there's this different paradigm of fluidity and uh you know i invite people to compete to collaborate with each other because of this that we were talking about earlier yeah you you just i don't think being um a silo or a shark today in the ocean just way too much light you can be seen and uh you you know you you don't synthesize well you don't mm-hmm there's just too much inefficiency in having a shark body in this new water i have a lot of water metaphor millennials and gens here sniffing out corruption quite quickly um so that's um quick questions last two on the way out are we in a simulation maybe i don't i don't i i don't find that question to be um particularly uh kind of it doesn't bring me to the place of exploration um i think there's uh ways to explore simulation like i like chemical simulations or physics simulations right these high performance computers that could simulate chemo informatics uh that could simulate quantum computing kind of uh you know phenomena that's really a simulation in my opinion a mathematical simulation you could simulate the way that one pharmaceutical interacts with different med you know bodies and and genetic codes so for me simulation belongs there is a word when it comes to the simulation of an actual um reality i do like to think about reality in the engine room of reality and kind of going in and playing with the knobs so is it a simulation i i guess i don't know enough about that particular um question to actually be able to interpret it to actually be able to feel what that's what simulation means i i guess i'm maybe ignorant of the of the whole context behind it what would you say is the most beautiful thing in this reality that's a good one curiosity why you know it's just it's the starting point for everything it's it's what is that why is that how is that it's just it's just it's it's a it's a basis for questions for asking questions if you have a million questions and you ask them in the right order you can actually get a few answers out of it and you get to see the world and and experience it for what it really is and taste every flavor and you know me to all the people um i kind of have this little theory that there's like 20 000 people are on the world that make it spin right i mean realistically and uh i want to meet all these 20 000 and explore how they do it and learn and interact with them so you know 20 Pareto principle 20 80 20 so my goal is to yeah just experience people i fell in love with people again i used to i used to hate people seriously seriously i mean it's it's you know i'm very honest about that um the way i grew up and some of kind of my upbringing there's that's a that's a thing that i've reconciled a lot of those contradictions and and traumas but now i've learned to love people and to see inside of them beauty and the architecture and kind of their unique geometries and i i guess yeah love for people is one of the most beautiful things to appreciate it to be curious about people i guess is to love them really that that's how i would put it so it's a curiosity directed as a laser towards something but you need to sometimes you're a flashlight and sometimes you're a fucking laser and you point it at a question that's worth solving yeah um and if you were if you're fortunate enough to have people around you that illuminate this darkness with flashlights you can act as a laser and when they need a little light for their laser you turn you open that laser into your flashlight and you shine it towards the place that they're trying to love it you know so that's teamwork that's collaboration that's uh yeah i i think that's the most that's one of the most important things that we need to figure out as a species because man do we need to explore more cave systems and more stars curiosity and collaboration and making the right ecosystems around that exploration or process that was very beautifully eloquently put throughout that episode and leveraging the computational renaissance that we have now to structure the data and to build the right brain cities to make it happen all this type of stuff to get back to some of those roots of interconnectedness uh and embed that style of feeling and emotion and awareness into um the future that we're building is paramount as we move forward otherwise the tree grows too crooked too much suffering we can grow it with more beautiful flowering along the way so yeah i think i think that this is this is kind of one of those uh feelings that i want to share like i have this kind of emotional internal emotion to to share this but uh i think right now during this computational renaissance these periods are extremely rare in history like most people never have a chance to to see light it's almost like sunlight coming out of very very shaded clouds you know and these there's periods and moments and places uh most computational cognitive revolutions happen in a very isolated place and with a very short limited period of time uh i i know for a fact there's one going on in San Diego right now kind of this era where it's an epic period with heroes and villains to a certain extent um and heroes and monsters right um but at the same time uh this is a period that it's almost like you're not allowed to be angry or upset doesn't matter who you were before the revolution or the renaissance it's about who you're becoming that's the real question here so whatever your baggage your story your ego all these things that you've held on to and they actually don't matter at this line at this point in the sand it's it they don't matter going forward you could drop them drop the anger the the fears you know just drop the all of those things that you believe all of this the write a new mythology write your own new mythology i think that's just an opportunity these epic periods they are for writing mythologies so if you respect the the ancients uh you know this is a period to write a new mythology for yourself for your civilization for your city and uh yeah um just go out there meet other people and and create that's that's my message yeah i love it wow this has been such an epic conversation Tristan thank you so much for coming on the program thank you so much super honor to have you on thank you it's a big pleasure thank you so much i love what you're doing man and uh yeah i support it any way that i can thank you come to San Diego and i look forward to uh introducing you to some people and would love to share some ideas i love the silicon beach i love San Diego and LA there's so many smart people down there i love it it's been such a great conversation thanks everyone for tuning in we greatly appreciate love to hear your thoughts in the comments below in the episode let us know what you're thinking about the computational renaissance about all of these different ways to structure the way we metabolize data and the way that we execute leveraging network theory and design and also all these other thoughts about just the what's written on uh innovation hyphen labs dot co computational renaissance check out those links in the bio below also tristans linked in profile check that out as well and then thank you ori for co-producing greatly appreciate it thank you to the team thank you to the and thanks to tristans team that's here we love you guys all thank you very much where the homies yeah you guys are amazing um it's amazing to have people that are from a different angle than you i always thought that it was supposed to be people just like me no no no no you actually have to have people that are very different but compatible that's just a little lesson for teamwork yeah yeah yeah it's a good one and then also support the artists the entrepreneurs the leaders the organizations your communities that you believe and support them and help them grow you can find all of our links in the bio below you can support simulation you can find us on paypal cryptocurrency patreon all those links are in the bio below you can also design merch and get paid check all those links out and go and build the future everyone manifest your dreams into the world we love you very much thank you for tuning in and we will see you soon peace


What is the minimum number of props that you can fly a multi rotor with well we usually fly four that's a quad four that's a quadcopter multi implies more than one so I mean David did the tricopter three right and you had to have one right yeah right at last I've had a bicoctor before I'm famous David Vindistall bicofter that was two motors on a servo yeah okay what if I told you there was a I want to call it a multi rotor but it only has one prop it's a mono rotor a mono a mono copter single prop how did that even work good question monocopter monocopter it's a drone very careful do not do not try to rotate these by hand I did that off camera I broke it oh sad had to make a repair because Drew broke it like within the first 10 seconds of holding his hands oh it's got veins yeah veins veins this project was a failure so far I tried this multiple times I tried a couple of different things I tried changing a bunch of things and this is kind of like version 1.6 at this point it's a lot of times what I do with my projects and I just kind of like throw stuff at the wall and see what sticks and sometimes I'll do that sometimes I'll put a lot of scientific thought into what I'm doing and sometimes I don't you know I thought I was putting a lot of scientific thought into this design but I didn't do any kind of calculations all the theoretical bits are there right so I mean I could see how it would work but you didn't like I didn't calculate weight I didn't calculate the size of the prop versus the size of the fins this was basically just the best guess yeah I just basically stuck it in 3d space printed it out and tried it and it failed it's fine Drew there's my elevator and our rudder just like an airplane I haven't tried to fly like an airplane yet seems like it's probably got the wrong balance point which I haven't actually checked balance or anything but the software should fix all that hopefully come back to me no y'all the other way what are you doing it looks like it looks like you're hovering a plane type of it is in auto stabilization okay I could switch it but it keeps yawing randomly and I'm trying to bring it back to me but the wind is blowing it away I'm gonna land it because I'm losing it I've been at this a while yeah I've been trying to make this work for a long time this was my first prototype and it was extremely heavy and I try to yeah but it was yes it was very heavy and it still is very heavy and it actually had enough thrust to counteract its weight which was awesome but it always wanted to spin out of circles it just wanted to rotate out of control and I thought maybe that I needed to increase the size of the flaps maybe they weren't enough to compensate for the yaw movement of the propeller so then I made this guy which is basically an airplane because the propeller has counter torque when the propeller spins yeah it generates counter torque that has to be counteracted you're directing the thrust down through this duct which is like theoretically gonna make it more efficient but she just didn't have enough surface area here and interest would spin right at least that's what I thought so that was the first design failure so then I moved on to this I said let me try way more durable make it extremely lightweight okay out of foam board like that so I was like you know what let's make a 3d airplane that's essentially what it is it's just really big parts missing here yeah I still I robbed the electronics for for version 4 the motor was up here right it was yes I feel like you just built an airplane I basically did yeah this is just a 3d airplane I didn't build it well it was my fault and I just wanted to try to see if I could get the software to work so then I came to this guy you've abandoned the duct I really wanted to put this inside of a rocket this one didn't fly either it would hover it would it would hover in place but then it would spiral out of control so in a typical drone you've got four points of thrust and you're able to tilt the drone by adding more thrust to one side and that's how you can get forward momentum as you would like tilt it forward yeah fly forward and you get rotation through the rotational inertia of spinning up the two props that spin the same direction which would result in the drone spinning the opposite direction of those two props with this all this is done with veins veins it's really cool so one propeller gives it thrust and these servos turn these veins to give it the ability to rotate the air yeah this is a just as cool proof of concept but I do think that built out there could be some advantages it could be smaller technically it could be if you could shrink this down you could probably essentially have the smallest drone yeah and only one propeller yeah if you could get more thrust out of it you could build out like a shroud for this whole thing and you would have this this fly like a ball drone that would fly with no risk of you know put a grill up top so you can't get into the propeller not going to get through the veins in the bottom yeah you'd have like a very safe flying ball fully enclosed propeller yeah possibly longer flat time too because only one motor you could build like a little 85 millimeter 95 millimeter in approximately this footprint but then you've got little tiny two two and a half inch props that are not very efficient right now I guessing this isn't actually going to be very efficient but in theory when you go to a larger prop you get more efficiency so instead of having a bunch of small props you can have one big prop right and get longer flight time I truly don't know what to expect with this this is purely a really cool proof of concept that Sean put together all I've done so far is made it hover this has been a labor of love and hate I have made four different prototypes of this and had four failures and it turns out that I finally just had to eat my pride and go and borrow somebody else's project this isn't my design I have to give credit the person who put it up on Thingiverse not only did they help me get a design that I knew was already working to work but their PID settings and beta flight turn all the filters off turn all the stuff out that we want in our quad racing drones just put it on the bare minimum just basic PID controller and it flies we're gonna break it right and the gravity oh I know we're gonna break it and this is plastic so it probably isn't gonna take much but I just wanted to have something working I've been sitting so much time on it let's just see if this thing actually flies I'm just excited to see it fly let's put this thing up who's gonna fly first who's gonna have the most gentle touch soft landing it's okay it just it just spun out sure that was seems alive still that was um what was it like to fly did it like was just shaky it was really shaky on the yaw axis it was and I wasn't sure how hard I could push the sticks before it would fall no no like a turn drink it won't even get the chance to break it cuz as soon as he touches the sticks it'll just fall over I'll be gentle I'm gonna try to do a gap I'm not saying you can't use y'all at all I'm just saying I think I think that's what happened is when I tried to yaw it a little bit too much it fell out of the air and it's straight pretty much and then once you try I mean I did turn a little but not like the sharp turn you tried to do at the end I don't feel like it was that sharp I mean yeah what did it break the veins broken a little bit it might still fly oh like it needs less authority why do you think that the current design that we flew today doesn't spiral out of control the main thing that I changed was I said you know what let me just go to somebody else's design that I know actually works I've seen this fly I've seen other people do it I'm not the first person to do this so somebody has to have a working design and finding documentation on this isn't easy so I found the one guy that I actually found enough documentation where I think I could get through the project from beginning to end and he used beta flight which is surprisingly all these designs up until this point we're using ardupilot there's so much history with ardupilot they've been around for so long I figured they know what they're doing and I tried to use that software and I don't know if they've just abandoned the monocopter software or if I'm just doing something wrong I don't know what I'm doing but for some reason I couldn't get it to work with the monocopter setup in ardupilot so I just went to beta flight use this other guy's PID controller do you think this is the problems you were having we're not actually problems with your designs but with your flight control I mean in theory you could go back to this guy and put maybe it would work yeah yeah yeah that excites me in a way that a monocopter has never excited me before I'm gonna let you get up first okay oh my god wow your flight is way more aggressive now it's so shaky let's get some nice smooth working on the tree yeah there you go that's awesome just doing it very small it's doing it it just makes one sound the whole time it's crazy it's not like that's why that's really interesting it's a mono sound yeah mono chronic monocopter it's like the controls feel dull like there's nothing in the center but then if you give it a little too much it's like you almost can't bring it back so it's like a fine balance of just being you have to be patient for and then I don't know what just did it just like I literally just went a little bit pitch back and it just like completely wigged out hopefully it's okay this thing there's no pushing it it has been such a journey to get here and it's so finicky I just want to experience it I'm just using very I see purple on the ground I still ended up being the one break it's not I was really committed to not being the guy this time cameraman okay okay well that didn't last long manual mode yeah like full manual yeah okay yeah let's let's try now we're in angle mode let's try see this works I'm just gonna give it all the gas oh yeah that's definitely safe decision it's far away you're ready to run all right here we go spinning all the gas okay maybe the fins aren't big enough


Welcome to All Hands Update. This is your week in Navy history. December 21st, 1861, Congress authorized the Medal of Honor, the nation's highest military award. On the same day in 1968, Apollo 8 launched with Navy Captain James J. Lovell Jr. as the command module pilot. During the mission, Lovell was one of the first people to see the far side of the moon. The mission lasted six days and three hours and included 10 moon orbits. Recovery was executed by HS-4 helicopters from USS Yorktown, CVS-10. On December 24th, 1814, the Treaty of Gint ended the War of 1812. Hostilities between Great Britain and the United States ceased and Britain agreed to relinquish its claim to the Northwest Territory. The United States and Great Britain also pledged to work together to end the slave trade. To learn more about the Navy's history, visit the Naval History and Heritage Commands website.