Hello everyone, welcome to the class engineering statistics again. So, in the previous lectures, we talked about confidence intervals and in particular we focused on how to construct confidence intervals using hypothesis test and then we talked about various test based on p values. So, in particular we talked about p values, p test, t test and f test. Now, in this lecture, we are going to continue our discussion of test of a hypothesis, but now we will focus on something called nonparametric estimation. That means, the one which does not need to make any assumption about the statistics we are going to use to make our decision either to accept or reject or null hypothesis. And then we will talk about various goodness of fit test for this nonparametric estimation. In particular, we are going to talk about three goodness of fit test. First one is chi-square distribution, chi-square test, then Kolmogorov-Spirnau test and then Deliphos test. Let us get started with what do you mean by this nonparametric estimation. So, the statistical methods we use so far assume the knowledge of the populations distributions and that too we assume they are parameterized. For example, we assume that the sample we have, we assume that this is where xi's are going to come from a certain distribution with a parameter theta and then we set up our test as whether this theta is at a particular value like is this theta corresponds to certain 30 and particular theta naught or r naught ok. And we did that using hypothesis testing. And in hypothesis testing if you recall, we defined something called power function which was like a beta of a theta that is defined as probability that my sample belongs to my rejection region. So, where r is a rejection region for example, r could come from your log likelihood ratio test which defined it like this. But notice that to compute these probabilities, we explicitly needed no this particular distribution and this probability was calculated under the parameter theta and when we try to give alpha level test, we try to find something like this belongs to null hypothesis right. If you and I hope you people all recall this discussions we had. So, in computing all this, we kind of explicitly needed to know the underlying distribution and this the probability of something falling under this region r, we calculated using the knowledge of this particular distribution. And we also looked into various statistics like for example, we use statistics to do t test and f test. But in doing t test for example, if you recall the t test we had something like x bar sorry yeah I think we had something like x x bar and sigma square and this is we assumed it to be Gaussian distributed right which was the case when it was when the samples are already coming from the Gaussian distribution. But we assume that this statistic is Gaussian distributed right or when the sigma square is not known we looked into the case when this statistics is student t distributed. So, we kind of enforced some distribution on the statistic itself which we used to make our decision right. But now the question is what if we do not want to enforce any distribution on the statistics beforehand that is what if my underlying distributions are not Gaussian and do I still need to make this make this assumption always to apply this test or put alternatively if I want to do certain these of this test I am invariably making this assumption that the underlying samples are coming from Gaussian distribution. But then how to check that indeed the samples are coming from Gaussian distributions for that itself we need a test right. So, thinking all of this we need a method where to know the distribution of the statistics we do not need to know the underlying distribution of the samples itself ok. So, keeping this in mind what we have so far discussed is all this hypothesis testing t test f test these are called parametric method because they explicitly made use of the properties of the underlying distribution or the parameters of the underlying distribution. And in this at least in the t test and f test they kind of assume that normality assumption work holds. But this is true only when we have large number of sample and in that case my statistics which was of the form x bar we could be think of following Gaussian distribution using our center limit theorem. But however, this is not the case when we have small number of samples and that is why before we are going to apply any of the hypothesis testing f test or t test that we used before we need to validate that the assumptions we are making on the underlying distributions of the sample is correct. So, to do that itself we need to have some statistics whose distribution itself does not depend on the distribution of the sample. If that is the case then we are going to call them as non-parametric method or distribution free methods ok. Distribution sorry I want to meant here distribution free methods ok. Now, suppose we want to check whether observed samples are going to follow certain distributions then we need to have have a certain test to check whether they follow the given hypothesis or distribution which is taken as null hypothesis and those tests we are going to now call it as goodness of test. Basically we are going to say that the samples we are going to observe are they going to follow given distribution and we want to check the goodness of that fit. Now, in that regard like assume that or like let us say you are underlying population distribution unknown and we want to check if the data follows a hypothesis distribution which I am going to denote as f naught. So, now the goal itself is like earlier when I have this samples I kind of assumed f i's are going to follow certain pdf or let us say some parametric cdf. Now, I am going to assume that this itself is not known I want to check this itself and that I am going to denote it as f of 0 here. Now, then what is my hypothesis now? Now, my hypothesis test my test can be now posed as that my cdf is that of f naught which I am hypothesizing it to be and this holds for all possible values of x and the alternative hypothesis is at least it differs at one point that is my distribution of the data points is not same as the null hypothesis distribution at least one point. Now, this hypothesis distribution now can be this hypothesis distribution can be either completely set specified with all the parameters. For example, this f naught could be associated with a probability density function which is Gaussian with parameter mu and sigma square here the parameters of the distributions are completely specified or it could be told that like our null hypothesis is a Poisson distribution with the parameter lambda or it may happen that this hypothesis distribution is only specified in terms of its shape for example, we only know that this is the null hypothesis is a Gaussian distribution that is it we do not know what are the parameters or we may be just told that it is Poisson distribution without specifying what the parameter is. Now, how to go about that how to go about checking whether my samples follow this null hypothesis for that we are going to see majorly two tests one for discrete random variables and another for the continuous random variables. In the discrete random variables we are going to use something called chi square test which is proposed by one of the famous mathematician called P. S. N. in I think early 800s. So, in this what we are going to do is compare the observed frequencies with that of the expected frequencies and the null hypothesis and as I said this will be used mostly for the discrete populations ok. And another test again introduced by famous mathematicians mathematicians and also statisticians Kolmogrom and Smirnov and variant of that by a Lilly force. So, here we are going to compare observed cumulative relative frequencies with that expected under the null hypothesis. So, notice that here we are trying to compare the frequencies of the classes I will make it a bit clear and here we are going to compare the cumulative relative frequencies of the distributions ok. So, we are going to compare cumulative relative frequencies ok. And this Kolmogrom Smirnov and Lilly force test usually is going to apply for continuous population density and more specifically Lilly force will be applied to check whether the underlying population is a Gaussian distributed ok. Now, let us focus on the chi square test. Now, our we want to test whether my observed data follows a given discrete population which I do not as F naught and we are going to assume that that is completely specified. For example, if it is Gaussian sorry we are going to talking about a discrete here maybe this F naught my distributions can be Poisson with lambda. So, here I am specifying the parameter or it could be let us say binomial with parameter n and p where both n and p are specified. Now, in this case if I am given a data I want to check whether it follows this CDF how I am going to do that. To do this I am going to group my data into k classes. What are these k classes? For example, let us say that my random variable x is there which is going to take values 1, 2 up to k ok. So, then there are k classes or my random variable is that it may just take value like head or tail head or tail. So, in this case my k is going to be 2 these are the 2 classes and similarly if it is let us say dies you have obviously 6 faces in which my k is going to be 6 like that. Now, what I will be interested in the expected frequency of the class i. Suppose I have this Poisson distribution let us take Poisson distribution let us say my x is Poisson distributed. Now, I know that x is going to take the value x is going to take the value 0, 1, 2, 3 like this or maybe Poisson instead of Poisson let us take maybe at this point it is easier to work with binomial. Let us say my x is binomial distributed and I have let us say the samples n samples and I know that probability that x going to take value some i is going to be n choose i p to the power i minus i and 1 minus p to the power n minus i. Let us call this as theta. So, this is the probability of observing value i and then my samples the expected frequency of observing class i is in this case is going to be n of theta. That is if I have n samples the expected frequency of observing the class i is going to be n i in this class. So, that is what I mean by E i here and now F i is the observed frequency. What is this observed frequency like now let me write this observed frequency here this F i is basically how many times you have observed maybe I will write it as j or maybe it is okay to write i, but maybe F i is equal to basically j equals to 1 to observed j indicator that your x j is equals to 1. So, it is basically counting how many times you have observed sorry this is i here. Now, observe your random variable has taken value i out of your n samples. So, this is your observed frequency of class i and this is the expected frequency of your class i under your null hypothesis. So, notice that under null hypothesis because my null hypothesis is completely specified I know what are these theta. Now comes the statistic. Now, what we are going to do is we are going to check how far this F i and E i's are. So, we are going to look into the difference and take the square of that that is basically the square difference of that and normalize them by their expected frequency and then submit over all the possible classes. So, this is way in a way this matrix is going to capture how different the expected frequencies and the observed frequencies are. Now naturally once we have this if this difference is too large it is kind of indication that maybe these what is my observed sample is not following the null hypothesis. On the other hand if this difference is small or this summed difference is small then it is a kind of indication that yes maybe it is like it is a kind of indication that my observed samples are following my null hypothesis distribution. So, based on this distribution one can compute or make a decision whether to accept or reject the null hypothesis. So, as we did earlier again we can set up a threshold and let us say for a given threshold Z alpha we are going to accept the null hypothesis if this statistic is going to be less than or equals to Z alpha and we are going to reject this h0 if it is larger than certain this threshold Z alpha. Now the question is can we quantify like how good or bad is our acceptant decision. So, now we may want to compute what is the probability that I reject my sample can we compute this probability and that under a null hypothesis. So, this is we want to quantize and if you are able to say that this is like less than or equals to some number then that is going to give me the significance of this test with that number. Now then the question is how to compute this probabilities do we know about this distribution. Earlier when we talked about hypothesis testing we kind of assumed this this statistics we assumed it distribution right we enforced its distributions to follow Gaussian distribution or to compute its distribution we needed to know the distribution of the underlying samples. But now in this case I am only looking into the empirical values of F i see here q is still a random quantity because this F i's are random here ok. Now will I be do I need to know the underlying distribution of my samples to compute a distribution or I can say without knowing that it. So, happens that in this case we do not need to know the distribution of the underlying samples and in fact, one can argue that this q is roughly distributed as chi-squared it has this q has chi-squared distribution with k minus degrees of freedom right. So, we will we will discuss more about that why this is the case. But notice that without requiring what is the underlying distribution of my samples I can argue that this q is going to satisfy chi-squared distribution with k minus of degree. Now once I have this I should be able to quantify the significance or the level of my test by setting my threshold appropriately particularly an approximate alpha level test is obtained by rejecting your null hypothesis when your q is larger than 1 minus alpha fourth quartile point of the chi-square distribution or like if you are if you want this alpha test we need to set z alpha such that your p of x is greater than z alpha is alpha where your x is chi-square distribution with k minus degrees of freedom. And since we know this chi-square distributions well we can compute it is a tail probabilities and tabulate them and for a given value of alpha we already know how we should be selecting z alpha so that my test is has a alpha level significance or it my test is a alpha level test. So, good now what we have argued is without knowing the distribution of the underlying samples we are able to say that my statistic has chi-square distribution and we can use readily available table to compute the significance or the level of my test or how should I set up my threshold so that my test achieves a given significance level. Now this test works well when or like this approximation that your q is going to follow chi-square distribution with k minus of degrees freedom well when the expected frequencies are more than 5 that is when your EI is greater than 1 for all the classes. This need not be the case all the time but this is a kind of thumb rule which will can be used when you have when you want your approximation to be good. Like for example, we said that EI is going to be n into probability that your random variable takes value i equals to n right. So, whatever this is like theta i this is known under your null hypothesis if your n is such that your it makes your EI larger than 5 then this is a very good approximation. Now composite distribution as I said every time the null hypothesis may not be completely specified only the shape may be given in that case we call the distribution is composite and now how to go about in this case. Now in this case let theta i's are the probabilities of the class now because the underlying parameters of the distribution is known we do not know this theta i exactly. So, what I mean by this suppose for example if x is Poisson distributed we know that probability that x equals to i this case theta i is equals to e to the power minus lambda I hope I am going to make it correct and this is i lambda. But so to compute this theta i I need the knowledge of lambda, but what if I do not know this. So, in this case you may estimate this lambda itself from the data that is if you have your samples you can estimate your lambda to be the empirical mean of this data and we know that this is a good estimator it is an unbiased asymptotically it is consistent and all and then once we have this we can plug in this lambda i's in this expression here and then you may get lambda hat lambda hat i and i fat and that is what I am going to call it as a theta i here based on the estimate. Now once I have this now I can also get an estimated frequencies which is now theta i hat. Now all I need to do is for my given EI values now I need to compute my statistic which is same maybe I had to write this as f i I think earlier I wrote this as small f i and I have this value only thing is I have replaced this E by n theta hat 0 subscript i here. Now what about the distribution of q? Does it follow the same distribution like we had earlier like which is a chi square distribution with k minus 1 degrees of freedom. It so happens that when the parameters that you are going to estimate are based on maximum likelihood estimator then indeed one can argue that q still remains chi squarely has a maintained chi square distribution. The only thing is now the degrees of freedom is now k minus 1 minus s. Now what is this s here? Earlier it was k minus 1 now you are saying it is k minus 1 minus s. Now here s is the number of distributions parameter that we estimated. For example here in the Poisson we estimated one parameter. In this case if you have to apply this method so then let us say we have observed only some k like even though there are infinitely many classes in this Poisson distribution because k the x can take value from 0 to infinity. Let us say you have in the samples that we have observed in this I only see certain k number of possible classes they belongs to let us say only k classes. So in that case my k minus 1 and minus one more term one is going to come because I have estimated one more parameter. So this is going to be k minus 2 in this case.


Hey what's up folks! In this project we're making a visual light display with Neopixels. We designed a lamp with edgelet acrylic and added Neopixel LEDs. It looks like a frame-by-frame stop motion when each pixel is lit up one at a time. We thought it'd be fun to engrave some festive designs in different shapes. The acrylic panels are swappable so you can use this to make all sorts of creative animations. For this project we have it powered by the QtiePie RP2040 running Circuit Python. It uses just a single strip of Neopixel LEDs with a total of eight-quarter inch thick acrylic panels. We engrave some snowflakes and letters but you can do all sorts of fun arts and graphics. For any Neopixel project we like to use Circuit Python because it's easy to use the LED animation library. We strung together a few chase animations using the animation group module with each one having a different color. We set the timing to a quarter of a second so each panel has a little bit more time to be seen. The LED animation library makes trying out different settings really fast and easy. The LED strip is fitted into a 3D printed holder with each LED fitting into a little cavity. Our 3D printed holder keeps the LEDs isolated so the light doesn't leak into each other. The acrylic pieces feature tabs that are press-fitted into slots that are on a separate holder. They're placed directly over the LEDs so they're nicely edgelit. The parts are made with PLA filament and they can be printed without any support material. All you need to build this project is a strip of Neopixel LEDs and the QtiePie RP2040. The bottom cover features a built-in holder for the QtiePie and has special edges that snap fit into the 3D printed case.  The assembly is modular with the parts snap fitting together. I designed the holders for the LED strip and acrylic to be parametrically driven. This means updating the pixel count will add or remove slots from the design so it's easily scalable. The CAD files are free to download, links are in the description. We hope this inspires you to check out the QtiePie RP2040 in Circuit Python for your next light-up project. From everyone at Adafruit Industries, happy holidays and happy New Year!


Okay, okay, okay, I am sweating right now. No! Unbelievable! How's it going everybody? Dato do it back with some more Dragon Ball Fighter's Rank Matches. Today we're playing a team of Beerus, Base Goku, and Yamcha. Now overall, this team is very focused on those high blocks to assist. Oh, maybe I should have had trunks. That assist is pretty good too. But it's really just supposed to make Beerus, you know, get in there and do some work. Oh god. All right, we should be fine. Let's go. Couple of Keyblast, and we are just going to switch this dude out for Goku GT. That might have been a mistake. Oh, never mind. We are doing fine. I'll mess that one up. Yeah, but if he's just going to give it to me. No, he's too small to jump. Dude, this guy is mashing hard. If I can DP here, rest assured I will. Dude, I just love Beerus' DP so much. It's the ultimate get off me tool.  Might regret. I'll just knock him down. Got him. Damn it. Oh, nice reflect. But how are you going to handle the Yamcha assist? You've got to hold it. It's block or be killed. And two, three, and just a little. One Beerus orb should get the kill and then it's just going to be honestly, as long as we get like a clean Super Dash into Yamcha assist, we should just get a clean mix to make it over. There it is. That's clean. Oh, reflect. Oh no. Oh god. Who's doing the mixing? Who's mixing who here? Okay. All right. We get to reflect. I mean, I don't have to vanish. DP. Okay. Nice. DP. Oh no. Imagine trying to hit a Beerus while he's in the middle of his DP season. Imagine trying to touch a DP. Let's go. Beerus. Oh my god. This character is fun. I honestly do enjoy Beerus a ton. He has a ton of problems though. Like if they fixed up a couple of his normals, I think Beerus could be maybe not top tier, but enjoyed by a wide air populace of people players just to get him in the corner, but unfortunately we miss heavy. There we go.  Dude, if they don't know how to play against Beerus, forget it. It is top tier. If you don't know, you don't know. And Beerus is not going to take pity on you for that one. Yikes. Miss the light, though. We could be looking at death here. Three bars. Side switch. No, we're not looking at death. That was an extension though. If I got to give something up, it's got to be that one, dude. If I'm giving anything up. Okay. Get back in the corner. I didn't know what I wanted to do there. Oh, indecisiveness killed me. Nice dragon rush. Hit it behind the trunk. This guy's got some tricks up his sleeve. Down tech? Oh, never mind. Yep. Never mind. We're playing on his rules. All right.  But I'll have you know I have house rules on my own. I'm out. Now you could vanish, but don't rush it. Or you could run behind. That is also an option. Damn.  Oh, I regret that choice. Goodbye, uh, didn't fall for the reflect. And now we're just switching back out into Beerus. Yep. Oh, he tried to reflect too. He knew the pressure was coming, but I also knew that he knew that, dude. Oh, wow. We actually do clash there. That has too many. Dude, Beerus is just crazy.  Okay, I'll block that. I'll try my best anyway. Nice overhead. We're dead. As long as he knows the spear bomb stuff, which I don't think he does, but maybe he's got something else. Does this kill? I'll be impressed. I thought he was just going to go with the spear bomber out. Nah, we good. Right, deep being. Nice. All right, Yonche. Actually, no. Basically, he's powered up now. Do this to get the sliding with it. I got it. It's too late. You can kill me. Oh, and I think you will very much take me up on that offer. Oh man, I was, I meant to say you can combo me, but you won't kill. But clearly that was wrong. Damn. I thought I'd take a little bit more of a beating than that. What a mess of a combo. That's not hitting. Yeah. I couldn't decide if I wanted to move. Death. Nice. It is death. Is that three games? No, that's two. That's two. That's two games. No way that was three. Yeah, that was definitely two now that I'm thinking about it. Just a longer second half to the second one. Dude, Beerus got a moment in there though. That block pressure into a dragon rush. That's exact. That's textbook Beerus. All right, living legend. But he was on the verge of Super Saiyan Rose. Trunks assist. That's a sliding. Oh, he extends it all the way into the corner. But both of his assists are down now. This is a bad, it was a bad place to be for him, but he got a read. Dude, he's not letting me get away with any fake stuff. We're out. You know, oh, I can't believe it. Oh, I think that was cross of protection that saved me in the end. No, no jump. Over at Yancha. Come on. Back off the boy. I tried to put out a orb. No. Oh, no. All right, we're good.  He held that for so long. I was like, all right, we're good. Dude, I'm getting, I'm like, I'm going for so many cheese options and he is ready for them all. I should have jumped. Why did I try to mash? Oh, we don't have to spark you for this either. I tried mashing again. This is his round, dude. This has been nothing but nonstop offense. But how is Yancha going to stop it? No sparking Yancha? And yet, why do I feel so confident? Yeah, why am I so confident in the club right now? Four dash. Four choice. Oh, this guy's crazy.  It's time for you to be mixed. Level three, coming in hot. Okay. All we have to do is not get touched ever. Again. Oh, these assists. No way. Unfinance. Did you see the way he hit that medium and immediately down heavy? Damn. No, that was a, that was a thorough washing. God damn. Dude ran me on rinse cycle, bro. He's moving now. He's got the confidence back. Oh, no. My confidence is shattered and his is at an all time peak. Oh, dude, he's confident. I'm all about this confidence, but I'm not enjoying being on the receiving end. Oh, dude, I'm trying every cheese option in the book, but he wants to see something real. Cheese options are not options in this guy's eyes. And you know what? I can respect that. That's why I got to give it to him, dude. That's why I got to be real. That's why. He's too small and I got no meter. No. No, I could reflect. Oh, no. He's coming in too hot. God, the six frame delay is really coming in. Seven frames now. Not the seven frame mix. Dear Lord, not the seven frame mix. Okay. Okay. Everybody stay calm. Everybody stay calm. Stay calm. Stay calm. Stay calm. Please hit. Beer is nice. Okay. Okay. Okay. I am sweating right now. Unbelievable. I became a rage quitter, dude. All right. Well, all we can do is play a game and apologize to that last guy, dude. I am... I don't know why that happens. If anybody does, let me know. Oh, geez. At least it's another trunks. At least I hope if I lose to this guy, that guy that other guy is watching is like that could have been me. That was the longest Super Dash I've ever had the pleasure to be a part of. That was so crazy. I really didn't even feel that high off the ground.  That's not as safe as I'm making it out to be, apparently. Oh, he tried it. Snagged this man. Boom. Back in the corner. Ah, that was kind of cheesy. But imagine if that setup worked. That would have been pretty cool. Just bounces back up into a drag rush. Much like me. DP. Now who's getting mixed, bro? Look at how the tides have turned. If he flips again, we down heavy. Damn, I got panicky, clicked down light. Now I'm living this life. Not the life I wanted to live, but I think it's the life I deserve. Is he going to go three level ones? He is, and that's going to be the death of Beerus and the start of the Yamcha arc. Nope, the Goku base, the base Goku arc. That's fine. Goku be Goku, I like my odds. My odds are dying. No, dude. Wow, his light hit. Man, that assist. Okay, is this far enough for a snap? It is. Don't level three. Got him. Got him. Got him. Does this kill? No, but can we somehow buy enough time to get? That's fine. Oh, I am so mad I had to spend another bar on that. I forgot his Kamehameha is only one hit for some reason. Weird choice. Back dash. That works out fine for us. Ah, we have to spend another bar. Sliding in the corner though. Come on. Nice switch, dude. I tried to get the... I tried to get something else, but it does not matter now. The assist hits. This is at least a hard knockdown. If not, like something else he has planned. I'll take it. I'll take it. No, poor choice. Uh, no, there's not much we can do here. I guess I could... No, that was supposed to be a normal one. Let me hit you. Very good reflect. All in all today, people have been doing a good job reflecting the fake Yamcha stuff. Does he snap out? No, he wants the hard knockdown. We just take the mix. We have to. We have to. Oh, I wish my teching skills were better. No drops. That's a one bar kill. Base Goku has never been this powered up though. Come on, Base Goku. Come on. We're living. We're living. We're living. We're living. Two bars is not enough. Let's go. I deserve this. I deserve it. I deserve it. I deserve it. I deserve it. I deserve it. Oh, but I deserve it. I can't complain. I can't complain, dude.  I deserve it. Oh, just kick me while I'm down. Thank you so much for watching this video. Sorry that that disconnect happened. Yeah, yeah, it was fun. It was. I'm sorry the disconnect happened seriously, dude. I don't know why. I'll look into it online now. That doesn't happen too often to me though. Other than that, while you're down there, if you like these videos and you want to see more of them, make sure to hit the like button and subscribe to the channel. It's the reason I can keep these coming out to you as often as I am. So if you do enjoy them, that lets me know that I should keep making them. Other than that, there's some videos up on your screen. If you happen to miss any of them, make sure to give those a watch as well. But I have been Dr. Doya. Thank you so much for watching this one and I will see you in the next video.


So, in the news, Governor Samal Autumn of Benway State on Friday pledged that the 18.5 billion-dollar loan approved for states by the federal government through the Central Bank of Nigeria, CBN, will be judiciously applied. The federal government recently approved a loan facility of 18.5 billion-dollar to be disbursed to states with a moratorium of two years and a repayment period of 30 years. Governor Autumn spoke to newsmen in Maccordia, the state capital, acknowledging economic challenges faced by states of the federation, including the federal government, which has led to borrowing of trillions of naira. According to Autumn, the state executive council will make or meet, rather, to deliberate to take appropriate decisions on application of the loan. As a government that is transparent, I will sit with my state executive council who will look at those areas. Two years are better than one. When I sit with them, we will actually agree on how best we can appropriate this money and it will be effective and have impact and add value to the development of our state. But on the whole, I welcome the development. It's a good thing. At least we are not stealing, we are borrowing. People say a literal translation that because you are a man because you borrow. But when you see it's an offense, but this is why it's not stealing, we are borrowing and we'll pay. I've been paying debts of apérico. Even my three regimes that were here in Buenos Aires have been paying those debts. So there's nothing wrong.


So let us kick start and the rest of the people who will be joining a bit later can take the participation. So welcome everybody. And it's a pleasure to do one more webinar together with our Harvard Business School alumni. This is an exclusive session with our leader, Sam Almizano, chairman of the Center for Global Enterprises and former chairman and president of IBM. And Chris Kane, president of the Center for Global Enterprises and president and CEO of Mercator 21. My name is Marco Kovachowich and I'm an OPM 52 class and I'm a founder and CEO of Signet World. And basically I'm fortunate to work together with Sam and Chris within the Digital Supply Chain Institute, housed within the New York based Center for Global Enterprises. You will hear more about the CGE from Sam and Chris and you can all find common thread that it's closely correlated with today's topic, the future of business and the role of Digital Supply Chain. Please feel free to think, share and react out because collaboration and cooperation with businesses worldwide is in the core of the both organizations. Before we start, let me share just the basic housekeeping rules. We will be recording this session today for our records and we will be sharing it with you after the event. We will begin with 25 minutes, let's say presentation and then we'll go to an open Q&A. Please ask your questions within the format of the chat and followed by your name because we will be then creating the Q&A list and we ask you kindly not to add any comments or thoughts into your questions because you will be asked to do a verbal question directly to the speakers after we create the list. Now we know that we are very limited with time so this is why we ask you to keep it short and direct so as many alums can ask the question. For the ones we will not be able to answer because of the time limit, we are committing to answer in two weeks time and send it to you along with the recording of this session. If you have any questions about the Center for Global Enterprises or Digital Supply Chain Institute, we will provide the contact details to all of you at the end and if anybody is willing to take the conversation forward and have one-on-one calls, we will be glad to create that and organize that. So now I think it's the time to start our session and to create together one-of-a-kind Harvard experience. So dear Sam, dear Chris, thank you very much for being here with us. Thank you very much for contributing to create this session and thank you for working on the future of business. So the floor is yours. I agree, thank you Marco. This is Sam, let me start and then I'll pass it to my colleague Chris.  But we, when I retired from IBM, I thought that it was important that we fundamentally create an entity that could advance learning for future leaders because we felt that there were gaps relative to what was happening, at least as we observed in the marketplace. And so Chris was kind enough to join the initiative with me and become the president which actually done most of the work here and helped us get this thing to look, I think in mature state. I just will spend a second on the board because the board is heavily involved and it makes sense when we talk about our research agenda and I'll just highlight some of the people, I won't go through everyone, but I think you know some of these folks. I mean, if I start with the, I'll start with the entrepreneurs. Jerry Yang is an old old friend from Yahoo days and then as you know, Ali Baba now zoom, zoom now is a hundred billion dollar valuation. So Jerry's doing quite fine from a technical technology investor perspective. Another gentleman, if I stay in that path is Jim Breyer was also on our board. Jim ran Excel for a long time, another Harvard graduate by the way, Stanford, Harvard. He was one of the first investors in Facebook. And as he said to me, you know, you don't need many after Facebook. And so the cost basis of his Facebook stock is a nickel US 5 cents. So he's done fine. If we go through the outcome, a little bit on the academic side, we have a gentleman by the name of Michael Spence, Nobel Prize laureate who ran the graduate school of business at Stanford. He's on our board and great economists, Kevin Warsh, he was yesterday in the Wall Street Journal but was up for the central bank in the US and the bank of England. Also a professor at Stanford works with us. International, we have some international members but I think I'd like to highlight the issue of G. Lee, the automotive company who acquired Bobo. So, and then we, you know, I have like showing Lazarus who ran Ogabee. I think it's one of the best marketing people in the world. So the point of that is that they go through necessarily those people, but they're all engaged and they work with us and they were heavily, they were providing great advice of how we should structure CGE, which gets me to the point of what I'll call the research agenda and then I'll explain the institutes but on the research agenda, we decided to take a different path versus just say CGE or Chris and I pick a topic, go work with some leading academic institution, whomever it happened to be, Harvard Business School, let's say whomever, right? And do research from the academic dimension. We felt that this should be much more pragmatic. So we went around the world and we did, we had these meetings, exchanges with CEOs. We started in China, partnered with Peking University. We did it at Stanford for the US side. We went to NCI for Europe and ITT in India and we had over a hundred CEOs tell us how they thought we should structure the research and they all gravitated to supply chains. Before I go to supply chain, there are others in CGE that might be a venture. So one is we're developing African women entrepreneurs called AWAC. That's been great. We've done about six or 700. We're about to start another cohort there. We've done a lot of work around engaged in investing in activism to the Applied Corporate Governance Institute. Many of us that ran the Obama Commission on Cyber created this institute afterwards called the Cyber Readiness Institute, which is now housed in CGE. And then lastly, we have a scholars program, a global scholars program. Chris can take you through the numbers, but it's thousands of kids around the world in various schools that are all participating in that. As we produce content, we try to make it available to these young people. What happened in the research getting me to the digital supply chain, which was the first one we did, the CEOs really came to the point that, hey, the most impactful thing that we could work on was research around the digital supply chain. And as we all know, the digital supply chain touches everything in the business from the customer, the revenue side to the cost of productivity side. It's end to end. And so, and there was a tremendous amount, this is before we got into all the issues around trade and those sorts of things of populism, but there was a tremendous amount of understanding and they saw the impact of technology was going to play in the future of these digital supply chains. So that's where we launched all of our initial research. And we did a lot of work there. What happened recently, and we'll go to the next slide, is then we run into this pandemic, right? And so that when we ran into the pandemic, our colleagues, and we've done a lot of work at CG through DSCI, but our colleagues all sat there and said, you know, we have two challenges. The first challenge we have is a business which you see the details on the chart, but fundamentally it's just, how do I recover? What does it mean to recover? You know, what's necessary? Now I'm back, I'm going to take you back to like March timeframe, you know, right? In the early stages of this thing, especially in Europe and United States, what does it take to recover? What do I need to do to make my, company safe for my employees? How about my employees? What do I do to take care of my workforce? What do I do to maintain my relationships with my suppliers and my customers? And then what I do to deal with availability issues if I have any kind of constraint because the pandemic, as far as getting key components of parts, whatever it happens to be into the companies, I mean into my supply chain to get the products or the services, what have you to the actual end user themselves. And of course, then there was the financial crisis at the liquidity side of the whole issue. And some of them were just scrambling to maintain cash flows. Now governments have done a lot along the way, both in New York and the United States, the South, some of that, but no one at that time believe that the government's was talking about a V-shaped recovery, especially in North America, but none are corporate colleagues. The guys running these businesses believe this thing was anything but more like a W of anything. It wasn't going to be bouncing all around for quite honestly, most people are saying to 2022. So the first phase of where we did a lot of work and Chris is going to get a little more detail on DSCI, but a lot of work around what does it mean to kind of stabilize? How do you keep yourself going in this tough environment, especially with industries that are being really impacted by entertainment restaurants and those sorts of things, apparel, cause people can't get in the stores and shop. Now obviously there's the other side of this where things are booming, like healthcare, Zoom, like we're using today, a hundred billion dollar evaluations I mentioned earlier on and on and on. So the first phase of all the analysis and all the research we did is around stabilized and recover. Then from there, which we learned quickly in our colleagues that worked with us in DSCI, I realized that it's more than just stabilized and recovery. It's about retool. It's really necessary that we retool the supply chains. And if we can go to the next chart, I'll go back on retooling. Basically, if you think about it, I mean the pandemic brought out all the vulnerabilities of the pinch points and their supply chains. Key components, you hear about all the time when it comes to PPE equipment or in pharmaceuticals and those sorts of things depending upon where you're positioned. You have too much risk, you're too concentrated in one geography for a source of a key component. It's true in the APIs at pharma. It's true for semiconductors and those sorts of things. And people realize that beyond just populism and trade wars and all those sorts of things, there are serious things that need to be addressed of these pinch points. At the same time, they need to look at location for resiliency, not just for cost, but now resiliency is the supply chain. And then beyond that, let's put technology on top. So if you're gonna do these things, if you're gonna analyze in your supply chain and it's called how to make it more flexible and agile, more resilient to minimize geographic concentration, you might as well also think about the same time making the investment to add the tooling to this or the technology to this to really make it both resilient, robust and positioned from a responsiveness, quickness to the market as well as cost perspective by exploiting all the various technologies. And CGE and DSE have done a ton of work around technologies, whether that's blockchain, whatever it happens to be, demand calls on AI and go on and on and on in nature, the capability, the competencies, the people, but Chris is gonna give them a detail. So fundamentally, we did a ton of work. In addition to the charts we've shown here, we've done a lot of work with governments explaining to them what it would take to re-stimulate demand in the supply chain and what you could do because we believe that after they stabilize them, two or $3 trillion packages of stabilization, but none of that is aimed at generating end demand that actually businesses need at the end of the day to get back to growing again. So we did a ton of work, ton of analysis to help governments think about what's necessary through the supply chain to stimulate end user growth and more demand. With that, I'll pass it to Chris and I know at the end we'll be taking your questions. Yeah, great, thanks, Sam. And Marco, thank you for arranging this and welcome everybody. I wanna extend what Sam was saying about why we got into the supply chain area. You know, we convene, at CGE, we do three things that are kind of an organizing principle for how we conduct ourselves. We convene, we create and we collaborate. So we convene leaders, senior leaders, CEOs and C-level executives to try to understand what they're dealing with. We create content to be responsive to those challenges that they are having a hard time with. Sam mentioned finding ideas and solutions elsewhere. And then we collaborate to make sure that those ideas and research deliverables are actually relevant and practical. What I'm showing you here is that when we launched the digital supply chain institute, we convened a number of companies around the world and these are some of the logos that you, from those companies who have come to our activities. Vivek, can you go to the next page? And you can see that it's pretty extensive and very diverse, diverse by size, diverse by sector, diverse by geography. And so when we bring pre-COVID, when we were able to bring people together face-to-face, as opposed to Zoom, we brought people together all around the world. And if you go to the next slide, Vivek, please. These are the locations in which we brought these executives, Oh, hang on a second. There we go. We convened executive, what we call digital supply chain executive leadership forums. And you can see here in the various locations in which we did it. These were really powerful opportunities to make sure that we had a clear view of what the management needs and management research, applied management research topics were that were confronting yourself, people like yourself and other leaders of functions in the supply chain business. So, but COVID arrives and we have to change our approach to our convening, creating and collaborating. And we shifted to Zoom-based collaboratories. We call them collaboratories. Some people call them webinars, but we think our collaboratories are more interactive and therefore more real time in the creation of activities. We've held a number of collaboratories on a number of subjects since March. But the core essence of what the digital supply chain institute is doing is around looking at the management competencies that are necessary for supply chain transformation and execution. And as Sam said, when in three years ago, 2015, actually five years ago now, CEOs from around the world said, no, I'm struggling with how to transform my supply chain from a physical traditional supply chain to a more digital supply chain. The rest of society, many other parts of my business are increasingly transforming to a digital reality and digital execution, but my supply chain isn't as far along as it needs to be. And so that's really what we took up the flag to go and to do into create applied management learning around. So these are the areas that we have worked on over the last four years to try to help executives deal with the transformation of supply chains and the power and the leverage of digital supply chain models and execution. We produced a vision in cooperation with these companies called the Frontside Flip. Let me just say it very simply, it is how do you take a back office activity that traditionally was a supply chain and make it customer present, make it on the front side of the marketplace decision making, the customer decision making. And this is a pretty powerful objective if a company can pull it off. And we see examples of it today, but very few companies have moved to the management kind of transformation and adjustments necessary to execute it on a regular basis. So we've looked at things about the new customers.  And yet the customer that companies have today has been changing. We entirely, we make decisions as customers, whether that's B2B or B2C and entirely new in different ways. And so what we have been looking at is the profiling of the new customer. And if we have a new customer, they have to have a new supply chain to meet the needs and to address the needs of that new customer. So we've looked at how do you make digital supply chains more resilient, as Sam was saying. Algorithms are a core daily working element of any supply chain and any business in today's world. But what we've heard from our supply chain leaders and participants is companies are not managing their algorithms the way they manage other assets in their business. They're very siloed, they're not horizontal management. And so we've done a fair amount of work around how do you create a management process and a management system so that you can have extended functional value coming from algorithms that may be within one portion of your business but can be used and valuable to other functions in a horizontal manner across your enterprise. The number one priority that supply chain leaders have told us over the last four years is people and their talent pool. And they acknowledge that they do not have the talent today and we're from their traditional supply chain functions that will be needed to be competitive and winning in a supply chain of the future. And so we have spent a fair amount of time looking at executive leadership and talent development. We have a course that we've developed for members and non-members that is around digital supply chain executive leadership. We have also looked at the general concept of change leadership in a digital world. And what we've been told time and time again is the way I used to do change leadership or organizational change, pre-digitalization isn't working in this new world. And so therefore how do I, once I have a vision how do I get everybody on board and how do I move the organizational on? So the re-profiling of skills and the different strategies for organizational change in leadership is another area we've been involved with. Obviously metrics can't do anything. It can make any progress unless you have metrics that are relevant for where you're trying to go and what you're trying to do. And then we've also looked at the value proposition of data. You have more data than you know what to do with. Some of it is of excellent quality. Some of it's not very good quality, but you have data that is probably unoptimized from a value standpoint and for you or maybe just isn't that important to your business. Yet for a customer or a supplier it might be exceptionally important. And so we've looked at how do you value and how do you utilize your data assets, these intangible assets that you've got the same way in which you would if you had tangible assets that were in excess. You wouldn't let them sit around and just be carried on your books. And yet what we've learned from so many companies and leaders that we've worked with is they don't view data and intangible assets the same way they view tangible assets. And so we've done a fair amount of work on how do you create a data trading framework with a supplier or a customer that will allow both parties to gain more valuable insights about their business going to market and their value proposition. And then we, as Sam said, we've looked at a number of emerging and cutting edge technologies and how do you capture value from those high impact technologies such as blockchain. We've done a lot of work with blockchain. We've been through the hype cycle and the sobriety cycle. Blockchain, it works, it's a valuable technology but it's only part of a solution. And I think companies are now starting to pinpoint where that value and where that solution can be supported by blockchain. So maybe we can go to the next slide. So these were the collaboratories that I was referring to before. Since March, you can see these are the companies down below or the companies who have spoken at those collaboratories. We've tried to make them geographically diverse, sectorally diverse, which is how are you dealing with your supply chain in this COVID environment? And we're happy to show any information from those sessions with you. Let's go to the next slide. And so before we get to the Q and A, I just want to close with something Sam alluded to based upon the work that he was describing that we've learned over the last four or five years about supply chain. CEOs often refer to their supply chain as a critical must deliver responsibility for them. But if they can't get their supply chain to be operating efficiently and in a optimized way, their job is at risk. Well, in today's world, we also see supply chains as a path to the top because of the changing nature of supply chains. And there are increasing examples of people who have led supply chains and enterprises who are now becoming and or now are CEOs. And where we stand right now is that executives are telling us my supply chain has to be resilient if it's going to be dynamic enough to propel and sustain my business. At the same time, I need help with demand accuracy. The world is so uncertain right now that the demand forecasting, demand management, demand mechanisms I've used in the past aren't working or are bad and I know they're bad and they have to change. So we have been doing a lot of work around demand accuracy at the company level. And quite honestly, our goal is to eliminate the demand forecast as a management tool and to make the ability of a company to understand demand by being customer present at real time data element and data source. So let me stop there and Marco, turn it back to you and maybe we can open up for questions. Thank you very much, Chris. And thank you Sam for sharing the insights and thoughts and everything what you have been working on. I would as well ask once more, all of you please to just type into chat. You don't need to type the whole question. You can just type your name and raise the interest so then we'll follow that order. So we can follow it in a way that it's suitable for the panelists. And now we can start because we have the first question coming from Alex Fernandez. So Vivek, please let's give Alex a floor. Hi everyone, good morning. Hi, Sam, Chris. Thanks for coming. I think you guys can hear me. Yes, we can. Perfect. My question here is how have you found organizations responsiveness to having to change their perception of how they judge their vendors from a standpoint of cost but moreover to a holistic threat perception? Can they deliver? Are they in a country of risk? How are they doing that now with COVID? Do you think it's gonna change or will it go back to a race to the bottom? Alex, I'll start and then I'll pass to the Chris because I think when you get a couple of different perspectives here, most of my colleagues that I've been retired for a while but I still stay in touch with a large number of these CEOs around the world, they all believe that there's gonna be a lot learned in the pandemic and that learning is not, they're not gonna get back to the old ways. And we can talk about lots of examples in this path of technology but I'll just stay on supply chains, for example. I mean, as you know, there was reliability and cost-driven, we all scaled supply chains, IBM had a lodging, especially we were in the PC business, we spent about, I don't know, 70 billion a year, component costs and those kinds of things. So it was sizable, needless to say, and it was globalized. But my point is that everyone now has learned that you can't have a critical pinch point, you have to have redundancy. I mean, that could be a vendor strategy, quality is every bit as important, stability of the supply chain. I'm also involved in an initiative that's being run with International Chamber of Commerce on trade financing for small companies in the supply chain. But my point of all these examples is that, people have realized that this could happen again and the focus that was strictly on, say, quality and cost is now gonna become broadened. Now, I know there's a debate in that and I've been engaged in a lot of these debates but I would say the more thoughtful people in these discussions certainly understand if, yes, look, now's the time to invest, let's be honest about it, because dependent upon where you're positioned, other than in tech, valuations are being crushed. Take tech out of it, take the top 10 tech companies out of the S&P. So therefore, if you're a public company, you have financial flexibility and you need to redesign your business models and your supply chain. And a lot of these guys just say, now's the time to do it because my stocks been crushed anyway. So let's get on with investing for the retooling the supply chain as well as I'll call it the digitalization journey. Chris, I'll pass it to you. Yeah, it's a good question, Alex. What we've seen and what we're hearing from companies we're working with is kind of two things that I would comment here. One would be visibility of their suppliers is more important than ever because we are clearly in an age of disruption. But the disruption, as Sam said, is not gonna end with a vaccine for the coronavirus. The age of disruption seems to be faster, more accelerated and more constant. And so executives are trying to understand how do I get visibility, reliable visibility for my suppliers? And because I need those suppliers to be reliable if my supply chain is gonna be resilient. Technology-driven integration ends up being a key to allowing that visibility to be evident as well as valuable. And what we experienced with blockchain is not everybody wants to be integrated so that visibility is enhanced. And if an ecosystem or if a group of companies finds common value into having visibility across the processes that link them, then it's actually easier to do that now and we'll give a comparative and a competitive advantage in an age of disruption to them versus their competitors. But let me say again, not all companies want their customer or their suppliers to have visibility into their operations. And so we've seen resistance to the value proposition of technologies like blockchain, which enhance visibility and in many cases, not always in many cases, enhance as reliable. So I would just offer those two thoughts as in response to your question. Thank you very much. That was great. Thank you. Thank you, Alex. Thank you, Chris and Sam. We have a question from our friend Fatai from OPM 52 who just direct message me. And he's asking, how do you create the algorithm for food supply chain? What data do I need to formulate a specific algorithm? It's a cool question. Yeah, that's a great question. I tell you, since I have never created an algorithm, I think I'm almost speechless and I lost four words, but I'll pass it to my colleagues. Anybody on the phone, anyone who's on this session, I should say zoom in. They can help us with that. That'd be great. Well, thanks, Sam, for that toss. I will say, I have a very good answer for you, which is I don't know how to do that, but we are working with companies who do that and know how to do that. For instance, the Food Marketing Institute is a partner for us and we've been working on a lot of things on that point, actually. And then we have a company who has been involved with us and is a food chain, a food supply chain company, as well as a producer. So I think we could at least connect you with some people who could have a more informed point of view, but it's not my book. Sorry. Thank you both, but it's a topic which definitely comes along the way. And as Chris shared, there are institutions with whom the Digital Supply Chain Institute is cooperating and will definitely hook you up, but I read them to move the question forward. Now, Vivek, can we please unmute Simon Khan? He has a question. Hi, everyone. Thank you, Marco, for arranging this. This is really excellent. Great to meet you all. Sam, this is a question for you, just around the current environment. And based on your tenure of leading IBM, which I believe at that point was the largest tech company in the world, what do you make of the current environment where tech, big tech, obviously the valuations increase significantly and significant values created in the stock market to the recent crash in big tech. Can you give us any color on what your thoughts are for the reasons behind that? Well, yeah, Simon, I think the thing is that I think we need to keep the, let's start with the broader than I get to the more specific of the valuations because that's the thing, it's crazy. And we can comment on that, but let me start with the broader issue. If you just look at who's doing well in these markets, but from a stock perspective, versus those that aren't, if you segment it out, I mean, the top eight or 10 in the S&P, companies are all up, say, 60 to 80%. I mean, they're driving the S&P, they represent about 24, 26% of the S&P. If you take the bottom eight or 10, they're down 80% or so, you know, right? So you have this bifurcation that's occurred. The lesson in the bifurcation quite honestly, then we'll talk about valuations. The lesson is that I think people now are realizing that companies that are farther along on this digital journey are doing better than ones that aren't. I mean, let's take for an example, e-commerce is a great example. Companies that were better positioned on the e-commerce, you know, take Amazon and Alibaba, those guys out of there, but they just take, you know, the average company involved in the e-commerce journey that was making these investments has it's faring better today as they turned us on and scaled it than the guys who were falling behind. Walmart's a good example, you know, Walmart's actually done quite, for traditional retailers done quite well, relative to the category killer Amazon, you know, in this environment because they made those kinds of investments. So my colleagues have all learned that they need to be farther along on the digital journeys. Now, backed evaluations fundamentally, I mean, you had a lot of momentum players in the marketplace and we'll see what happens as a result as things get back to normal.  People, as you know, I mean, the Federal Reserve and the Bank of England and the European Banking, Central Banking, Europe, et cetera have done a lot to stimulate. Money's basically free. So therefore, and there aren't a lot of options relative where to go bonds, et cetera, et cetera. So a lot of people jumped into these spaces because they saw the fangs as the winners. Well, their valuations sort of got way out of line. All these trillion dollar violations, Tesla at a 900 times earnings. I know people say it shouldn't matter, but 900 times, you know, right? At some point, you know, this stuff is going to adjust. And that's what I think you see happening here. The other thing that's happening is a macroeconomic environment that's happening. Quite honestly, all the hopes for short-term bounce back, I think, are now out of the system. I mean, there was a lot of speculation in the system about, well, there'll be a virus by the fall. Therefore, we're going to come back and then back to normal. Well, guess what? You know, things aren't going to become back to normal. Now people are saying maybe it's more like end of 2021, 2022 from a macroeconomic perspective. So I think you have all those factors to play here. But I think the lesson learned quite honestly for a lot of companies, if you're not mature in your digital journey, it's now time to accelerate. If you are mature, then obviously capitalize on it. And you see a lot of people doing that. But what's driving valuations is a huge moment in play. Now what's happening, people are shifting back to safety. What does that mean? Well, value. They're going back into more traditional value-based companies that they think, once this thing can use to modestly improve, they'll do better than they have in the past. Okay, great. Thank you very much for that. Thank you very much, Simon. We have several more questions. The first one comes from our colleague Ramesh from OPM 52 again, and he asked me to ask him for him. So he's in logistics business and they have a great company in that area. And he's asking, given we are in the midst of COVID and the challenging geopolitical scenario, do you think the supply chains will be closer to the point of consumption? This will all obviously help in making it more competitive. So what are your thoughts in that area? Yeah, I'm happy to take that. Derek, Chris, you want to take that one? So the answer is we do. We think so. And they're going to be closer to consumption using a number of different methods, right? One would be distributed in advanced manufacturing capacity and capabilities that didn't exist as prevalently a number of years ago. And the other one is around regionalizing or hedging your bets, right? So that you don't have large concentrations in one region or another so that these disruptions that we were referring to before put you at tremendous risk. So we live in a world and an economy of distributed information. What we're seeing is supply chains are going to follow that path of having a distributed footprint. And if you think about technologies like blockchain, what do they call it, distributed ledger technologies, right? So the ability to be connected but distributed, I think, is an organizing principle for supply chains based upon what we're working on with companies and what we're hearing from supply chain leaders. But Sam, any thoughts? No, I completely agree. And one of the things that Chris said that we all worked on with some of the governments was what they could do in some of these incentive packages they're creating stimulate or encourage R&D to do exactly what Chris was saying. Because fundamentally at the end of the day, well, let's start with the basic. If I am the end customer and you can be closer to me and more resilient and faster to respond to my needs, that is a plus. It's a revenue generator. It's a differentiator. So I know that pure command, like I was in a pure commodity business called PC's, and I understood when you're in a pure commodity business, it is totally scale at the end of the day. And we all globalized. We all had components coming from the same places. We all globalized. And you did other things within your supply chain to make sure you get real time to deliver within 24 hours or 48 hours. But you stacked up inventory and distribution centers. You modified things. That's how you did it. But quite honestly, if you could have used technology, which didn't really exist, but if you could have used technology, well, you could have a hub and you could quickly respond and customization. I mean, you see that in 3D printing today, not in PC's, but in components and those sorts of things, where you could quickly respond in that environment. That is a customer plus. I mean, you saw Schneider, and Chris knows we do a lot of work with Schneider and those kinds of companies and Blean Fund and other logistics companies as well. But those things are all pluses from a client revenue generation perspective. And it's a balancing act between cost and a client satisfaction or revenue generation. This is why I believe in Chris and I, and we know this in all the work we've done in the past five years, the head of supply chains and company, that role is changing dramatically today. Dramatically today. And people I think, well, I should say, I think a lot of companies that I've learned that it's more than just, I need to be the low-cost quality provider. And there's a way to differentiate yourself from a demand perspective, if you could be more responsive and relative to your competition. Yeah, the former head of Schneider Electric's supply chain is now the CEO of Schneider North America, all right? So to Sam's point, if you master, if you design, architect and transform the infrastructure that delivers value, who better than to know how to lead it and manage it and the enterprise level? And she's a very impressive executive. In fact, we'll be speaking at one of our collaboratories next week. Yeah, I mean, I'll give you the icon of this. The guy who worked for me in the IBM PC company did our supply chain to Tim Cook. I think you'd all say that he's done quite well since he left me, needless to say. But phenomenal guy, and I would argue that his knowledge and the details associated with global distribution and supply were one of the reasons why he and Steve Jobs were such a good team. Steve would be the great designer and Tim was a phenomenal operator in the executive. Thank you, Chris and Sam. Now we have Gabriel, I can unmute Kibbe back as well. So. Can you hear me guys? Yes, just click on Gabriel. All right, so one of the options I assume many companies are looking at is to integrate some of their core activities in terms of supply chain. But then when you think about it, there are two kinds of core, you know, whether it's parts, in my case, or it could be processes, right? I'm sure. Those that are more commoditized, that you have a couple of suppliers and perhaps it's not so hard for you to integrate that from a technological or even investment perspective. And then there are other core parts which are more sophisticated, more advanced and maybe you don't have the skills or the technology or the hardware to integrate that at least not so easily. So my question is, are you guys seeing some trend for companies to integrate some of these activities and parts? And if they are, what is the best way to do it? To focus on more sophisticated processes and parts that perhaps will be harder to integrate, but in the end will pay off or let's go to the, let's say, to the logo hanging fruit? Matt. Okay, let me take a cut at it. I mean, since we've tried all these things when I was working and we've developed a lot of the technology ourselves let's just say for our large complex systems or storage products versus desktop PCs and think pads for computers. But even if you go back in the early stages of the PCs we were all driving for what's called integration because the key to the integration, how you integrate? Forget the Microsoft and Intel duopoly. Well, that would be a good example who did extremely well either in the operating system or in the chip or the board, right? But the more that you could integrate those advanced technologies the more margin you could generate versus just assembling the component piece parts, right? So economically you were better off and why the duopoly, I would say, well, y'all got sued. So I said they got pretty big and maybe some argue their monopolies is because they did that extremely well, you know? They integrated functionality into the operating system so the guys who could do things around it now were part of the core operating system. The systems management of the PC or the thing that let's say mobility and same thing on the chip itself. They kept putting, because you had more geometry in the chip you could put in more space, more stuff in and in and into that particular chip. The challenge associated with that is to do those things in technology in the world I lived in requires a sophisticated skill set and a larger in the budget, you know, right? It's hard to do on a smaller set of economics or resource pools. I mean, those kinds of things. That's why you had in fragmented industries guys consolidate into the big players. I'm gonna go back to the PC example. There were lots, when Bill Gates came up with the thoughts to operating system there were tons of people who had operating systems for the PC. You know, I can do the same example in cell phones. Now there's two iOS and Android, but they were, we had 15 and IBM research, by the way. I mean, so in the early stages of all these things before they integrate and consolidate but the consolidators get the biggest scale. So my lesson learned in this is if you can, if you can integrate and you have the expertise and the capital to do so, that will always generate at least in my experience the opportunity for more economics and better margins versus the pure low end commodity guy who's always gonna have lots of competition, procurement guys are always gonna beat the crap out of you to take a nickel or a penny out and those kinds of things. So now, I mean, I get into the challenges of doing it. It's easier said than done depending upon where you're positioned. And of course, if you're observing anything from our members. Yeah, I draw a distinction Gabriel in between access to core assets and technology driven integration with core assets. And I think what we're seeing is that companies are starting to take inventory of what do they consider to be their core proprietary assets. Read that to be intangible assets as well as tangible assets. With those, I'm not outsourcing those and building skill. I'm looking at how to leverage them and multiply them but not everything is a core asset. And this is one of the things we do with the framework and the rubric of our data trading initiative which is work with companies to think about what data is core to their competitive value proposition and what data is useful but not core. And integration, technology driven integration with others seems to be acceptable and easier to do on that second category than the first category. So I would just, in response to your question I would just organize my thinking around who am I gonna give access to, to some core data but I'm not gonna necessarily allow them to integrate with it for all the vagaries and the uncertainties that are evident in today's global economy. Thank you very much. Next please, Imad, Imad, please. First, thank you for this opportunity. I heard that you were saying that we could do away with demand plans when we structure supply chains. Usually demand plan is the beginning of building the supply chain. And so I was wondering whether you could elaborate how we could do away and why we have challenges of getting access to our customers' dashboards and then stock movements. So I was wondering if I'm finding this quite challenging. So please, could you elaborate on this? Yeah, I'd be happy to and I should be more precise. What I really mean is do away with the demand forecast, right? And any forecast by definition is a guess. Demand planning is necessary for sure. We'll always be a part of a management competency and needs to be. The question is how real time is that demand plan versus the time horizon of a demand forecast and the uncertainties of the forecast. So you're absolutely right. It's very challenging. But here's what we know. Every company says their demand forecast is almost always inaccurate or useless. Yet they still do it. They go through this management exercise to do it every time. And they come to us and say, it's just not worth it. The sales guys say this, I'm the supply chain people. We plan this way. It just seems to be a hamster real experience. A lot of movement, a lot of exercise and not getting anywhere. So what we're trying to do is work with companies who are interested in having capacity to be more customer present, i.e. in line with the front side flip and understanding the new customer and the real time connectivity with a new customer and to do away with that demand forecast and allow the demand plan to be more accurate and more acute in its real time nature. We don't have the answer yet, but we are working on it. And we think given the technological capabilities that companies can deploy, it will arrive. It will arrive sometime soon, but not everybody will be able to do it to Sam's point. You're gonna have to make a decision that your business model and your business imperative warrants you and making a run at this. Thank you very much. Thank you very much, Chris. Next is Jay. Jay, please. Thanks, Marco. Hi, Sam. Hi, Chris. Thank you so much for your time. And Sam have always admired you even during my IBM days and even afterwards as well. So my question is around blockchain technology. My question is what are the areas in supply chain that you see the primary adoption of blockchain technology? And given the changes that we are facing under COVID and obviously the possible changes that will be coming as part of the recovery, how do you see the companies are willing to spend that much of money given the evolving nature of blockchain technology and even in future? What do you see how the companies are ready to adopt the technology or spend money for all the work that needs to be done? Jay, first of all, thank you for your compliment. Now, pass to the Chris. He's been involved with his journey from he called it the hype cycle, but it's been a journey and we've done a lot of use cases and things. So I'll let him take the lead on the answer. But again, thank you for your kind words. At my age, I need all the kind words I can get. Thanks, Sam. So Jay, let me separate out blockchain for payment systems and blockchain for operational execution, okay? And let's talk about operational execution. We've done at the Digital Supply Chain Institute probably four or five blockchain proof of value projects with companies who are trying to ascertain is blockchain useful for me and my supply chain objective in this area? And some have been very successful and some have been useless, basically. Where blockchain in our experience has been highly useful is, as I said earlier, it's a part of a solution. It is not the solution in a supply chain initiative in itself, but it does allow, assuming you have willing partners that have real-time visibility and information immutability so that you can determine things like integrity of components, reliability of delivery times and the amount of safety stock that is being held by one of your suppliers and is it too much and they're just covering their bets? We have, there are a lot of you, so traceability, visibility into components, we've seen it in agriculture, we've seen it in manufacturing, especially in areas around sustainability, manufacturing of sustainability areas, such as recyclable products. And it's really quite fascinating. It can be a real advantage, but it does take willing partners. So therefore, in answer, I wanna answer to your question from our experiences, if I'm a company and I wanna have greater visibility into my tier one, tier two and tier three suppliers for a product, I can do that using blockchain as long as I can make sure that those tier three, tier two and tier one suppliers are on board with my request, demand, mandate, whatever you wanna call it. I said before, blockchain does give you visibility, but not everybody wants visibility. Not everybody sees it in their interest for you to have visibility into actually how I am fulfilling my terms and conditions. But it can be a powerful, both cost factor, cost saving factor, as well as a speed accelerator and compliance accelerator. Let me put it this way. It's really useful in a world where you have to be accountable for your behavior. Thank you very much, Chris. We are coming now close to the end of the hour. So what I would ask you kindly, both Sam and Chris, is just to give a closing comment to the group of international entrepreneurs and people who are leading businesses in this crisis period as your final thought and then we'll take it from there. Well, Chris, I'll start then I'll pass with the Chris. I quite honestly, I know it's everybody, we all get caught up in the moment and therefore it's very difficult to see this thing improving or changing. However, I make the argument that this creates tremendous opportunities, especially for fast moving entrepreneurs and smaller companies that could respond quickly to this.  I mean, take what we're doing today on Zoom relative to people and how they work or say an education using similar technologies for education.  Even in the public school system, people are realizing that it can't go back to the way it was. I mean, the benefits to the old systems are great benefits to the technology, but it's going to evolve and it'll be a hybrid model. You see it in healthcare. I mean, you talk about healthcare, there are companies that are providing services to the home. Now the payers, Medicare and Medicaid in the United States are actually paying for those services. I mean, who wants to sit in a doctor's office where it's always late and see the guy for 10 minutes? If you can, on your schedule, get the same quality of services or close to the quality of service unless you have a serious critical issue. Do you really need to do that? All those things and those companies again are absolutely accelerating. You see it along the way. So my point is there's all these opportunities there's gonna be opportunities in the supply chain to transform your supply chains. And as you are participants in that space, you are gonna also see those opportunities to go ahead and do that. Now the key to that is you obviously need the capital structure and the resources. So if you can, and well, if you have a friendly banker, I mean, as you know, money's cheap and there's so much money flying around in the BC community these days, it's crazy. I mean, I happen to be involved with a lot of the stuff Jim Barr and Brian Meyer partner. So there's capital everywhere these days, but the point of it being is that if you have access to that flexibility, now is the time quite honestly, I think to invest in these obvious trends. And I would just make the point of view that the hybrid model always wins over time. And I like to use the example when a software leader gave a famous speech because of technology, they would never be a branch bank. Because of the ATM, there'd never be a branch bank. Well, guess what? There are lots of branch banks. They still do different things. We were gonna get rid of paper because of office automation, and guess what? We've automated a lot of offices and we still have a lot of papers. So it's always the hybrid model that wins over time. So look for opportunities to see where this digitalization is actually creating value through the pandemic. And I believe you'll see a lot of that through the hybrid model becomes sustainable over time. So it's like, you know, from an entrepreneurial perspective which decided that I'm no longer running a large industrial company with, you know, 400,000 people scrambling every day trying to get them back to work. I mean, this is a great time to be in those kinds of businesses. Chris? Yeah, I would just close by saying, don't focus on proof of concept activities and projects. Focus on proof of management value projects. It extends from what Sam was saying. At the Digital Supply Chain Institute and CGE generally speaking, we're really focused on management, applied management learning and knowledge sharing. And what we find in supply chain, especially is too much focus on do the toys work, right? Do the technology toys, can we prove the concept? The answer more often than not is yes, the toys work. Okay, so what? If they can't be deployed to create management value for your business, then it's really a fool's errand. And so what we have been dedicated to doing is working with companies to look at proof of management value of a project. And along the lines of what Sam was saying, using the realities and the vectors of digitalization, but being able to take the supply chain and make it a huge driver of competitive value and differentiation. So let me, I'll just end with that as my closing thoughts, but thank you very much for your time and for being willing to listen to us and ask us the great questions that you did, Marco. Thank you very much, Chris. Thank you very much, Chris. Once again, I think it has been a great session. To all of you who are here, we'll revert back and share the recording and the inputs. And on the other side, we will be as well glad to share one big thing which Digital Supply Chain Institute is working on. That's our new white paper on resilience of supply chain, especially in the arena of pandemic, because as rightly Chris said, there is a supply chain as a backbone of, all of the businesses is a thing we should focus on and try to revert. So from that aspect, the Institute would be very glad to help everybody and share the work we are doing. So thank you all for participating. Once again, thank you, Sam and Chris, for a great session and a big thank to Digital Supply Chain colleagues who have been running this call smoothly with us. So thank you all and we move forward. Bye-bye. Thank you. Thank you guys, bye-bye.


Welcome to NMSU. I am Deanna Dugas, the Director for Instruction and Research Support here in ICT and the NMSU Lead for the Cyber Infrastructure Team. My name is Nicholas Van Wolf. I'm a Systems Administrator here at New Mexico State University. I work with Deanna on the high performance computer. And we are here to support the computational needs of the upscore program, ranging from the undergrad, grads, postdoc, all the way up to the faculty member researchers. We are currently inside the Computer Center Building, and we are also where the data center, the brains of the institution lies. Inside that data center is also the HPC. As of today, Discovery has 25 compute nodes and 11 GPU nodes, with a total of slightly more than a thousand cores. Project related improvements specifically for the high performance computer include four GPU nodes and the addition of two, three terabyte of piece high memory nodes. In addition, there is one petabyte of storage capability. The HPC is composed of three racks of hardware. The first rack on the far left has our original cluster compute nodes. This was the original hardware we got from 2015 through 2018, where the cluster was first put together and became a thing here at MSU. And then in the middle rack, we have our, I believe it's six, upscore purchase nodes. These are the nodes at the bottom. These allow for accelerated machine learning, graphics processing, modeling. A machine learning task that may take months for using the CPU can be done in a matter of days on GPU. A lot of students use this for research for their PhD or their masters or for classes. Hi, my name is Crickley Rezman Jr. I'm going from a master's degree in computer science engineering in Mexico Tech. I first became involved with this project in my undergrad. And with June, I'm researching the application of using machine learning, specifically a deep forest classifier to detect outliers in smart grid data. Machine learning classifiers take a lot of RAM in general, but mine specifically take even more than that. So I couldn't actually conduct this research without the high-performance computing resources. And then in the far right rack, we have our high-speed storage cluster. Epscore bought the 220 variant, and then we added on a third storage with the CC Star Grant. The most recent grant that we've gotten is actually the CC Star Hardware Grant, and the Epscore Grant collaboration has been incredibly important and incredibly successful for receiving the CC Star Grant and amplifying its effects. The CC Star allows and encourages classrooms, both undergrad and graduate across the state, to incorporate using the HPC inside of their classroom experience. NEC was vital in improving online resources and accessibility. And one of my favorite things is open on demand, which is a website access to the system. So that means that you don't have to know Linux, you don't have to know the command line in order to be able to access the cluster and do your analysis. And there's no way we would have been able to hire NEC without Epscore funds. Project related improvements at NMSU also include having a new webpage, increasing and improving the training modules. And for the first time ever, we now have a self-serve version of the training modules available to researchers outside of NMSU. After the Epscore Grant ends, the resources will be returned back to the NMSU general pool. What that means is that anybody without having to worry about fancy things like checkpointing their scripts will be able to use those resources.


The particular focus on sexual violence is really triggered by the absolutely appalling and brutal nature of this type of violation. I mean, one just has to first think about what it means for a victim of sexual abuse to deal with the consequences, both physical but also psychological of that type of abuse. It's something that is very often underreported, underestimated in terms of armed conflict, and therefore there's a real sense of a need to mobilize and think very differently about this issue in situations of armed conflict. Fundamentally, in dealing with sexual violence, we need a paradigm shift. Previously, what one would say is our teams are there, they're in contact with the population.  We need the opposite. We need to assume that sexual violence and abuse is going to be widespread and we need to develop ways of engaging with the population that brings the violations to the fore and helps us address the needs more effectively. It is essential to understand also that sexual violence, of course, affects first and foremost the victims of the act themselves, but it has multiple effects, including at community level, because it is associated with all sorts of taboos, shame, ostracization of victims by the communities themselves, and it is often used as an act deliberately of war to destabilize, dehumanize, and in fact disrupt entire communities. Historically, we have to be very clear that the ICRC had not done enough about this issue. And it's only in the last decade or so that we have started to come to terms with what this means in terms of violations for the people affected, but also what it means to try and address this more meaningfully. We are now deeply committed to reinforcing our activities in this regard and in this everything from the medical response we give to victims, the psychological and psychosocial support that we can provide in different ways, the economic support in terms of reintegration, but also the prevention activities in order to ensure that countries adopt national legislation that are, of course, supportive of the efforts and in favor of victims of sexual violence. One often hears comments about the fact that sexual violence appears to be inevitable in armed conflict. That's something we cannot accept as ICRC. Most of all, the international humanitarian law prohibits such acts and it's our responsibility to take those messages to the armed groups to insist on that fact, but also with governments to seek to mobilize and to prevent these issues from happening. And for that, awareness raising is crucial.


So one of the things I want to ask you now is, what are all of these operations in in-form? Now, if we thought about it, a push and popping and all of these things, what's interesting is each one of them is actually being ran through a constant speed. Now, this depends on your implementation, but if you follow sort of some of the guidelines of a stack, you can make something like push and pop and all of these, only a one. And that's going to be through the magic of variables. There's nothing in the world that says I can't have a variable in place. Let's actually sort of look at just a generic list for a second. Let's say I had 80, 90, 250. Well, actually let's start with just an empty list. I think that might be a better way. So one of the things that we do is if we created this stack sort of class, is we could assign it a few different variables. So I assigned it a size of zero. All right, well, if we think about that, since I happen to have a size variable, then that size operation, all I have to do is return this. And we already remember that a return statement, return size is just o of one, because it only takes one operation. So what happens if, say for our sake, I then came in with a push of one, well, 10. All right, well, this is where things can be a little interesting, because how big is this array, this list that I've created? We don't know right now. And so you're saying, oh, I might have to double this and copy over the array. Now, you see, one of the kind of tricks that we can do is we could create another variable, just like we did here with size. What if I also created something called capacity? And I just gave it some arbitrary value, 10,000. It could be, you know, more or less, doesn't matter. But I gave it 10,000. Well, what that means is I now have 10,000 prearranged slots inside of my array that's being used in this case to handle my stack. So all of a sudden, when I say something like push 10, well, the first thing I do is I look up what size. Well, size happens to be an O in one operation. Let me, there we go. So that's only going to take one. And we put that 10 in, because I've now accessed that point in memory. And then I need to increase size. Size plus plus. Once again, this is a mathematical operation. It's O in of one. And so just like we did here with size, push can stay O of one. All right, well, pop. If we think about using those same two kind of concepts there, pop is going to give me back that 10. It's going to remove that from the list. So, first thing I need to know is what size. Again, I need to know sort of where I am. Size, well, size happens to be that. I also need to do a mathematical equation of that minus one, but that's still one. And then I need to make size one less. As you can imagine, if making it one more is one, size is one. So just like before, pop is one. So we've already started to tackle a few of these. You can imagine that top, I'm going to keep it in the same color. Top is everything but getting rid of size and deleting out the element. So top, we can already just knock out as being one as well. And then finally we're left with that last operation. Is empty. Well, luckily a comparison, say for example, a compare is sun. For our sake, is size equal equal zero. Comparison's no different than a mathematical equation. I take one element, I look at another element, and I do something to those elements. Again, not terribly outlandish. It's a primitive operation, and so we would classify that as one. And so, just like I was saying, every single one of the operations of a stack are then stored as one. Now, before I go, if I happened to need to increase my capacity, that, well, change colors, if I had to increase that capacity, maybe I wanted to double it. That is in that case, O of N, I would have to go in, copy all the elements, to a new list, and iterate through that. And so it would be dependent on that. So that one, yeah, okay. But for the most part, we could just not design that.  But as you can see, pretty much all the others. Oh, that is not what I wanted. All the others, O of one.


Hi and welcome to the session. Let's work out the following question. The question says evaluate limit x approaching to 0 square root 1 plus x minus square root 1 minus x divided by sine x. So let's start with the solution to this question. Now this can be written as limit x approaching to 0 square root 1 plus x minus square root 1 minus x multiplied by square root 1 plus x plus square root 1 minus x divided by sine x into square root 1 plus x plus square root 1 minus x. Now what we have done here is we have rationalized the limit. Now this is equal to limit x approaching to 0. Now this can be written as 1 plus x minus 1 minus x divided by sine x into square root 1 plus x plus square root 1 minus x. Now here we have applied the formula a minus b into a plus b is equal to a square minus b square wherein a is square root 1 plus x and b is square root 1 minus x. Now this can be further written as limit x approaching to 0 into 2x divided by sine x multiplied by 1 upon square root 1 plus x plus square root 1 minus x. Now we know that limit x approaching to 0 x divided by sine x is equal to 1. So we have 2 into 1 into 1 divided by square root of 1 plus 0 plus square root 1 minus 0 and this we get by putting x to be equal to 0. So this is equal to 2 into 1 into 1 upon 2 and that is equal to 1. So our answer to this question is 1. I hope that you understood this illusion and enjoyed the session. Have a good day.