Live from Las Vegas, Nevada. Extracting the signal from the noise. It's theCUBE covering IBM Edge 2015, brought to you by IBM. Welcome back to Edge 2015. This is Dave Vellante. Jamie Gamakas here with Tim Cluberance and Jamie's the CEO and president and Tim is the solutions architect at Evolving Solutions out of Minneapolis. Gentlemen, welcome to theCUBE. It's good to see you. Thank you very much. So, Jamie, let's start with you. President CEO, tell us about Evolving Solutions. You know what's our 20th year in business? We're celebrating a little bit of an anniversary here. Congratulations. Thank you very, very much. It's awesome, 20 years. Absolutely, the partnership with IBM has certainly evolved over the 20 years. We've got about 70 employees and roughly $100 million in annual revenue. The bulk of that is with IBM. There's been a lot of shift, a lot of change, as I said, in the partnership over the 20 years for the positive. Tim, what's your role at Evolving? Yeah, I'm a solution architect and my role is to help customers. We try to focus a little bit more on bridging that gap for customers between the sales side and the technical side. So, I focus on building relationships with customers and we spend a lot of time doing that at Evolving. So, let's roll back 20 years. Wow, the world was a different place, wasn't it? You know what I mean? It was a mainframe centric was shifting into a client server, no internet really to speak of. A little bit, certainly no Facebook, no social, no mobile, no ways. You're right. Who could have predicted this? And even the pace of the change right now is happening so dramatically.  The first 10 years were, we were still selling IBM products. Still, there's some, the predecessors to the today's power technology, the R6000 was a big part of our portfolio even at that point in time. But the pace of change that is occurring today in the market and it's driven by the customers, of course, is dramatic. And we have to be able to adapt to that change. I mean, almost quarterly, we are really listening to what the clients are telling us and helping them on their journey. That's where the Tims come in, really to add value to the clients in the infrastructure level of their environment. So, Jimmy, you've decided to sort of invest in a role of a solutions architect. Jimmy, I want to dig in a little bit more. So, how do you spend your time with clients? It varies. Our architect team does do implementations and stuff as needed, but we spend a lot of time just understanding what the business requirements are for our customers. We spend a lot of time training and helping them understand what new technologies are available from IBM and our partners. And then we stay engaged throughout the whole process to make sure that they continue to, you know, continue to find a solution that's right for their business needs. Are there industries where you specialize? You know, we gravitate, we're really a cross industry partner. We gravitate towards those industries that are consuming technology, one of them being healthcare. And it's not that we have deep skills in any specific facet of healthcare other than the fact that just through repetition we have an awareness, a deep awareness of healthcare environments. So we're able to replicate that capacity needs, capacity planning, really understanding some of the key core applications that are driving healthcare growth. And if you think about the Minneapolis-St. Paul area, which is our home base and we have a significant presence, there are some large healthcare institutions in that geography. So it's been a natural evolution. So let's take healthcare. It's, I guess people say it's recession proof. So during the downturn, you know, it maybe didn't get as affected, you know, the healthcare industry and the government were sort of still spending. Yet you had the Affordable Care Act come into play and that's caused dislocations. Historically, docs haven't been big consumers of technology, although that's changing certainly with mobile. So what are you hearing from that constituency? How are they dealing with meaningful use and what does it mean ultimately for the architecture? So Jimmy, maybe you could start about, what are those patterns that you're seeing in healthcare? So the consumption of technology is accelerating in that industry in all facets of it. I mean, you look at some of the companies up there and how they're branching out into other segments of healthcare through acquisitions. It really is all about data, the accumulation of data and what they can do to act on that data. Ironically, the technology side of healthcare never saw a significant downturn. And the reason was, is because the automation was still needed throughout the, you know, the 2000s. I mean, they were on a growth curve to accumulate data, understand data through analytics, what they can do with it. And also the healthcare companies, at least in the Twin Cities, and I suspect throughout North America, I mean, they're on an acquisition, an aggressive acquisition pace. So meaningful use and other things, those are all elements of what was driving the growth, but it really is all facets of the business that are increasing and utilizing technology much different today than they were in the past. And the Tim's, our solutions architect role, it is such a significant part of our participation and investment in that market. I think Tim probably spends, you know, 50%, maybe 75% of his time with some of our healthcare clients solving problems. You know, Tim, if I roll back, I think about theCUBE started in 2010. So it's sort of five years in now. I mean, if you think about the cloud discussion back then, it's very bifurcated. You had the Amazons of the World saying, public cloud, working with developers, and you had the rest of the enterprise world saying, private cloud. And now it's evolved. They talked about hybrid cloud, but it really, you know, wasn't real. And it seems like it is now. So as an architect, what are you seeing in cloud? How are you connecting the public cloud, the hybrid cloud and the private cloud dots? So there's a, well, depending on the industry, of course, I've been talking about healthcare, there's a sort of a battle between protecting data as well and making data available on a cloud level and for analytics type applications, et cetera. So plus the other thing that we deal with a lot is just the rapid growth of the data. And there's some tough, there's some tough decisions to be made about how you get the data to the cloud, how we process it. So my role, essentially, is to help bridge some of those and to make sure that customers are able to grow that infrastructure at the pace that their data is increasing. So what do you see as best practice? Cause people are concerned about putting their data in the cloud, although some people aren't. People don't, you can't move big chunks of data. There's too much data, right? It brings you to a grinding halt. So how do you solve that problem? You obviously have to think through, like I said before, the business requirements, you know, the data governance, edicts, et cetera, but how do you solve that? That's a tough question to answer cause it's a little bit different for every customer depending on what type of data that is and how sensitive the data is. So I'm not sure I could say there's one solution that's right for every customer. And I suppose that's part of the benefit from evolving and having a team of architects that provides that bridge so we can help find the right solution for each customer.  The CEO's all over it, the CFO wants to shift CapEx to OpEx, wants this outsource, you know, a lot of it except this little piece over here which is our family jewels. So help me, right? Do you hear that a lot? Or is it more the other way of people saying, you know, we're going to use the cloud for some test and dev, maybe some analytics, you know, we'll throw some stuff in the cloud but help us protect our core assets. Yeah, we have customers that are sort of dabbling, I suppose is a good way to put it. Yeah, so that's the sort of more common use case, is that right, you guys? No, I think they would like to invest more in it but they're kind of cautiously entering in some of that space and other customers are going much more full into it but I think that's a little more rare at the moment. But yeah. And how do you look at that, Jamie? Is the chief executive of a company that has for 20 years been pretty basically on-premises infrastructure in place? How do you look at the cloud? How do you turn it into an opportunity? So we've made an investment in the cloud, we have a dedicated group that is doing nothing but working cloud opportunities and I mean, it's our responsibility and our goal to help our clients on that journey to the cloud and that doesn't mean just taking them and moving apps to the cloud. What it really is, is helping them understand what's the benefit of going to the cloud? What are the security risks of going to the cloud? You alluded to the fact that there are the family jewels, there are applications that are going to remain on-premise. There are applications that are much more logically placed in the cloud and then there are some that are going to be shared. There are the compute may be in the cloud, this is what we're seeing or hearing more and more frequently where the compute may be in the cloud but the storage, the data may actually still reside in a private enterprise. So really there isn't a one-size-fits-all but the more sensitive the data, so compare healthcare to manufacturing, the more likely that that data is going to be owned and privately held in an on-premise environment. And your relationship with IBM extends to cloud offerings? It does, absolutely. It means software and Bluemix and all of the above. Do you private label that or? We don't as of this point in time. But you could, that's part of the business model. Absolutely, so Watson, Bluemix, Softlayer, I mean they are all part of our strategic growth initiative and the key is our infrastructure business is growing, grew at 65, 70% last year and which is for a 20-year-old company is phenomenal. Now it's interesting because you have kind of a bifurcation of the business partner market and it really is for the first time there is a strong recognition of those companies that are investing, have invested over time in deep resources and then you have the other side of that bifurcated why those partners that have chosen not to invest are most likely not going to be able to survive. Box sellers, absolutely. For years we've loved the box sellers, it's great moving boxes, moving boxes but if you don't transform, you know, you're going to be driftwood. You are. You tsunami. Correct. That's interesting, that's an interesting call you have to make about private labeling or not, you got the great IBM brand, you got a hundred million dollar company building your own brand so be interesting to watch how that proceeds. So good luck with that. We got to go, we got to leave it there but thanks for coming on theCUBE and congratulations for all your success, amazing story and we appreciate your time. Sounds good, thank you very much, we appreciate your time. You're welcome, keep it right there everybody, we'll be back to wrap. This is Dave Vellante, this is theCUBE, we'll be back right after this word.


And now for your U.S. Army Europe spotlight. General David Perkins, commander of the U.S. Army Training and Doctrine Command, shares his vision of the Army's new operating concept and the role of U.S. Army Europe. What the Army operating concept does, in sort of a long-term macro view, is describe the environment that we're going to operate in, determine the Army's role in that environment, and then determine the capabilities that the Army has to have to fulfill its role in the environment that we describe. And so the environment of the future is, it's going to be a very complex environment. It's going to be a multinational environment. Change is very quickly. You have to have what we call multiple options and multiple domains with multiple partners. So when you take a look at United States Army Europe, it's almost custom-made to do that. I mean, it's right here in the middle of a very complex part of the world. Every day they work with multiple partners. They're working in multiple domains. They're really surrounded by a bubble of multinational capability. And so user is indispensable to this. For more on the Army in Europe, go to er.army.mil.


As far as the spiritual politics is concerned, there is not just in Tamil Nadu but elsewhere as well, we are seeing a lot of symbolism, the temple hopping that happens. The big competition, everybody is rushing into temple after temple. We have one of the youngest electorates that will be going to vote in this current cycle of elections. If they are not that interested or keen in spiritual politics, how does all of this fit in with that? And how do you see the temple hopping element in political campaigns? See, whether they go to a temple or a mosque or to a iftar party or to a church or to Christmas parties, all these things have been there, all right? But generally it is the majority community who was left behind. Now they are catching up. Going to temple also has become an in-thing. Otherwise going to Christmas parties and going to iftar parties were in-thing because in Christmas party there was wine, in iftar party there was biryani. In temple, only water. So it was not a cool thing. But now that water has become sacred, in the last probably five, six years this evolution has happened. Now everybody wants to be seen in a temple. This got nothing, even the iftar has nothing to do with Islam or Christmas party has nothing to do with Christianity. Temple going by politicians like this has nothing to do with the Hindu way of life. They are doing every trick possible to get maximum number of votes. So don't call it spiritual politics, it's just politics. But instead of saying what I will do, you're trying to show who I am. My intention is that is what we need to change.  What will you do is the only question. I think every citizen in this country should raise this question, okay, I will give you my vote. What will you do in the next five years?  What will you do, what are you capable of doing? That's all that matters. We have to shift. The media has a big responsibility in this direction. Not who, what is the big question. Every citizen should raise this, media houses should raise this. Everybody who's concerned about this nation should raise this. What will you do?  Right now by going to a temple, they're trying to show who they are. They're not saying what we will do.


The study investigated the use of three different plasticizers, tris, 2-chloroethyl, phosphate, tris, 1-chloro, 2-propyl, phosphate and tris for methylphenol, phosphate, in order to improve the fire safety properties of epoxy polymers. It was found that the optimal concentration of these plasticizers was 40 parts per million, resulting in improved fire safety properties such as increased char yield and reduced volatile thermolysis products. This modification also resulted in improved fire protection properties with the epoxy composites achieving a UL94V0-V1 rating. Additionally, the thermoprotective properties of the char were studied, along with its relationship to the combustibility of the composite. Finally, the behavior of the modified composite during high-rate pyrolysis was analyzed. This article was authored by Amirbek Bekchev, Anton Mostovoy, Andrey Sherbakov, and others. We are article.tv, links in the description below.


Every religion has its principles. Every religion has fundamental ideas which define which that religion stands for. And especially when we talk about religion, religion is just not simply what somebody thinks or what somebody feels, what somebody aspires to, what somebody sets as his goal in life. Religion is a unique type of philosophy of life. Everybody has a philosophy of life. The sea is the atheist whoever it is. So religion cannot simply mean a way of life that you have chosen. Otherwise the word religion would become a meaningless word. So religion would have to have something unique, something specific. What makes religion unique and specific? First of all, you can't have religion unless you have a concept of God. Without God there is no religion. That's what sets religion apart from every other philosophy of life. In everything else you can postulate these or that premise, these or that theory, whatever it may be. But to make it unique, to make it a special category, it must have something unique and that is in terms of religion, God. Now just because you have a concept of God does still not mean that you have religion. You may believe in God, you may even believe in God as God being the creator of the world. You may believe all the things that are said about God, omnipotent, omniscient, almighty, everything. That still does not mean that you have a religion. In fact, in theology and philosophy we have two concepts, one of which is called deism and the other one which is called theism. Both words mean exactly the same thing, except one comes from the Latin deos and the other one comes from the Greek teos. Both words meaning God. So basically both words mean Godism. What's the difference between deism and theism? In deism a person believes in God, of course God exists. After all, it's a basic fundamental logical premise that no one can deny that ex nihilo nihil fit. Nothing can come out of nothing. From nothing you cannot establish anything. If there is a world, if things exist it must have had a source of origin. There are certain things which theoretically could be eternal but we see in day-to-day life that the scientists would also do. How long do they say how old is the human race, the human species, what have you? I think the longest known was about 20 billion years. For that matter you can make it 200 billion years, makes no difference. And then I can always ask what happened before 200 billion years? If there is a certain moment in time when this begins there must have been something which set it off. And that we call the beginning. And once you have a beginning of something which is ex nihilo which came about from nowhere as such then the question arises how did it come about? Regardless whether you're a believer or an atheist it doesn't matter. Everybody has to start with some eternal substance which is the origin, the first course, the pie mover of everything else that we see in this world. That's number one. Nobody will argue this point. Second point that nobody will argue that this course, Carla's first course, Carla's pie mover must contain within itself all the potential for everything that eventually evolves or comes about. Because otherwise you get right back to square one. Where did it come from? How did it come about? The effect can never be greater than the course. So the course must contain all the ingredients that the effect displays later on. So therefore it's quite simple and quite logical to assume there was something that existed eternally with not out having any source of origin that brought everything into being. And then you can develop a whole theory about that and give it any name. Call it X, call it Y, or call it God. The name means nothing. The term means nothing. All you can do is you can define in order for that eternal first course to exist and to be the course of all things that came about thereafter there must be certain qualities. For one thing, it must contain all the positive qualities that we see evolving in the course of time, in the world, in all the objects, in all the creatures that we see. But that's about it. And deism argues, of course, God exists. Those of you who have studied philosophy or theology, you may be familiar with the most famous of the deists, famous philosopher of the 17th, 18th century, David Hume. He accepts, yes, of course, God exists. Yes, God created the world. But after God created the world, God is not interested anymore. He had his fun. He got it out of his system. As the Bible puts it, all is up our shameless odds. God's forsook the world. As a matter of fact, the deists will go on with a logical argument and say it's presumptuous and arrogant on your part to think that God cares one hoot about you.  I care about things which have some relationship with me. How can you say that God has a relationship to anything in the world? God by definition is infinite. God by definition is perfect. Anything existing is imperfect, is finite. Compared to God, it's nothing. If you take the number one, the smallest number, and you take a huge number that you need a computer to even figure it out, zillion to the zillion's power to the zillion's power to the zillion's power, which means practically nearly infinitely greater than the number one. There is still a connection and still a relationship between the smallest number and the biggest number. The biggest number is simply so many times bigger than the smallest number. That's all. When you talk about infinity, then the largest number, the biggest number, is no bigger in relation to infinity than the number one or the number zero. Because infinity is beyond counting. And therefore they argue if God by definition is infinite. God by definition is completely beyond that. And the world by definition is finite. The world in relation to God is nothing, zero, nada, zilch. So for us to argue that God cares about the world, that God is involved with the world is sheer nonsense. It's sheer arrogance and presumptuousness on your part. That's deism. But then why did God care the world? I haven't got a clue. God cared the world, had his fun, got it out of the system.  You put in a whole days of work and ingenuity to build your sand castle, made it very intricate and complex. And then you look at the watch. I had to go home for supper. What's going to happen to your sand castle? You know very well the next morning it won't be there. Tide and app will be washed away. Are you concerned?  It was interesting. It was a challenge. Tomorrow I'll build another one, different kind. So why should we not say the same about God? Yet we like to think no God cares about me. I'm important. Who says you're important? Nothing. That is deism. So the basic premises they accept because they're simply necessary to explain logically, philosophically, certain facts that we have to confront. This obviously has nothing whatsoever to do with religion. It's the opposite of religion. Religion is the term that would use in Greek theism. Theism says not only does God exist, not only did God create the world, but after creation, even though God doesn't have to, but God chose to create the world for his purposes and God is connected with the world, God is what we call a personal God. That's religion. But just because you believe in a personal God who is involved with his creation, who is involved with his world, still does not mean you have religion. So fine. I know God cares about the world. God cares about mankind. So therefore, well then, there must be a connection between God and you and you and God. Perhaps. What kind of a connection? I have no clue of knowing. You cannot make a connection between God and man and man and God. You cannot talk about a religious code of conduct. You cannot talk about religious principles unless and exclusively so, if and when God says so. If and when God directs us in that direction. That God says to us, this is what I expect from you. You cannot say, we have now adopted these or those religious principles. People assume that when it comes to religion and relationship with God and there are certain things in life which turn me on and they turn me on and make me feel spiritual. So I can simply devise now that system or that's this lifestyle, whatever have you. It's sufficient for me to establish a religion. It's sufficient for me to establish a lifestyle, a philosophy of life, a religious code. And you may go out and be indeed very sincere about it and devise a very intricate and very delicate and very subtle philosophy of life, the most noble and the most moral. And you may say for that God which I now believe in, which come to that conclusion, I'm going to build the most beautiful edifice in the world and bring the greatest symphony orchestra to play the hymns to inspire anybody and everybody who comes there and go about and do it. And now you think that you have a connection with God? God may very simply turn around and say to you thank you for the compliment, but frankly you're not my type. That's not what I want. That's not what I expect. That's not what turns me on. You want to know how to serve me? You want to know how to connect to me? There's only one and one way only that you can ever possibly find that out. Ask me and I'll tell you. That is the third concept that comes into the idea of principle of religion. First is idea of God. Second not just God existing but God, a personal God. And the third one is revelation. Without a concrete form of revelation you have no religion. No such thing. Even if you have a concept of God, you believe in God etc.  What is acceptable to God. All the Gators philosophers and all the Gators theologians all the wisest people on earth whatever they may come up with and it may make a lot of sense it is meaningless, it is worthless, it is zero. You can get that source of information from one place and one place only God himself. Now existence of God for that we have many philosophical arguments. All the philosophers some day one have been dealing with that problem Jewish, non-Jewish, monotheistic, polytheistic, whatever it is. And there are a number of philosophical arguments to prove that there must be this idea of first cause of prime mover. You can even go a step further and say look here this God surely must be connected with the world. You can give a philosophical argument for that as well to prove that philosophically. So these two major points and major promises you can argue and demonstrate on a purely logical philosophical level. The third item which is really the most important of all revelation for that there is no logical argument for that there is no philosophical reasoning. Revelation is history. It's something which either happened or did not happen. It does not depend on mental acrobatics. It's an event. It's an event that must have been experienced. And once we deal with experience an event that must have been seen, heard, whatever it is, then the same criteria that apply to any other historical event. Whether you talk about something of the far off past or you talk about something which is very recent. History is not something which happened two and a half or three and a half thousand or four thousand years ago. History is also what happened a split second ago. Anything which is not here and now is history. And the moment you deal with history you have a very profound perplexing problem. How do you know about any event of the past, anything that is not occurring here and now that it actually happened? In philosophy this is known as epistemology which is probably the most perplexing problem that mankind has to face. Epistemology means theory of knowledge. How do you know? How do you know anything? How and when would you know what you know? And how can you be sure that what you know is really real or not? Philosophers have been struggling with that question for thousands of years and I can give you today in writing that for the next thousands of years they will still be struggling with that. They have never come up with a satisfying answer regardless of how old the thousands of books have been written on that subject alone. And there will be thousands of more books that will be written. Each one trying to be smart and find out. It is logically impossible to come up with an answer to that. The only way that you can ever come up with an answer how does my mind work? When do I know that my mind is working properly? How and when would I know that my perceptions are correct and real? I would have to be able to step out of my mind. I have to be able to get out of my whole reality and judge my brain and judge my forms of perceptions from outside, from a kind of an objective point of view. And that of course is human impossible. The human mind is programmed, it can only work with things which work in time and space. Anything outside time, outside space I cannot even talk about it. I can discuss it, I can talk about it, I can talk about it, but it's totally meaningless. Revelation, we talk about it meaning God revealing himself, God speaking to man, God addressing man. Either this happened, God did speak to us or God did not speak to us.


Live from San Francisco, it's theCUBE. Covering IBM Think 2019, brought to you by IBM. Okay, welcome back everyone live here in Moscone North in San Francisco. It's theCUBE's exclusive coverage of IBM Think 2019. I'm John Furrier with Dave Vellante. We're breaking down all the action four days of live. Coverage of two great guests here, Elenita Elinan, executive director, quantitative research at JPMorgan Chase and John Thomas, distinguished engineer and director of the data science elite team. Great team, elite data science team at IBM and of course JPMorgan Chase, great innovator. Welcome to theCUBE. Thank you very much. Thank you, thank you guys. So I'd like to dig in, great use case here. Real customer on the cutting edge, JPMorgan Chase, known for being on the bleeding edge sometimes. But financial money, time is money, insights is money. Tell us what you do at the quantitative group. Well thank you, well first of all thank you very much for having me here, I'm quite honored. I hope you'll get something valuable out of what I say here. But at the moment I have two hats on. I am co-head of quantitative research analytics. It's a very small, SWAT, very well selected group of technologists who are also physicists and mathematicians, statisticians, high performance compute experts, machinery experts and we help the larger organization of quantitative research which is about 700 plus strong as well as some other technology organizations in the firm to use the latest, greatest technologies. And how we do this is we actually go in there, we're very hands on, we're working with the systems, we're working with the tools and we're applying it to real use cases and real business problems that we see in quantitative research and we prove out the technology and make sure that hey, we're going to save millions of dollars using this thing or we're going to be able to execute a lot on this particular business that was difficult to execute on before because we didn't have the right compute behind it. So we go in there, we try out these various technologies, we have lots of partnerships with different vendors and IBM is being obviously one of a few very major vendors that we work with and we find the ones that work, right? And then we have an influencing role as well in the organization, so we go out and tell people, hey look, this particular tool, perfect for this type of problem, right? You should try it out, we help them set it up. They can't figure out the technology, we help them out. We're kind of, like I said, we're a SWAT team, very small compared to the rest of the organization but we add a lot of value.  This is like a key thing. A lot of new things are emerging. One of the things we're seeing here in the industry, certainly at this show is it's not your yesterday's machine learning, there's certainly math involved. You got cognition and math kind of coming together, deterministic, non-deterministic elements. You guys are seeing these front edge of the problems, opportunities for you guys. How do you see that world evolving because you get the classic math, school of math machine learning and then the school of learning machines coming together. What kind of problems do you see these things, this kind of new model attacking? So we're making a very, very large investment in machine learning and data science as a whole in the organization. You probably heard in the press that we've brought in the head of machine learning from CMU, Manuela Villosa. She's now heading up the AI Research Organization, JP Morgan, and she's making herself very available to the rest of the firm. Setting strategies, trying different things out, partnering with the businesses and making sure that she understands the use case of where machine learning will be a success. We've also put a lot of investments in tooling and hiring the right kinds of people from the right kinds of universities. My organization, we're changing the focus in our recruiting efforts to bring in more data science and machine learning. But I think the most important thing is, in addition to all that investment, is that we, first and foremost, understand our own problems. We work with researchers, we work with IBM, we work with vendors and say, okay, this is the types of problems, what is the best thing to throw at it? And then we POC, we prove it out. We look for the small wins, we try to strategize, and then we come up with the recommendations for a full-out, scalable architecture. John, talk about the IBM Elite Program.  It's a service that you guys provide with your top clients, you bring in the best, and you just jump in, co-create opportunities together, solving problems. That is exactly what. How does this work? What's your relationship with GP Morgan Chase? What specific use case are you going after? What are the opportunities? Yeah, so the data science elite team was set up to really help our top clients in their AI journey. So in terms of bringing skills, tools, expertise to work collaboratively with clients like GP Morgan Chase. And it's been a great partnership working with Elinita and her team. We had some very interesting use cases related to her model risk management platform. And some interesting challenges in that space, but how do you apply machine learning and deep learning to solve those problems? So what exactly is model risk management? How does that all work? Good question. That's why we're building a very large platform around it. So model risk is one of several types of risks that we worry about and keep us awake at night. There's a long history of risk management in the banks. Of course, there's credit risk, there's market risk. These are all very well known, very well quantified risks. Model risk isn't a number. You can say this model, which is some stochastic model, it's going to cost us X million dollars today. We currently, it's somewhat new and at the moment it's more prescriptive and things like you can't do that or you can use that model in this context or you can't use it for this type of trade. And so it's very difficult to automate that type of model risk in the bank. So I'm attempting to put together a platform that captures all of the prescriptive and the conditions and the restrictions around what to do and what to use models for in the bank and making sure that we actually know this in real time or at least when the trade is being booked we have an awareness of where these models are getting somewhat abused, right? And we look out for those types of situations and we make sure that we alert the correct stakeholders and they do something about it. So in essence you're governing the application of the model and then learning as you go on in terms of... That's the second phase, so we do want to learn at the moment what's in production today. Morpheus is running in production it's running against all of the trading systems in the firm inside the investment bank and we want to make sure that as these trades are getting booked from day to day we understand which ones are risky and we flag those. There's no learning yet in that but what we've worked with John on are the potential uses of machine learning to help us manage all of those risks because it's difficult. There's a lot of data out there.  Because there's too much stupidity happening right now we're looking at emails, we're looking at data doesn't make sense. So Morpheus is an attempt to make all of that understandable and make the whole workflow... So it's financial programming in a way that's come with a high whole scale of computing a model gone astray could be very dangerous. Absolutely, and it costs real money to the firm and this is all that you said. So a model to watch the model. So policing the models, kind of watching. Yes, I met a model. And you have to isolate the contribution of the model not like you say before, are there market risk or other types of risk? So you isolate it to that narrow component. And there's a lot of work, we work with the model governance organization another several hundred person organization and that's all they do. They figure out, they review the models, they understand what the risk of the models are. Now it's a job of my team to take what they say which could be very easy to interpret or very hard and there's a little bit of NLP that I think is potentially useful there to convert what they say about the model and what the controls are on the model or just something that we can systematize and run every day and possibly even in real time. So it's really about getting it right and not letting it get out of control. But also this is where the scale comes in. So if you get the model right, you can deploy it and manage it in a way that helps the business versus if someone throws the wrong number in there or in the class, we got a model for that. Yeah, exactly. And there's two things here, right? So there's the ability to monitor our model such that we don't pay fines and we don't go out of compliance. And then there's the ability to use a model exactly to the extreme, right? I mean, where we're still within compliance and make money, right? Because we want to use these models and make our business stronger. And there's consequences too.  You guys look at the quantification of those kinds of consequences where the risk management comes in. Yeah, absolutely. And there's real money that's at stake here, right? So if the regulators decide that, oh, a model's too risky, you have to set aside a certain amount of capital, right?  If that's done incorrectly, and we end up putting a lot more capital in reserve, then we should be. And that's a bad thing. So quantifying the risk correctly and accurately is a very important part of what we do. So a lot of skill sets, obviously. I always say in the money business, you want the best nerds, right? I don't hate me for saying that. You're smart as people. What are some of the challenges that are unique to model risk management that you might not see in sort of other risk management? There are some technical challenges, right? So the volume of data that you're dealing with is very large. If you are building, so at the very simplistic level, you have classification problems that you're addressing with data that might not actually be all there. So that is one. But when you get into time series analysis for exposure or prediction and so on, these are very complex problems to handle. The training time for these models, especially deep learning models, if you're doing time series analysis, can be pretty challenging, right? Data volume, training time for models, how do you turn this around quickly? So that's how we use a combination of technologies for some of these use cases. Watson Studio running on our hardware with GPUs. So the idea here is you can cut down your model training time dramatically, and we saw that as part of the... Talk about how that works because this is something that we're seeing people move from manual to automated. Machine learning and deep learning to give you augmented assistance to get this to the market. How does it actually work? So there is a training part of this and then there is the operationalizing part of this, right? So at the training part itself, you have a challenge which is you're dealing with very large data volumes, you're dealing with training times that need to be shrunk down and having a platform that allows you to do that. So that you build models quickly, your data science folks can iterate through model creation very quickly is essential, but then once the models have been built how do you operationalize those models? How do you actually invoke the models at scale? How do you do workload management on those models? How do you make sure that a certain exposure model is not crumbling or it's not crashing some other models that are also essential to the business, right? So how do you do policies and workload management? And on top of that, we need to be very transparent, right? If the model is used to make certain decisions that have obvious impact financially on the bottom line and an auditor comes back and says, okay, you made this trade so and so, why? What was happening at the time? So we need to be able to capture and snapshot and understand what the model was doing at that particular instant in time and go back and understand the inputs that went into that model and made it operate the way it did. Can't be a black box. You can't not. Holistically, you got to look at the time series in real time when things were happening and happened. Happening and then holistically tie that together is that kind of the impact analysis? We have to make our regulators happy. That's number one and we have to make our traders happy. We as quantitative researchers, we're the ones that give them the hard math and the models and then they use it and they use their own skill sets too. What's the biggest needs that your stakeholders on the trading side want and what's the needs on the compliance side of the regulators? Traders want more, they want to move quickly. They're coming from different sides of it. Yeah, traders want to make more money and they want to make decisions quickly. They want all the tools to tell them what to do and then for them to exercise whatever they normally exercise. They want competitive advantage. They want that competitive advantage and they're also, we've got algo trades as well there. We want to have the best algo behind our trading. And the regulators side, we just want to make sure laws aren't broken. They're just auditing the whole. We use the phrase model explainability. So can you explain how the model came to a conclusion, right? Can you make sure that there is no bias in the model? How do you ensure the models are fair? And if you can detect there is a drift, what do you do to correct that? So that is very important. But do you have means of detecting sort of misuse of the model? Is that part of the governance process? That is exactly what Morpheus is doing. So we are, the unique thing about Morpheus is that we're tied in to the risk management systems in the investment bank. We're actually running the same exact code that's pricing these trades. And what that brings is the ability to really understand pretty much the full stack trace of what's going into the price of a trade. And we also have captured the restrictions and the conditions, like it's in the Python script. It's essentially Python and we can marry the two and we can do all the checks that the model governance person indicated we should be doing. And so we know, okay, if this trade is beyond, operating beyond maturity or a certain maturity or beyond a certain, you know, expiry, we'll know that and then we'll tag that in. And just to clarify, Morpheus is the platform name of the platform. Morpheus is the name of the model risk platform that I'm building up, yes. A final question for you.  What's the big complex of challenges? You know, you want to just be rubber stamping models. You want to solve big problems. What are the big problems that you guys are going after? So I have many big problems. The one that is right now facing me is the problem of metadata, data ingestion, getting disparate sources, getting disparate data from different sources. One source calls it a Delta, an IR Delta. This other source calls it something else. We've got a strategic data warehouse that's supposed to take all of these exposures and make sense out of it. I'm in the middle because they're there, probably have a 10 year roadmap, who knows. And I have a one month roadmap. I have something that was due last week and I need to come up with these regulatory reports today. So what I end up doing is a mix of a tactical strategic data ingestion and I have to make sense of the data that I'm getting. So I need tools out there that will help support that type of a data ingestion problem that will also lead the way towards the more strategic one where we're better integrated with this. John, talk about how you solve the problems. What are some of the things that you guys don't give the plug for IBM real quick because I know you guys got the studio. Explain how you guys are helping and working with JP Morgan Chase. Yeah, so I touched upon this briefly earlier, which is from the model training perspective, Watson Studio running on power hardware is very powerful in terms of cutting down training time, right? Now, but you got to go beyond model building to how do you operationalize these models? How do I deploy these models at scale? How do I define workload management policies for these models? And can I can do their backbone? So that is part of this. And model explainability we touched upon that. To eliminate this problem of how do I ingest data from different sources without having to manually oversee all of that? We need to apply auto classification at the time of ingestion. Can I capture metadata around the model and reconcile data from different data sources as the data is being brought in? And can I apply ML to solve that problem? So there are multiple applications of ML along this workflow. Talk about real quick comment before we break. I want to get this in. Machine learning has been around for a while now with compute and scale. It really is a renaissance in AI. It's great things are happening. But it's what feeds machine learning is data. The cleaner the data, the better the AI, the better the machine learning. So data cleanliness now has to be more real-time. It's less of a cleaning group, right? It used to be clean the data, bring it in, and wrangle it. Now you've got to be much more agile. Use speed of compute to make sure that your qualifying data before it comes in to these machine learnings. How do you guys see that rolling out? Is that impacting you now? Are you thinking about it? And how should people think about data quality as an input to machine learning? Well, I think the whole problem of setting up an application properly for data science and machine learning is really making sure that from the beginning you're designing and you're thinking about all of these problems. It's data quality. If it's the speed of ingestion, speed of publication, all of that stuff, you need to think about from the beginning, set yourself up to have the right element in it. It may not all be built out. And that's been a big strategy I've had with Morphosis. I've had a very small team working on it. But we think ahead and we put elements of the right components in place. So data quality is just one of those things. And we're always trying to find the right tool sets that will enable us to do that better and faster, quicker. And one of the things I'd like to do is to upscale and uplift the scale sets in my team so that we are building the right things in the system from the beginning. Well, that's math too, right? I mean, you talk about classification. Yeah. Getting that right up front. Yeah. Mathematics is... And we'll continue to partner with Elenita and her team on this. And this helps us shape the direction in which our data science offerings go because we need to address complex enterprise challenges, right? I think you guys are really onto something really big. Love the Elite program. But I think having this small team thinking about the model, thinking about the business model, the team model before you build the technology build out is super important. That seems to be the new model versus the old days. Build some great technology and then we'll put a team around it.  It's easier to build out and acquire technology than to get it right. Yes. That seems to be the trend here. Congratulations. Thank you. Thanks for coming on. We are Keeps Conversations. Here we're live in San Francisco for IBM Think. I'm John Furrier, Dave Vellante. Stay with us for more day two coverage. Four days will be here in the hallway and lobby of Moscone North. Stay with us.


Hello everyone. In this lecture, I will discuss the nuclear fusion process from the point of view of two aspects. One is the extension of periodic table, that means essentially synthesis of heavy elements. So, I will not give too much details, but we will explain the concepts behind what are the limitations in extension of periodic table, but that also involves a nuclear fusion process. And second is what are the research or what are the work going on producing electricity from nuclear fusion process. Okay. So, first let us discuss the extension of periodic table. You know that the elements up to 92 were available till 1930s. And after the discovery of nuclear fission, the attempts were made to synthesize heavy elements in actinium, plutonium by N gamma reaction followed by beta minus decay. And with the accelerators produced producing heavy ions charged particles, then by fusion reaction also heavy elements were being synthesized. And by this time elements up to 118 have been discovered. Majority of them, in fact, beyond under element 100, most of the elements have been synthesized by nuclear fusion, fusion of heavy projectiles with the heavy targets. And so, but there is a limitation. There are some inherent limitations in extending the periodic table that I tried to explain in this particular presentation. So, the limitation due to fission. As I discussed in the previous module, that facility parameter, if you have a facility parameter 0.6, that will correspond to a mass number of around 100 or so. You can see from here z square upon 50.13 into 8, you can calculate. So, these nuclei are as most, no, they are stable towards fission. They will not undergo fission. Whereas, if you see x equal to 0.8, so this comes to around californium or anstinium, fermium, gently close to 100. And these nuclei will have the fission barrier of the order of even around close to 1 MeV or so. So, the fission, so this is the spontaneous fission happening. They are having very short half-lives because they have a high fission probability. But if the facility parameter is 1, then there is no fission barrier. You can see here, there is no fission barrier for this nucleus. And so, you cannot produce this nuclei. The moment they are formed, they will undergo fission. For them, the fission barrier is 0. So, that is the limitation because of these instability towards fission of this heavy nuclei, it is very difficult to extend the periodic table. Another aspect, so the fission barrier decreases with the increased atomic number. And you can see how the facility parameter is changing for different nuclei. You can calculate from here.  So, let us take 100 square upon 2. So, it will become 10,000. So, that means 10,000 upon 10,000, that is equal to 1. So, a nucleus of mass number 200 will have one facility. So, it is not survived. But if you make it 250, so it will become 125,000. If you put 12,500, then it will be close to 0.8. A facility will be close to 0.8. And so, it will have some finite fission barrier and therefore, it can survive fission. Another aspect is the angular momentum. Angular momentum is adding to disruption of the nucleus like coulombic repulsion. The coulombic repulsion is trying to separate the protons away and that is the negative, that is the factor which accelerates fission. Another thing is angular momentum. So, in a heavy ion reaction, when you bring in a heavy ion, it will bring in angular momentum. And the angular momentum will try to destabilize the nucleus. So, because of that, there is a one more term apart from surface energy. So, if you recall the expression, if you recall the this one for surface energy, coulomb energy, the angular momentum term also will be destabilizing the nucleus. So, the net result of surface energy, centrifugal energy and the coulomb energy will dictate the fission barrier. And so, because of these, for the same nucleus, if you have higher angular momentum, fission barrier will decrease. What I am showing here is you increase the angular momentum from 0 to 20, 40, 60, 80 h cross for this nucleus 153 terbium. The fission barrier for zero spin was around, this is 35 or so, 35 MeV and it is going down too close to let us say 5 MeV at angular momentum of 70 or so. So, you can see it is sharply declining fission barrier with increasing angular momentum. So, in heavy ion reactions, invariably you will have higher angular momentum. And so, there will be more unstable towards fission. What I am shown here is the profile, locus of the number angular momentum and mass number for nuclei having fission barrier 0. The angular momentum for which fission barrier become 0, you can see here for a mass number around 150, it can accommodate about 90 h cross of angular momentum. But for a nucleus of mass 300, it cannot accommodate even 5 h cross. So, that means what the fission barrier for the angular momentum for which fission barrier become 0, it is increasing and then it becoming decreasing. So, when you go to heavier elements close to 300, they will have nearly zero fission barrier. So, that is why you will find that their survival become very difficult. And so, it is that puts the limit on exchanging the priority. The third is the competition with particle evaporation limits the formation of heavy nuclear. So, fission competes with the particle evaporation and therefore, that puts a limitation on the survival of the heavy nuclear. So, there are different ways to reduce the particle evaporation by using what we call as the cold fusion. That means you produce a compound nucleus which have very low exquisite energy. There are different ways, but we will not go into details of those processes. I just wanted to give you a feel that why what are the limitations in extending the reality. Another thing is to entrance to fusion. There are other limitations that when two nuclei come together, then there are other factors which hinder fusion of nuclei. So, if you recall the previous lecture I have shown in the componentless mechanism that suppose a nucleus is coming close to another nucleus Z1, Z2. So, this is the R versus the potential and this is nuclear potential is like this. The Coulomb potential is like this and the sum total of that will be so, this is the fusion barrier. Once you bring in angular momentum, then angular momentum also is a repulsive barrier and so, that will reduce the pockets. So, the special barrier will decrease and a time will come, but higher angular momentum the this pocket there is a pocket being formed in fusion a pocket will vanish. This is what I have tried to show here that for argon plus 197 gold, the nuclear potential and the Coulomb potential will give rise to this pocket. This is the pocket in the fusion barrier. For heavier projectile like xenon plus gold target is same, but the projectile is now increased you will see here that the Coulomb barrier is here, nuclear potential is here and the fusion profile has become very shallow. That means this pocket starts vanishing and once this pocket starts vanishing the compound nucleus formation becomes difficult. So, the two nuclei cannot come close enough to fuse and form a mononuclease called compound nucleus. So, you can see here 54 plus 79. If you want to go to heavier elements, you have to have heavier projectiles trying to fuse with the so, there are the nucleus community is trying to study what are the factors that will limit the formation of heavier elements. So, there is a effective facility parameter they call just squared by A effective they say that if it is less than 48.  If it is less than 48 then you may be having a pocket if it is more than 48 then you may not have the pocket. So, you can see here for argon plus gold it is 31, but xenon plus gold it is 50. So, that is how this is one of the limitations in fusion of projectile in target to achieve synthesis of heavier elements. So, the nuclear chemistry fraternity has been engaged in synthesizing heavier elements that there are predictions based on cell model calculations that nuclei having atomic number 114 and neutron 184 are expected to have heavy along half lives that is what is called super heavy elements. The super heavy elements around this region have may have a long half life. So, people have tried to in fact separate them from the natural resources from the earth crust wherever there is a large deposits of uranium, thorium people have tried to separate some elements resembling their lighter homologs, but so far there has been no success in the process people have been trying to synthesize them by fusion reactions. So, as I was mentioning the hot fusion to take lighter projectile and heavier target nuclei or cold fusion to take heavier projectile and not so heavier targets. So, by cold fusion reaction you will see you try to produce a compound nucleus which is not very hot in terms of excretion energy and so by these processes people have tried to synthesize heavy elements and because of that the half lives are very long very short, but still attempts are going on to synthesize heavier elements. So, you can see here the periodic table has been extended to mass 118 and these experiments take a very very long time. In fact, even to synthesize elements these elements rutherfordium, dubonium, cyborgium which the chemistry had been also studied element 104, 5 and 6. A lot of chemistry had been studied even there the production rates are one atom per hour or so as you go to higher and higher like this highest elements production rate may be one atom per month or so. You can see here the kind of experiments people are doing and then they have to get an unambiguous signature of that it is that Z and A. So, the atomic number the mass number of that particular isotope has to be established to claim it that they have discovered a particular the new element. So, what they do actually they when this heavy element isotope is produced they will undergo alpha decay and the alpha decay energies are monitored for the lighter part lower daughter products the alpha decay energies are known and so that is how they correlate that this daughter is growing from this parent. So, this is the atomic number and mass number of this particular heavy isotope. So, element up to 118 so the super heavy element as we are calling N equal to 114 Z equal to 114 N equal to 184 is close to that region the people have achieved, but the half-lives are not long enough half-lives are very short they are in millisecond microsecond range. So, still people may be searching for the super heavy elements with long half-life, but the experiments in accelerators to synthesize elements beyond 118 that is for 119 they are not going going on they are planned in in Japan and USA. Now, in fact, the different countries actually are pulling their resources to plan such mega experiment to synthesize heavy elements. So, to conclude the part of nuclear fusion in producing heavy elements I would like to say that there are experiments going on using nuclear fusion reactions wherein you try to understand what are the factors that limit the extension of periodic table. People have tried to produce heavy nuclei by hot fusion reaction or cold fusion reaction. This cold fusion is not the type of cold fusion which were in between it came in the news that fusion of hydrogen isotopes to give neutron. This is the fusion of heavy nuclei but with to give lower oxygen energy to compound nucleus. So, you want to survive the fission. So, you produce compound nucleus with low oxygen energy so that it can survive fission. Now, I will come to the next part how to produce power from nuclear fusion and what is the status as of now. So, the fusion of two light nuclei to form a heavy nucleus to release large amount of energy is similar to fission process and fission process has been already realized to produce electricity because we can control the reactor very easily but in the case of nuclear fusion process that still is yet to become a reality. So, let us discuss this nuclear fusion the fusion of lighter isotopes. So, here we have the different types of nuclear fusion reaction. So, fusion of deuterium plus deuterium giving rise to helium-3 and neutron a q value is 3.2 MeV fusion of deuterium and tritium to give rise to helium plus neutron q value is 17.6 MeV and fusion of lithium with hydrogen give rise to helium-3 and 4 q value is 4. Now, as you know that these are all charged particles. So, if you want to fuse the charged particles you need to cross the coulomb barrier and so, there are different channels which are people are trying to explore for achieving a nuclear fusion process which you can sustain. I will discuss this soon what are the problems in which sustaining a fusion reaction. So, this is a simple deuterium plus deuterium giving rise to helium-3 plus neutron 3.2 like that you will have deuterium plus tritium. So, let us see what are the problems in achieving a fusion reaction. So, as I was mentioning these reactions different fusion reactions of lighter isotopes of hydrogen the one which is having deuterium plus tritium having the lowest threshold that means the coulomb barrier. So, the coulomb barrier you know already z1 z2 e square upon r1 plus r2. So, for deuterium plus tritium the coulomb barrier in terms of kilo electron volt or so that is having about 10 kV. So, the coulomb barrier for this will be 10 kV and if you translate this 10 kV into temperature it becomes 10 power 8 degree Kelvin. So, if you want to it is like a threshold reaction threshold energy. So, if you want to induce fusion of deuterium and tritium you require to achieve a temperature of 10 power 8 Kelvin. Now, you can imagine unlike in the case of neutron induced fission you did not have this problem because thermonutron can induce fission, but for charged particles you have you require to have very high temperatures and then if you have to achieve high temperature how to what kind of container you will have to hold reactants at such a high temperature. So, the storage materials storage vessels how to achieve at this temperature material matter will be in the form of a plasma. So, you have to contain the plasma in a container. So, all these are the limitations for achieving a fusion reaction. So, now there have been attempts going on for last many many years several decades have been spent and there are mainly two types of approach people have followed one is the inertial confinement. So, what is that you are trying to confine that deuterium tritium plasma the deuterium tritium you they have to fuse together and you require a temperature of 10 power 8 degree Kelvin. So, how do you contain this plasma? So, the one approach is called inertial confinement by inertial confinement you mean that by virtue of their mass you can confine the solid fuel in a very small volume and but you have to also have a high temperature. So, you achieve high temperature by bombarding them with the high power laser beams CO2 or NDR laser beams and you take a solidified fuel. So, when the laser beams are bombard on the solidified fuel it will ablate the surface atoms outside and this ablating atoms now will give a recoil to the core and they will density will increase. So, you contain the core of the solidified fuel by ablating the surface atoms using a laser beam. So, the evaporating atoms on the surface bring together the interior atoms by the recoil of the ablating atoms and that will lead to rise in the density of the core and in the process by when the density is rising temperatures can go beyond that what 8 Kelvin, but then it may not sustain for long time. So, there is in fact a Lawson's criterion which I will discuss very shortly. So, for a very short time you can achieve very high temperature, but during that time the fusion can take place. So, in the process of inertial confinement the reacting particles like bacterium and tritium are held together by virtue of their mass and that is why it is called as the inertial confinement. So, this inertial confinement by using the laser beams to ablate the outer surface layer to increase the density of the core is experiments are going on, but it has not been that successful as the next experiment of magnetic confinement. In the magnetic confinement again you take the bacterium tritium fuel in the shape of a donut like a tire and that you have so you have it the tire in the central portion of this tire the plasma can rotate move and you how do you confine how do you know avoid the plasma touching the container walls using the electric and magnetic fields that is in fact that is called as the tokamak system where the electric field will accelerate the particles it will increase the category of the reacting particles and the magnetic field will keep the fuel away from the surface. So, you have to adjust the electric field and the magnetic field to have the plasma and when they are using they should not touch the container walls. So, the magnetic confinement strategy has been working and there have been several attempts to generate the tokamak type of reactor worldwide. One of the conditions to achieve to sustain a fusion reactor is called the Lawson Schuykeren. The Lawson Schuykeren essentially emphasizes how to achieve a plasma density of a beyond certain number for a reasonably long confinement time. So, we have to confine the plasma for a reasonable length of time. So, this criterion is rho tau rho is the plasma density and tau is the confinement time. So, if you have to have higher energy output than the energy input energy input is being given to heat the plasma to a temperature 10 power 8 degree Kelvin. If the product of plasma density and confinement time is more than 10 power 14 second per cc for the deuterium addition. For deuterium deuterium we 10 power 16 second per cc. So, for this is the one which you know which have lower threshold. So, the lowest temperatures required for this fusion reaction. So, this is the confinement. So, if you have a high plasma you will find high plasma density then slightly lower temperatures or lower confinement time also will do. So, overall attempt is to increase the confinement time and the plasma density. So, these are the two efforts are being made to have Lawson's criterion if you can have a high plasma density and high confinement time nothing like that. So, let me see what are the what is the current status in the form of for producing energy electricity from fusion reactor. Since this is a very costly affair to have to build a reactor which we still do not know when it will work. So, there has been an international effort called ITER international thermo nuclear experimental reactor which is a you know all most of the majority of the countries which I have interested in this fusion energy have come together and they have proposed a fusion reactor at Kaderash, France, south of France. So, this is the world's largest experimental prokomak fusion reactor which is being proposed. It is funded by European Union largely and India, China, Russia, Japan, South Korea and USA contributing 9 percent each. So, every country you know whoever has a stake in the fusion power they want to contribute this and this construction of this fusion reactor began in 2007, this is 2022. So, already 15 years have passed and the first plasma from this fusion reactor is expected to be produced by 2025. In fact, India has contributed a great deal in cash and kind. In fact, the cryo state for this reactor was built in our country and many universities in the country are also participating. We have in Institute of Plasma Research at Khandabar, Nandinagar they are leading agency in the country to contribute in the plasma research in the fusion reactor. So, this fusion reactor based on deuterium fusion fusion is expected to start operation by 2035 and this reactor is expected to have a power of 500 megawatt which will be sustained up to 1000 seconds. So, you can see here that even this is a very meager you know target was what do you do for after 1000 seconds.  So, this kind of mega projects if you can sustain if the such a high power of fusion power for 1000 second it will open up gates for the sustaining that actually materializing realizing the fusion electricity from the fusion in the times to come. So, this is the one area where there is a lot of scope for research for students in the country. There are many universities are also contributing in this fusion research and the department of economic energy is also contributing in a big way both in terms of producing the materials the different systems and that of course in the government of India is contributing by way of gas. So, what I wanted to share with you today that why the nuclear fission has been already utilized for producing electricity in our nuclear reactors. The nuclear fusion is yet to be realized for producing city, but maybe you young students will see one day that we are producing electricity from the fusion power and so the challenge it is a challenge for all the students to participate in such big mega projects those who are in the field of nuclear chemistry or nuclear physics or you may in fact many you know engineering students, mechanical engineers all types of disciplines are involved in producing this kind of a fascinating. So, I will stop here and the next I will take in the next lecture the production of radioisotopes in different types of nuclear reactions. Thank you very much.


So I'm going to try and capture with kept capture the net cap packets So I'll start TCP dump start the capture and then on computer 14 start a server Listen on port one two three four five and Then start my client connected to computer 14 Port one two three four five Send my messages and now we'll see that in the capture So just you send some packets between computer one and 14 stop my capture and now open that in wire shark and have a look And remember it's useful to Disable name resolution, then you won't see the nicknames. You'll see the raw addresses And I see there are a lot of packets. Let's try and find how do I filter on packets? There are different ways to filter port numbers can be filtered IP addresses protocols So it's the the slides show some different filters that you can use All right, so you can filter by protocol if you know the IP address TCP has its port number TCP dot port equals One two three four five because I know I listened on port one two three four five so that's one way and I find these packets and I'll just turn off color coding here the time let's hide that for now even the Source and destination So computer one is me computer 14 was the other computer running the net cat server So the first message is sent from me to the server and then back What are these messages? Well, we see the first three Me to the server back and then a third one from me to the server These are TCP messages and the way that TCP works is before we send any data. We set up a connection We synchronize the two endpoints and The way to synchronize two endpoints in TCP is to send some synchronized packets So that TCP segments, but there's a flag set called sin to synchronize So the way that it normally works is that I send something to the server saying I want to synchronize with you the first sin The server sends back an act saying okay, and the server also sends a synchronized message to me And it combines them together into one packet That's why we have a sin and an act together and the third one is this me sending the server acknowledging its sin message Roughly, we can try and draw that if we try and draw that on the screen if I can get at the work There's me and computer 14 This is our message sequence diagram and the first message is the sin message Sent from computer one to computer 14 So this is what we're going to draw is called the message sequence diagram try to capture the messages And then there's the sin act that comes back and then the third act This is TCP setting up the connection So the way the TCP works is before we send data we set up a connection and the typical way is sin sin act They're trying to synchronize sequence numbers and synchronize the two entities so they're ready for data transfer From my computer one to 14 you should write the IP address here to be more precise Okay, so I've just written the computer number then the next message we see I Send something to the server computer 14. What do I send in TCP? It's called a push message and Push usually means it contains data. It's saying here's some data Give it push it to the application at the other side as soon as possible And if we look inside that one message the fourth one here, we actually see the data Down the bottom we see it contains the word that I typed in the words. I typed in so hello Steve So this is the data message coming from Client to server and then the next one is an act There's no data in this one. It's just an act saying thanks for the data So we could draw that So the fourth message is the data and then there's an act that comes back So I don't write PSH comma act because what it really means to me It's data and the data was whatever the message I typed in and there's some more messages after that I could draw them if I like depends how many you sent but that's that's the important parts of what we see in that Message transfer we see a connection set up and then the data transfer and that keeps going If you're lucky you may see a connection close at the end may see some thin segments to finish the connection But you may not see them So this is what we call a message sequence diagram And I'd like you to draw them for each time we ask you to capture packets So for each of the three tasks today Don't draw things that you don't understand That is don't write names here, which are exactly like on wireshark Interpret to what it really means or simplify it So I don't write PSH comma act. I just write data because I know it's really the data Okay, and the next one's the act. I could add up more details But that's enough in the context of this question You could add sequence numbers if you like but that's sufficient to see the types of messages Then the other type of diagram is to draw maybe one or two of the packets in detail Let's say focus on the data packet Let's look zoom in on that one data packet and try and draw that this one data packet Is this fourth one in my capture if I double click It shows me that details of that one data packet and the way to interpret the wireshark information note these rows here That tells us the basic structure of the packet or a frame is a more precise name. The entire frame is 78 bytes long The frame is made up of an Ethernet header an IP header a TCP header and 12 bytes of data So if I want to draw this frame I'll try and illustrate that there's an Ethernet header an IP header TCP and data Let's try and draw that and quite simply just illustrate it as a packet diagram And you've seen in lectures how we draw this Some form of rectangle to illustrate that one packet And what do we have split it into four chunks doesn't have to be to scale There's an Ethernet header I can get this to Spell correctly Ethernet IP What was next TCP and then the data and all of this was our one large frame total size How big was the Ethernet header? So that's my frame That's how I say to draw the packet diagram identify the headers And the other useful thing is the size of each It's easy to see the size when you click them on one of the rows and I'll go back to the main window in Wireshark when I click on The Ethernet row if you look down the bottom in the status bar it shows you the size of that ethernet header 14 bytes IP right down the bottom 20 bytes TCP 32 bytes data 12 So we write the sizes on the packet as well. So the total frame size 78 bytes When we select it or we see here captured 78 bytes That's the entire frame But it's split into an Ethernet header IP TCP data That's how we can visualize it. The entire frame is 78 bytes the individual headers or the chunks Listed there. So that's the basic way to draw a packet diagram Sometimes it's useful to add a few details. What's inside the headers? in Wireshark What's inside the headers is shown when we again zoom in on a particular packet We can expand and see the Ethernet header contains a destination address source and the type IP packet the IP header Contains a number of different fields including source and destination TCP sequence numbers act numbers flags port numbers and the data Well, the data is just the data that I sent So sometimes it's useful on the packet diagram to draw the values of important fields Maybe the addresses are useful For example, I can draw the the source and destination IP addresses Now you don't need to draw all fields on the packet and sometimes you can get away with drawing none But some sometimes if there's a key value of importance highlighter on your diagram Addresses are usually important port numbers Sometimes there's a particular field in a question that that will arise So whenever you capture Whenever we give you tasks of capturing draw these two types of diagrams You don't need to draw every packet Maybe the main ones like I chose the data packet the act packets not very interesting the data's of interest And in the frame exchange the message sequence diagram You don't have to draw every single packet captured again. Just select the main ones or a sample of the main ones So that's your task for today The first so you draw a message sequence diagram a packet diagram Better draw ones there You should have captured with NC you should quickly try even if you don't capture try to use NC and UDP mode All right, try to use NC and UDP mode. You don't need to capture it Then we'll have a break and then at 240 you can continue on with tasks two and three So just get keep going with them task two is to use ping capture Look in wire shark answer some questions task three access a website while capturing look in wire shark answer some questions With the aim of learning about how to use wire shark and TCP dump today