Good afternoon. It is my honor to share the second Young Leader session in the 10 years history of the World Policy Conference. The purpose of this session, as defined by Thierry, is that technology in the hands of millennials offer a fresh perspective on new opportunities, on new ways of addressing today's challenges, and also in which order of priority. Thus influencing the multiple policy agendas that we have been discussing during these last three days. To shed this new light, we have with us successful entrepreneurs four from the private sector and one from the French public sector, as this has to work hand in hand. They will introduce themselves and share their thoughts based on what they heard during the last three days and on their experience. And we will of course have time for a Q&A. So I thank you for attending this session and it is now my great pleasure to invite Natalie to kick off the session. Thank you very much. It's such a pleasure to get to be here. My name is Natalie Cartwright and I run a startup out of Canada that's called FIN. What we do is we build virtual financial assistance for banks. So they take our product and they put their label on it and they push it out to their customers. And it's been really exciting to get to be here and to hear some growing consensus around the area that I'm really most interested in, which is tech governance and AI governance, since we use a lot of AI in our product. And at the risk of being indulgent, I'd like to talk a little bit about my company and how we grew it, because I think it's a really good example of what's happening with companies like mine all around the world and has some really big policy implications as well. So let me tell you about how we actually started the company. I actually used to work for UN organizations and an organization called the Global Fund. So my background is in a very different world than technology. And I realized that if technology or if international development was gonna improve, it needed a stronger business perspective. So I went to do an MBA and afterwards one of my friends who was a management consultant in the program called me and said, Natalie, do you wanna do something in FinTech? So while we were still on the phone, I Googled FinTech, which I can now with confidence, tell you stands for financial technology. And I said to him, sure. If you wanna move to Canada, I'll create a business with you. So when we're talking about the next generation and doing technology and doing jobs that didn't formerly exist, I am that next generation. I don't really, when I first started at least, did not know nearly enough about technology. And most of the people that I hire on my team have not been formally trained in technology necessarily. We've got PhDs in data science and other pieces, but lots of masters in geography, other types of pieces. So we've heard that this has really big policy implications for education, and I just wanted to share with you three of the things that I see as really fundamental to incorporating in our education as we go forward. So the first thing that we look for is we look for people who have an ability to code or to understand coding language. And it doesn't necessarily mean that everyone needs to be a developer in writing code, but it is the basis of our technology language and should be something that every child understands. The second thing that I look for in my team is people who know how to learn. And it's not just that they know how to learn, but they have to be able to learn independently and teach themselves. So whether that's going to the internet or asking a friend or reading a book, I don't really care how they learn, but they're always trying to improve themselves and take on new challenges. And the third thing that's really important for people on my team with their skillset is that they have to be failure resistant. When we're building technology, we don't build projects from zero to 100. We build them in these very small incremental steps. But often when you reach one step, you don't solve it the first time. And often it's not the second time. And often it's not the third time. It could be the 50th or the 100th time that you approach a problem before you actually solve it. But that means that I need people on my team to be able to fail repeatedly, pick themselves back up and continue to keep going. So for people who are involved in educational policy, those are the three things that I think we should be looking at going forward. It was three years ago that we started our company. Today we're about 40 people. We're hiring five to 10 people every month. We've been able to attract quite a few banks, which has been fantastic. We work across four continents. We work with one of the 10 largest banks in the world. And I just wanna give you an idea of the scale at which my company, which is really just 40 people, relatively small, is working at. So just through one of our customers, which is our largest customer, we'll be ruled out to 20 million people over the next three to four years. And I don't say that because it's exceptional. I actually say that because I think it's entirely unexceptional. We know that there's some big players who are creating AI. Everyone talks about them. But I think that companies like mine, of which there are thousands around the world, are also rolling things out at scale. And the implication from a policy perspective is that we don't have the luxury of time. We have to figure out how we move quickly because there's companies who are building and scaling and really don't have a lot of frameworks to work within. And I think one of the solutions for that problem can be borrowing one of the playbooks from the startup world, which is something called the minimum viable product. And it's a basic principle that Eric Rice wrote a book on called The Lean Startup. Basically, it's just you always start and you build the least amount that you can as quick as you can for the least amount of money that you can and you constantly iterate on that. And that's one of the reasons that we can move so quickly when we're building technology. So while I don't know entirely what it would look like, I challenge you to think about what a minimum viable policy approach would look like to try and keep pace with this very, very quickly evolving world. And the last point that I wanna make today is one about how we actually went about building our company. So we started using a cloud service from Amazon. Formally, you probably would have had to invest 20 to $30,000 to get a server up and running just to get started. We went and bought a third party product called api.ai that we could put our data into to try and test the data models. We've since rebuilt that. I think in total, we spent a few hundred dollars to get a very small product up, but that was enough to get us some interest from banks and to realize that we should continue going. And the implication from that, for me, from a policy perspective is the most exciting because these types of companies should exist everywhere in the world. Technology and cost is not the barrier for entry anymore. And when Patrick and I were speaking about this earlier today, the question now is how do we create and facilitate ecosystems around the world so that companies like mine and like all the other panelists can exist everywhere and really be the drivers of economies. So I'm extremely excited about tech. I love getting to be in it. I think AI is gonna bring really, really great changes and our challenge is how do we build governance structures, policies and systems that are nimble, innovative and equitable. Thank you very much. Thank you, Natalie. So anticipating, but to summarize, so your points are about education with a clear path, trial and test. So don't try to plan too far away. And technology is not the barrier, but build the ecosystem and try to summarize it. So thank you very much. We stay in technology. We move away from AI to go more in what is called big data. Edouard, over to you. What can we learn from big data? Hi, everyone. My name is Edouard Naté. I'm the CEO of a young company called Fox Intelligence. We're located in Paris. We're 25 now. And yes, we're two years old. What we do is a bit special. We know every revenues of any online companies. So you take Amazon, you take Uber, you take Deliveroo, you take any company online. We know the revenues for now in France. The way we do it is we gather, we anonymize billions in real time of eReceipts. EReceipt is the email you get in your inbox, in your email box when you purchase something online. I purchase these shoes. I get an email saying Edouard purchased these shoes at this time for this price, et cetera, et cetera. And the good thing is we've got a million people in France who gave us access to their email accounts, allowing us to know exactly the revenues of any companies selling something online in France. And we're going to be doing this in Europe in the coming weeks, month, and years. Just if you have the question, how can this guy convince a million people to give us access to their email accounts? Well, we offer them services, we offer them money by doing smart things. So one example, train delays. Every time you have a train that is late, we know it because based on your email account, based on your tickets that are in your mailbox, we know that this train was late and we can do the claim for you. So this is one of the ways we use to convince people to give us access to their anonymized receipts to their email accounts. Well, so that's what we do. But this is not what I want to talk to you about. I want to talk to you about something that came up quite quickly in the building of this company about data. And the point is this one, it's impossible to solve any of the key issues of our times, climate change, poverty, women's conditions, access to medication, to education. If we don't have access to publicly available, reliable and transparent data, it's impossible. You can't run the diagnostic, if you don't have the data, you can't design your solution, if you don't have the data, you can't test your decisions and the impact of your measures if you don't have data. Now the good thing, this is something that we both, everyone here lives every day, is we have the tools to do it. We have computing power, we have the science, it's called data science, we have the people and skills, it's called data scientists and that works super well. The bad thing is we're human beings and human beings have two flows. The first one is we love being slaves and we love or we love enslaving people. That's the first one. The second flow is we have a major issue with accountability. We have a major issue with being held accountable for the things we do. So I'm gonna skip the first part because you all know what I wanna talk about, which is the rise of the freedom ideology for the last three centuries, which is now even defining who we are, the free world. And I wanna focus on the second part, which is our issue with accountability. I'm just gonna make a small philosophical apartheid on this, which is if you take morality, the first attempt to codify morality, which is religion, it's full of this human tendency of always putting your blame on something else. It's called scapegoating. You put the blame on a goat and you kick it away.  And one of the consequences of that is people who do not want to be held accountable usually don't create data points and don't share data points that would show what they do. So if I'm a company and I don't want to say that I've got only men in my board of director, I'm not gonna put it in my annual report. I'm not gonna do it. And now the cool thing and what I'm really hoping for is that transparency becomes the default mode. So it means that leaders, individuals, institutions, they naturally start feeling themselves accountable for each of the things they do. And this is something that I'm gonna take a very small example that works super well in our company. In our company, each table, so each team has a table and each table has waste as a trash bin. And we measure how much trash, how much waste has been produced by each table. And we publish the number. And the fact that we publish this number, first we realize that some table would generate twice as much waste at another table and it's the same human beings working, eating, drinking, et cetera. But when you start putting these numbers, then people start to realize maybe I should change my behavior. And so introducing data points in everyday life is something that drives change. So my final point on it is what I feel as a responsibility as a small, young leader of my company, but that applies way more to big governments and big company leaders is that, first of all, you should always put your transparency mode as the default mode. And the second thing is everywhere it's possible, everywhere it's not against privacy and personal information, you should always try to, I mean, we should always try to find a way to be accountable for what we do because that's the only way towards change. Thank you. So thank you. I think the example of Edouard highlights really critical topics we see with the rise of the internet and the exponential development of big data. What you, if I summarize briefly, you say we had to trade off freedom versus privacy. As a consequence, then we had to trade off privacy versus transparency because this, the loss of privacy has generated the transparency for whatever it means, it will require some definition. And now you're telling us this transparency generates accountability. And of course, for all of us, the question is accountability for what consequences? Because it's okay, I'm accountable. I don't manage my bin properly or too much waste, but what are the consequences and what does it mean? And I think we had the example in the first day around the new transport mode and the connected cars and the question around the responsibility. And I think that's something your example highlighted. We'll go back now to artificial intelligence, but in a complete different environment, which is healthcare. So, Alan, over to you. Well, thank you so much, Patrick. My name is Alan, the CEO and the co-founder of a company called Hippogriff from Sweden and we were active in healthcare. I'm humbled to be part of this panel and would like to thank Capgemini and World Policy Conference for inviting me. I would like to start by giving you a little bit of background and basically why I'm here today. Every day when we wake up, we have a choice. We can focus on what's right with our lives or we can focus on what's wrong with our lives. I believe focusing on what's right with our lives rather than focusing on what's wrong with our lives is the best way to fix what's wrong with our lives. Moreover, focusing on what's right with the world is the best way to fix what's wrong with the world. For me, everything started from a tragedy a few years ago. My grandmother got a heart attack at my cousin's birthday and suddenly died. Imagine how tragic it was. She didn't have any signs or symptoms and died just in a moment. So the birthday party which everyone was happy and celebrating an anniversary of a person's existence turned to a funeral. Looking at the statistic, heart disease is number one killer all around the world. In fact, every two seconds, a person dies from heart disease. But the problem is not the disease itself. It's the late detection of the disease that kills most of the people.  Like my grandmother. So after the sudden death of my grandmother, it changed my world view and created a big question mark. I was thinking why there was no way to detect her disease in an earlier phase and what if we could save her life? So that was the ignition to start developing our innovation which is called heart strings. A life-saving tool that uses artificial intelligence to detect heart disease before it gets late. So what happens today when you have a symptom? You go to doctors, they examine you, take a blood test, ECG and in many cases, send you for angiography operation which is very expensive and invasive. But in many cases, angiography is not necessary. This unnecessary operation translates to 100 billion euros in additional cost each year. And that's enough to cover the whole budget of Sweden this year. On the other hand, there are a lot of data generated before angiography. So we believe that we could utilize the existing data and turn it to a valuable insight. If you just think about it, a huge amount of data is generated every single day in any sector. Imagine how the world would look like if we employ machine intelligence in the right way and through appropriate policies. This can lead to industrial transformation and significant improvements in all sectors because everything is connected. Imagine how impactful it can be for us as humans. So in our case, the question was how should we do that? How can we address one of the greatest challenges of healthcare with what already exists and with what we have? And that's the point. We are living in a period of time that we have access to advanced technologies and high quality infrastructure that can empower us to tackle the challenges which we are facing. So we developed our unique artificial intelligence algorithm that uses the existing parameters like electrocardiogram and demographic data to detect heart disease at a significantly earlier stage, even if the patient doesn't have any symptoms. Well, I'm proud that a project which was started a few years ago just because of curiosity have been validated in two different clinical trials and tested with more than 46,000 patients successfully. And this resulted in receiving several national and international awards and recognitions. And now today, thanks to my interdisciplinary team of cardiologists, doctors, and computer scientists, we are offering a technology which is two times more accurate, 10 times faster, and 49 times cheaper than the existing methods which can serve millions of people each year. And exactly this gives us confidence that we are not only the next innovative company but a venture, a venture with social mission. We believe that we can transform the quality of healthcare for every individual. Our vision is to save at least one million lives each year. You know, when you lose someone that you love, you realize the value of every single moment you could be with them. We're building a movement to save those valuable moments. From the stage of World Policy Conference, I would like to invite all of you to join us to save millions of lives. Thank you. So, Alan, thank you. Thank you also for the personal exposure. What I draw from your presentation is that you say, this is a people-centric technology development. So it starts from the people, not necessarily from the business opportunity. And I would say that we see it more and more. It goes with this evolution, the customization. We heard it previously on this drive. Having said that, from a policy standpoint, it creates problems because the way you will go through your approval is not necessarily the way these processes have been defined for. And as you said, it's multidisciplinary. And as such, it requires a more systemic approach. Notably, again, we are back to the question of data governance, which is a fundamental question. So thank you for this. We stay in the healthcare industry now. And we move to Arthur, who has an ambition that you will share with us. Thank you.  Thank you, Patrick. So first of all, allow me to join my fellow panelists in thanking Thierry for giving us the opportunity to express ourselves at the World Policy Conference and thanking Patrick for facilitating these discussions. So I have a very ambitious title. I'm aware of the future of healthcare and how to get there in eight minutes. So please bear with me. I think what most fascinating thing about healthcare is that it impacts all of us from the day we were born to our last day. It is a crucial part of the interaction with our loved ones, yet its basic principles have not changed for centuries. If you look at this picture from the Middle Ages, you see in the middle a knowledgeable doctor, possibly assisted by a nurse on the left, which tries to solve one narrow issue of a helpless patient on the right. Of course, the tools and remedies have changed, but the basic principles and the way we approach healthcare today are still the same. What I'm trying to convey to you today is that we're on the cusp of a healthcare revolution and that there is truly a time, which is now where healthcare is going to profoundly changed, especially in the way it is delivered. And I'm going to give you four main items for which I think healthcare is going to change. Healthcare is going to be highly personalized. Healthcare is going to be unified. It's going to be preventive and it's going to be embedded. Of course, this is an optimistic scenario and it carries many risks, but I'm going to go into those topics and provide you with examples of startups and companies that did not exist five or 10 years ago and that are trying to go in this direction. Thinking about personalization. Today, drugs and treatments are rarely differentiated, yet we know every single human being is unique. There's the development of autologous therapies, which is a very fancy word to say from the self, and you have companies like Novartis and Kite Pharma that just received FDA approval for therapies that are reprogramming your own immune system to find cancer cells. So we are taking your own immune system and using its power so that you can treat yourself, the tumors in your body. Of course, many of you have heard about genomics and companies like 23andMe are trying to democratize genomics. The way they work is they send you a little tube, you spit in it and a week late, you send it to the post and a week later, they give you a full detailed genomic analysis of your ancestry and what healthcare condition you may have and this is only for a couple of hundred dollars. So this is extremely impressive. And looking at the quantified self and all the wearables you have, like the Fitbits and all the things that measure anything from your head rate to the number of steps you take, this is truly happening now and allowing each one of us to start measuring what we do in order to better act on it. Now looking at how healthcare is unified. Today healthcare is still very fragmented. You have cardiologists, you have orthopedic surgeons, you have people trying to treat each and every single organ. Yet we know many diseases such as diabetes or cancer are whole and you need a truly holistic approach. But this goes beyond physical and mental. The physical and it goes beyond the body. It also goes to physical and mental.  Examples of which include Mindspace, which is a meditation app that from your iPhone allows you to meditate five to 10 minutes a day which has been scientifically proven to improve both your mental, obviously, but also your physical health. Interoperability is gonna be crucial and companies like Flatiron are developing electronic health records for cancer patients that allow to track all the individual healthcare steps that a cancer patient is undergoing, all the interaction it has with different doctors in order to provide the next doctor a truly unified vision of the patient's state. And of course there is interdisciplinarity and we talked a lot about it already on this panel. If you think, for instance, about this amazing lens that Google and Novartis developed which has a blood glucose monitor on the cusp of the lens. So just by wearing this contact lens you get your blood sugar measured in real time through your tear drops. And this is something that has been done by sharing the expertise of tech people, designers and doctors. Thinking about how healthcare is gonna be more preventive. In order to have truly prevention which is an oft-quotten word but not still very effective at the moment, you need three elements. You need awareness. So you need to know what diseases exist and what you can do about it. And social media are increasingly playing a huge role in addressing millions of people about serious health issues. And you can look, for example, a couple of weeks ago there was an Instagram campaign about the risks and danger of mental health and it could reach many people, especially young people, by talking their language. Once you have awareness, you need access. So what if you don't have an amazing hospital or a doctor next door? Again, digital companies like Babylon are trying to bring the doctor to your house and they offer a service that allows you to connect to a GP within minutes. Once you have access, you also need behavior change. And this is probably the toughest. We all know we need to exercise. We all know we need to eat better, yet we fail at doing it most of the time. Some companies are looking at gamification and fun ways to introduce behavioral changes. So I encourage you to try a zombie run, which allows you to run every day in the park by making you believe that you are followed by zombies and that you have to run as fast as possible. And this has been proven very helpful in making people to exercise far more than gyms or other things. Now, finally, healthcare is gonna be embedded. Healthcare is gonna be embedded within your home and there are already home agents like Amazon Echo, which is built on its AI platform, Alexa, that is playing the role of providing basic healthcare insights within the comfort of your home. In your workplace and companies like Limede are helping companies engaging with the well-being of their employees in a fun and social way. But also in your environment, thinking about physical exercise, you know if you wanna bike or walk to work, for instance, for your physical health, then it may do much more harm than good if you're in a very polluted area. Companies like Plume Lab are trying to have very small captors of air quality so that they can provide you with the best way to walk or to bike to work so that you don't have more harm by doing this physical exercise in your daily commute. Now, how to get there? And I'm just gonna give a very brief lessons from the incubator I've just joined. So it's an incubator based in London that aims at building new tech companies to solve the developed world's toughest social issues. And our first mission is to improve women and girls, emotional and mental health, which is a very crucial topic for which awareness has rates, but still many solutions are lacking. What makes it efficient in terms of innovating? We have a very diverse crowd. So we have 50 people from extremely diverse background. There are doctors, there are tech people, there are designer, there are business people, there are policy makers, and we are all put in a bag and we're trying to shake this bag, hoping that innovative solutions are going to come from this cross-fertilization of different people. It's mission-led, so we are not just innovating for fun or because entrepreneurship is fancy. We're innovating to actually solve social issues and looking at ones that have been massively underserved like mental health. It is time-bound. We have six months to find ideas of businesses otherwise we are going to be kicked out, which puts a bit of pressure, but it's also efficient. It's supportive but not prescriptive. So we are supported by the incubator, but they do not tell us anything about what we should do, where we should look, or the solutions we should get at. So we may end up building the next zombie run. And finally, it's user-centric. And we've talked about the importance of patience and I just want to end on this final note, which for me is the most crucial. It's extremely important to live and breathe like your user or like the patient you're trying to solve the issue of. You need to make sure that what you're building is truly adding value to them by ideally being as close as possible to them and living their life. It's the only solution to make sure that what you're doing is going to have a truly profound impact. Thank you. So Arthur, thank you for the very passionate speech. And Fanny also with your example, I think we start to see a convergence because basically you're telling us, you think big and very big, but you execute in small, rapid, iterative steps and initiatives. And we see also another pattern that we've not seen before is that a lot of these solutions are available through micro-ecosystems. And it's back to the early point of Natalie. It's very easy to build today and I think it's very important for developing countries to build micro-ecosystems that can serve a purpose as such because the technology is available and then you aggregate this component, it is interlinked and it works. And that's what's your point about being relevant and user-centric. Now if I try also terms of policy, I think it's a challenge because we tend to look at a horizon that is more mid to long-term, establish institutions and here, from a governance standpoint, it becomes difficult to cope with this trial and test approach, though we heard at lunch that COP 21, 2, 3, 4, 5 is accelerating the cycle and possibly embarking on this type of approach but a very large scale. But I think here the time horizon is a challenge. Now, talking about dealing with the policies, I'm pleased to introduce Aurelien who is on the other side, if I may say. What I call the public sector entrepreneur because we must be too to dance the tango. So the partnership must be created. You belong to this generation of millennials. You have friends, they develop, you interact very easily. What is your take from the public sector perspective on this development and what do you see as a solution that can be brought in the current institutions? Well thank you very much Patrick. It's a easy question. In eight minutes also. So thank you so much and thank you again Thierry for allowing us to have this fruitful debate. My name is Aurelien Biillot and I'm the head of trade policy at the French General Secretariat for European Affairs. And my job is basically to bring ministries in the same room and to make them talk together and have possibly innovative ideas on trade policy. Data is of course one of these issues, a rising issue to that aim. And as we are in the world policy conference talking about global governance, I think it's very useful to have this other side of the mirror. So if you allow me to take a step back, we've had presentation on four very promising startups from different parts of the world on different domains. In Europe you have about six million entrepreneurs in that field for about a value of about 60 billion a year, it's going to be 110 billion by 2020. So it's a very thriving industry. And at the same time we see some difficulties. Some are difficulties of old, like the question of regulation, of democratic ownership and other are new questions, such as the speed at which these technologies evolve and at which you need to react in these fields. The fact that on big data platforms bring monopolistic issues and finally the issue that was mentioned earlier in the conference that if it's free, you're the product, which means that you have to deal with the different environments. I take also from previous intervention that we have a mix of a thriving economy. At the same time we have lots of emotional and political issues to solve. So what are the main challenges for the EU to act in a policy perspective? I see three main challenges. The first one, which particularly did too, is data governance or let's say data privacy versus data sharing. The benefits of sharing are huge. Everyone has used the Google Maps to know where the traffic jams are. At the same time you might not want to be geolocalized at any time and therefore a balance needs to be struck here and as no one is reading the terms of use or the authorizations of the apps, it's a first, maybe one of you has, but so it's a first policy question. A second is the alternative between access and security. One of the huge challenges for data is to share it but at the same time you have security concerns that justify limits on that and fragmentation issues that have the same impact. And the third main challenge I see is that of fair competition. And one way of saying it is that these big data technologies challenge almost every business we can think of. They challenge traditional industries when Uber, I mean a data company goes in the field of taxi drivers. They challenge tax models when Apple only pays 50 million in taxes for 16 billion in benefits in Ireland. They challenge cultural diversity because online medias are not subject to the same rules as traditional medias. And finally, as a European, they challenge our economy because the US now and possibly China tomorrow have quite a competitive edge to that regard. So what can the EU do on these three aspects? And I think it brings us back to Natalie's remark of trying and build an ecosystem that allows this innovation to strive while addressing these three issues. So on data, for example, we both have an issue with personal data, which is data which is linked to someone and non-personal data. I think the issue on personal data, I mean, we have an EU regulation, and the fact will be how to implement the new EU-US data information, personal data information exchange. You might know that the previous one, the safe harbor, was disqualified by the Court of Justice of the EU. And the new one, which is enforced still since last July, is a bit smarter because it allows for better enforcement, and it will be extremely important because of course, this personal data goes to the US. On non-personal data, what EU policy can bring is to define precisely what barriers make sense and what barriers do not. For example, when you want to protect critical infrastructure, when you want to protect security issues, when you want to have platforms, online platforms that can resist attacks, these all legitimate barriers to data transfer. On the other side, it means that there should be a free flow of data on issues that are not sensitive to that purpose. On access, access versus security, so there is also this big work to be done on standardizing platforms and agreeing on common European standards, which will also be done in link with cyber security issues, and addressing the issue and enforcement, and this links with what what Eduard said on accountability, because having access to this data is what will allow us to implement this accountability. And finally, on the level playing field, which might be the most complicated issue, I want to go back to some points, for example, that Natalie made on developing skills or investments, but I would like to stress, of course, the French proposal to find a way to tax profits where they are made, and I will only stress the complexity of the issue because of the difficulty to localize profits, and hence the idea of also taxing sales. So as a conclusion, in this thriving environment, I mean, we need someone, an entity with a democratic ownership that can address these issues of data privacy, of access versus security and of level playing field, and I think that the EU has a chance here and could help fill this gap for all of us. Thank you very much. Thank you. Thank you. I think very good summary and the position from our alien doesn't require any summary on my side. And with this, I have the pleasure to open the floor for questions to our young participants. Yes. The lady on the back, yes. Amanda from South Africa. The questions I have are pertaining to some of the developments each of you have made in terms of your research. What is it shifting in terms of policy specifically and the impact on the community that it's having on, because it's great to hear what is emerging from those that are, I wouldn't say slightly older than me, but from those that are considered young leaders, what exactly are your developments in your research? What policy is it shifting and what's the impact of that shift and what is your trajectory and your sustainability in changing that policy? Thank you. I suggest we take a few questions and then you decide on which one you wanna go. Yes. My name, pardon me, my name is James Stewart. I currently work for the government of Canada. We have a room here full of industry leaders, government leaders, and I just ask the panel, if you think about your current situation and your desire for growth and how you look to drive the good work that you're doing, what's the one thing specifically? One thing that you would put in the ear of the leaders here who manage and drive the behemoths of the world, that when they run into small organizations or they run into startups or run into organizations like your own, what's that one thing you want them to remember, whether it's to forget about risk aversion or something else? Be very interested in that, thank you. Thank you, yes, here. Hi, I'm Manu, I'm an engineer from India. I have a question for Aurelion. So when we speak of cybersecurity in the EU, now I have a feeling that unless we resolve some of the larger geopolitical issues, we will never have that because it's an escalating war just being played out in different ambits. So I am just curious about your take on that because it's not only a question of defending ourselves using the tools of technology but to break the will of the opponent. So I'm maybe referring to Russia and what's been happening off late, but yeah, so I'm just wondering if there needs to be a more comprehensive approach when we speak of cybersecurity in concrete, yeah, thank you. Thank you, another question? No, but now I suggest we'll take cybersecurity at the end, it's more specialized, but views from the panel shift in policies and impact on communities. And I think communities, it's really one of the foundation of this new economy. We create a lot of communities, we grow people through communities, there is less hierarchy, so what are you takes, who wants to give it the first go? Anthony? Thank you very much for the question. So in terms of shifting policies, the one that we see most often is around data and how data has to be handled. We've seen a big change with the EU legislation around data. So where there are policies, they tend to be around data and largely around personally identifiable information. What's challenging for a company like mine is that every country has different legislation about how that has to be treated. We're working across four continents, including in South Africa where we're launching in eight weeks. So it makes it very complicated when we're working at the scale that we are, so we'd love for there to be a global body that takes that on and really makes it easier for small companies. And then to the question around what would I love to put in the ear of the people who I have the privilege of sitting in front of today. If there's one thing that I underestimated in starting this process, it's the power of partnerships between large organizations and small organizations. We've built really effective partnerships with banks and they obviously bring a lot to the table that we absolutely could not bring to the table, scale, operational capacity, risk management, huge, huge customer base. But we're also able to offer something that's difficult for banks to do at a large scale, which is to innovate. And with our bank customers, we are very close with them. We are in offices between them each other and it's been a really cost effective way for them to bring innovation responsibly. And I think that that's gonna be a model that's effective across all kinds of different industries, including government as we go forward because when you're a very large organization, it's just hard to keep up with technology. Thank you. Another view on these two questions. Yeah, go ahead. So on the, I really like the question of this one thing to ask.  People say a lot that entrepreneurship is about risk taking. I disagree. I'm coming from a scientific background. I think it's just about experiment. So my advice is really don't be afraid to experiment.   It can be downloading zombie run when you leave this place. So really don't be afraid to experiment. And if it doesn't work, just kill it, but kill it fast. That's the... Thank you. One point on this question as well. My job when I see CEOs of retailers, big companies, I do two things. The first thing that I do is I start by showing their own numbers. And the guy's like, oh, how do you know my numbers? And I explain it to them. And then I tell them that I've got the competitor's data as well, and this is how we do business. The second thing I tell him is that when I was, I mean, not a kid, but when I was in 2003, I was dreaming of being at Lehman Brother. I was using taxes. I was buying my PS4 at the local store. I was on Facebook, and every kid was on Facebook. Now, each of these things have just changed in a matter of 10 years, and some of them have even changed in a matter of four years. And most of the CEOs with which we discuss all the discussion and with there is the probability of your business not being uberized or totally transformed is absolutely zero, unless if you uberize yourself. And I've got just one example. One company uberized in a way itself, which is Indigo. I know you guys are familiar with Indigo. Indigo is the leader in parking in the world. It's the former of Vincy.  And OpenGo is the uber of parking lot.  Your number is recognizing something. And this is the only company that I know that has made such an effort to avoid being challenged by the new economy. So that would be the warning, I would say, to any CEO. And then the comment. First question about shifting on policies, I would say, since we've been working with the governments in the different countries, also different continents, yeah, of course, some governments, they tend to change because they see the impact, how impactful it can be, for example, in our own case, that how much money we can save for them. And on the other hand side, how impactful it can be this project for them. So they tend basically to change the policies. And in the long run, of course, it will be sustainable. But on the other hand side, there would be the countries that they are very, very conservative and it takes some time. And when it comes for a word that remains here, I would just say, do what you love and never give up. Because this is the only thing that can be sustainable in long run. I mean, I was reading an article that recently, there was a research in US that the majority of people that they don't like what they're doing. And I mean, I'm very surprised. I usually ask this question from the people that do you love what you're doing? And they say at the first sentence, yeah, we love it. And when you ask what is your dream job, they will say something else. So this is not what you love. And the only thing that I would say that do what you love and never give up because this is the only thing that can bring you happiness. Thank you. A bit to react on the first question policy shifting. I see a tendency to go from national policies to European policies at least in this field. We see some countries used to be very protective on these issues. And I'm thinking of course of France, other to be more open. But there is this feeling that the fragmentation of national markets is in itself harmful for the industry that we have an incentive to gain an edge in standardization. And at the same time to have a collective response to this, to the personal data, et cetera, issues. On Manu's question on cybersecurity, I will leave the floor to Patrick. I think it's different to your question on cybersecurity because you have to start with the threat as I mentioned briefly. And threat is, first, it's permanent. It comes from a very different horizon. Is it national, military or non-military? You have more or less organized crime as a threat. You have what I call the libertarian hackers of the anonymous type. And you have the sheer incompetence of everybody, included, that do mistakes that generate cybersecurity vulnerabilities. So in this context, your response is diverse today. And as I answered the question yesterday, there is an arms race on the technology, but then you have to know what is it that you want to defend? There will be never as in any other such similar situation before cyber warfare, a no risk situation. So yeah, so there is, we are still, what it creates in, is that the corporate world is involved into it. It's not only, we call it, in military terms, asymmetric warfare, where cybersecurity is a typical example of an asymmetric type of warfare, where a small entity can challenge a much larger organization and create disproportionate impact. And cooperation are involved into this cybersecurity question, like it or not. Because we are the vehicle, we are the means, through our networks, through the technology that we have deployed, and we are part of this, but from different angles. So there is no structured answer so far. There is a lot of coordination between the different institutions, and it's new for the corporate world to be involved in such activities as it was not the case before. But yes, we will have to organize a response, first an industry response when it comes to the enterprise world, and then connect with the different agencies. So that's for cybersecurity. If there are not other questions, yes? Two, yes? Hello, thank you very much for your speeches. So I'm Hermine Durand from France. I have a question for Alan. I would like to know how it works, because I'm quite curious to know how you bring the data together and why it hadn't been done before. And can you apply your method to other diseases? What are your next projects? Thank you. Thank you.  Should I answer directly? Yes, yes. Okay. Basically, like the core of the technology is like we have developed the software. And the software, we have different categories of parameter.  The other category will be electrocardiogram or ECG. Some parameters will be extracted from the ECG that will input into that category, and the other category will be a normal blood test. So this system, the user of the system will be the healthcare professionals, like the doctors or cardiologists or nurses. And so they use it at the primary care that they can understand, for example, if there is a need to do the angiography operation or no. Because today, angiography is the gold standard when they want to see and make sure if, for example, one of the main arteries of the heart is blood or no. And the point is that why it hadn't been done before, actually, the point is about that this is the emergence of artificial intelligence. I mean, the data is there. It's the way that we handle this data. And today, when we go to doctor, they basically, they use the man's intelligence. They want to correlate this data in their brain, but a human's brain is limited. I mean, the strongest brain can maybe correlate 10 to 20 different parameters, but we look at about 50 different parameters. So in this direction, we can come up with the more accurate results. Thank you. I've got a question here. Oh, and about the other diseases, sorry. Well, basically, we have built the foundation that can be used for the complex diseases, but the main focus at the moment is heart disease because heart disease is the number one cause of this all around the world. And about 17.5 million people die every year in the world just because of heart disease. Of course, in the long run, we have the plan that we extend it to other complex diseases like cancer. Okay, yeah, please. Hi, my name is Estelle Yusuf, I'm a journalist. I wanted to ask the panel their thoughts on what I see as a tension regarding this new digital era. As in, the data that you're talking about is a commodity for business, whereas for government, it's statistics, i.e. for some, it's money to be made, for others is the obligation to protect privacy and anonymity, and I don't know the term in English, but in French, that would be the right to be forgotten. As in, when I'm listening to the health applications that you're talking about, as a cancer survivor, I would be very scared that those data would be used by my insurers, as in paying a premium. So I would think that that's one tension, but what I would, our colleague from the European Union mentioned, the tax evasion. In a way, business, corporations are expecting, and that leads to what you mentioned about cyber security, are expecting governments to step in in terms of ensuring security, but are they paying the price of the accountability that Edouard mentioned? Corporations are trying to pay less and less taxes and being less and less accountable for a field where they almost have total monopoly. So I would have to have the thoughts of the panel on that. I guess I would first respond to your question by a question, which is that, I mean, Montaigne used to say that science sans conscience, n'est qu'une de l'âme, so science without maybe ethics. Pardon? Rablais? Pardon. OK, go ahead. To seniors, to tender. Anyway, so there is a trade-off between science and ethics, or science without ethics in modern terms doesn't go very far, but what we can see in a globalized world is that you can choose to have lower standards in terms of conscience or ethics to gain an edge on the economy and competitiveness. We see that on personal data. I mean, it's clear that if you give no protection to personal data, it will be much easier to create your business on that and to use the data. On the contrary, if you put up two strong regulations, it is certain that the economic opportunities will be more difficult. And this is increased by the fact that as you fight, you don't fight to be better, but you fight to be the best because it's a platform economy. So in a way, in such or such sector, you need to be first. And that's why my question in return is more that my interrogation is, I mean, I think that maybe in Europe we can reach an agreement on what is the right level of personal data protection. You mentioned the right to be forgotten. I mean, it is or will be in EU legislation. And so there will be an EU standard, but there will also be standards in other parts of the world. And this will interact with competitiveness. And my preoccupation is, where should we discuss this? Is there a place, a way to discuss this, given the pace of change? I'd like to add two things on that point, because that's basically the heart of my business, saying what is personal and what is otherwise data. The first thing that I want to do is to make a compliment to the public forces. No, the public, which is previously all regulations about private data only showed one thing, which is the guy who wrote the laws didn't know much about what he was writing about, or at least it would not, it was not aligned with the state of technology and the reality of what data was. So for the first time, GDPR, which is the regulation that has to be enforced by May 2018, it's the first regulation of its kind, which is basically matching in terms of expertise and what we live on a daily basis in our businesses. And the correlation of having more expertise from the lawmakers is that it creates opportunities for companies like Fox Intelligence, for example, because in GDPR, anonymized data for the first time has been properly described, and we sell anonymized data. So my take on that is by integrating private sector in the debate, by elevating the level of expertise from the public sector, then we can achieve the kind of things that has been achieved with GDPR. I also spend a lot of time thinking about PII versus non-PII. Personally, I identify with information versus generic information. And a large part of what makes my business defensible is that we have a large amount of non-personally identifiable information that data that I'm largely interested in is how you ask your bank, what's my balance? Do I have money? Can I afford this coffee? That's the data that we feed into our model. So from a business standpoint, we're interested in making sure that we can maintain that data in our defensibility. Where it gets interesting is the personally identifiable information. And you've got an example where you would be hesitant to have your health care information available. I have an example where I actually really wanted my health care information to be available. I lived in multiple countries. I kept moving, and every time I moved, they refused to release my health records. So now I don't know what my past is, so I've been negatively impacted by that. And I think that this fundamental tension is going to work itself out because one of the promises of AI is a level of personalization that we've never seen before. So where consumers can drive value from their data from different businesses, they're going to want it to be available. And I think that the logical consequence of that is that increasingly policies are going to have to find ways to give each individual user the autonomy to say where and how they want their data used. How that's actually managed and handled will definitely take time. It will also take a lot of technology to manage that. But we're going to see a personalization in terms of people getting to choose in a very granular way who and where their data can be used. So I would like to add one point from the enterprise perspective. In fact, it's our entire society that was mechanical process-centric. I mean, processes is something from the 50s, 60s. It's been developed and society was organized around processes. With what you just heard, we completely shift towards a knowledge data-centric type of organization. So it rocks the entire enterprise. You are constantly... It's a big challenge, but it's a challenge for society as well.  And one of the big challenge at large corporation I have today is how do you keep it together? Because the tensions are coming from everywhere. If I was discussing with the chairman of the large insurance company in the US, and he was explaining to me, looking at these value changes to illustrate my point, on the back in the refinancing, I'm attacked by the FinTech, not the kind of Natali, but other type of FinTech. On the front, I'm attacked by the type of Google. In the middle, in risk management, there are all the algorithm developers that are playing with this. I have already subcontracting my underwriting activities. So what am I left? What makes the value? And we speak of a complete activity that is a significant activity in our world, that is insurance. And that's the reality. And then the discussion we had is, okay, how can we maintain, because the value is maintaining this value chain together? And then he said, okay, how can you inter-operate with me? So which for us is a complete new world of engaging with our clients. And so we are all here discovering and in terms of policy and responsibility, because you're right, it's an important point. There is, beyond GDPR, there is another European directive called NIS, Network and Information Systems, that come into law in May, that defines the responsibilities, what notably between operators, service providers, enterprise, who is in charge of maintaining what, and if you fail, it's like for GDPR, the fine is up to 4% of your revenue, which is a big amount of money for anybody, whatever your size is. So this is a first attempt. But the fundamentally, we all have to rethink the way we operate. And so we don't have all the answers today. Other questions? If not, I thank you very much, yeah? Did you mind if I just add one thing that I, or if it's, if you- Oh, go ahead, conclude. Okay, if you, getting back to your question, James, one thing that makes for me the difference of most of the companies that I've seen as potential clients and the startups that I see, is that there is a hidden principle in every startup that I don't see in every big company. And this hidden principle is, you always hire people that are better than yourself, who have at least one thing that he does, whereas he has more talent than yourself. And the opposite is what you see in many companies, you take somebody who's not gonna be challenging you, who sometimes, let's say in political party, would be able to do things that you don't want to do. And the consequences of that, after 20, 30 years, is you end up with a GOP in the US, the Republican Party, which is basically, if you always hire somebody who's just a little bit talented than yourself, then you just take one generation, boom, you're gone. And the difference with startups, since we don't have that much money to hire people, we always make the effort to choose somebody who has something to bring to the company. And that would be what I'd like to leave in the years of a CEO today. Thank you, so thank you for your participation and I hope we couldn't bring a new light. Thank you very much.


Howdy how's it going? My name's Davy Chappie and today's time to make sweet, sugary love to the four natural forces of the Material Plane because we're going to be going over the guide to the good guy, Janasi. I'm going to talk about the origin and the everyday livelihood of everyone's favorite 90s-70s funk band and I'm going to give stats on how to play a pet rock in one of your own games. As always, keep in mind that a lot of this is just my opinion, so if you feel like I need to make like a tree and go leaf myself, feel free to play your half-baked elementals however you want. And just real quick, I want to give a shout out to my new patrons this month. Paul Weissman, Armani Asari, Jeremiah Williams, Heikin, Shelsa Bob, Daniel DeVare, DeVair, something like that, Samuel Soto, Luke Eith, N7 Sherk, Fressliver, Alexander and Thomas. Corey, thank you so much for being my new patrons this month with your cash dollars and my know-how I might be able to afford Wendy's for another week. But with Allaway, let's begin. Earth, water, fire, air, long and ago, the four elements boned in harmony. Then everything changed when the material dicks attacked. Only the genie, masters of all four primordiac ox, could handle the girth of the main plane. But in doing so, the elemental essence and the material must collided to create a new type of creature, a half-human, half-primal element consciousness known as the genasi. And thus the way that people look at extra curvy rocks was changed forever more. So there are four flavors of genasi that exist in the world, depending on which style of genie ended up showing immortal their whole new world. And these flavors are extra chunky earth, smoking spicy fire, creamy, moist water and light, fluffy air. The element of a particular genasi largely contributes to both their name, i.e. Fizz, Aqua, Rocky, Windo.  In the past, there also used to be para genasi, which were genasi that could manifest two different elements to form one franken element, such as a genasi that could manifest both earth and fire to make lava or fire and water to make steam. But after the multiverse-wide magical apocalypse that was the Spell Plague, genasi found themselves briefly able to attune to any single element that they wanted at a given time to correlate with how during the Spell Plague, the four elemental planes forgot what personal boundaries were and just smashed into each other to form one elemental plane suit. However, this didn't last long. And when the second sundering came about and unwrecked all the chaos at the Spell Plague Rock, the elemental planes decided that they just weren't in the best place emotionally to start a relationship and decided to remain friends with benefits. In turn, the genasi, as a reflection of the elemental planes, ended up getting stuck in whichever elemental form they happened to be in at the time. And the idea of a para genasi became all but a myth, even more so than the normal genasi are themselves. You see, in the normal world, genasi live very tumultuous lives depending on where they ended up living. Because they're so exceedingly rare, only coming into being when a genie does to your mother what Disney did to genie. Or if another genasi and something else mates or a normal creature is hit with a master blast of pure elemental energy, the majority of the material world has no clue what to think of them, usually confusing a genasi for an elemental or maybe a construct and demanding that any accompanying wizards de-summon them or leave them at the door because their kind ain't welcome here. Alternatively, a culture might look at a man made entirely out of fire walking around in a forest and take it to mean that the forest spirits are very angry and they could either seek to appease this quote-unquote fire spirit or if they are a particularly violent bunch, they'll go out with pitchforks and torches to burn the fire before it can grow. The point is that humanoids are dumb and they don't know how to react to a thing that they'd never seen before so results may vary and your liquid boy may be seen as a seagod if they come wandering out of the ocean and into your sleepy port town. And it doesn't really get any better or more structured for the genasi if it goes to their own would-be elemental home plane either. Have you ever gone to an event where everyone was supposed to dress for the occasion but you just showed up wearing that suit shirt that I know you have in your closet? Yeah, it's like that. Technically, genasi are made of one of the four elements but that doesn't really mean they belong there. Normal elementals will wonder what the hell this cosplaying human is doing here and even the genasi's phenomenal cosmic parent will just ignore it if it ever even shows up at all as it considers the birth of a genasi to be little more than just a byproduct of sleeping with a humanoid and if one does find its way face-to-face with its progeny, it'll just think, huh, well that's weird and go back to whatever it's doing.  But the one place that any creature elemental or otherwise can find a place in is in an adventuring party and to join one of those, you're gonna need stats.  After that, it all depends on your element. Air genasi get a bonus to dex, they can hold their breath forever because they are the literal embodiment of hot morning breath and they can cast levitate on themselves once per long rest making them really just good at pretty much anything given that there are absolutely no classes that don't benefit from bonuses to both dex and con. The earth genasi get a bonus to strength, they can easily move through difficult terrain made out of earth or stone and they can cast pass without trace to presumably make themselves look like a statue. I really don't understand why that was the spell they got but it does mean that you can play some of the punchier classes like a barbarian or fighter and still have a stealthy trick up your sleeve if you ever need to get out of dodge. Fire genasi get a bonus to intelligence, a special red dark vision that goes out to 60 feet resistance to fire damage and they can cast produce flame whenever they want followed by burning hands once per long rest. While the bonus to intelligence implies that there'll be a good wizard, I found that fire genacies can work pretty much anywhere given that their abilities are just so universally versatile. Finally, the water genasi get a bonus to wisdom resistance to acid, they can breathe both air and water, they have a swimming speed of 30 feet and they can cast both shape water and later they can cast create or destroy water once per long rest. Like the fire genasi, water genasi aren't super beholden to the roles of the cleric, druid or ranger due to the powers that they get being able to benefit anybody but it does seem like maybe Wizards of the Coast is perhaps prioritizing some genasi stat blocks over others but that'll about do it. I hope you enjoyed this video. If you did, like, share, subscribe, comment, ring that bell icon.


In this video, we provide the solution to question number 10 for practice exam number one for math 1220, in which case we have to evaluate the indefinite integral e to the two theta times sine of three theta d theta. Now the fact that I see this exponential times a sine function, this makes me think I want to use integration by parts, more specifically integration by cycles, because as you take derivatives of e to the two theta or antiderivatives of e to the two theta, you always give back e to the two theta with a constant multiple that is changing. Same thing with sine, when you take the derivative of sine or the antiderivative of sine, you're always going to give back a constant multiple of cosine, for which if you do that again, you'll get a constant multiple of sine. And so if I do integration by parts enough times, I'm going to cycle back to the original expression. So that's going to give me this integration by cycles, okay? So for my first iteration, it doesn't really matter which one you do, just think, just be consistent about it. I'm going to take u to be e to the two theta. That means du is going to equal two e to the two theta d theta. Then for dv, I'm going to take that to be sine of three theta d theta. And that means v is going to equal one third, well actually negative one third cosine of three theta. So if we apply that, I'm also going to use the simplification that the original integral I'm just going to refer to as capital I, because I'm going to need that later on. So I is equal to, if we apply integration by parts, we're going to get negative one third e to the two theta cosine of three theta. Then we're going to subtract from that the integral of v du. So we get a negative one third cosine of three theta. That's the v times by the du, which is two e to the two theta d theta, like so. We of course can simplify that. We can make that a plus negative there, plus plus. Let me just erase that negative sign, make it better like that. And then there's these constant coefficients in there. You don't necessarily have to do too much at once. Negative one third e to the two theta cosine of three theta. Because there's this one third right here. There's this two. I'm going to bring out the two thirds out in front. And then I'm also going to put the e back in front. And so this is what we predicted. We're going to get something that looks like e to the two theta times cosine of three theta. So I'm going to do integration by parts again. That's how we do it with cycles. You have to do it at least twice. Well I guess maybe you could get away with it once, but not in this situation. But make sure you do integration by parts, you're consistent. If you was your exponential beforehand, you're going to do that again. So two e to the two theta d theta. And then for dv, the trig function is going to serve that role this time, cosine of three theta d theta. And so then v is going to equal one third sine of three theta, like so. So putting those things in there, you're going to get i equals negative one third e to the two theta cosine of three theta. Then for this next one, do remember that the two thirds applies to everything coming up just now. We're going to take u times v, so we're going to get one third e to the two theta sine of three theta. And then we should get an integral that resembles the original one we're looking for. We're going to get a minus integral of one third sine of three theta times cosine times two times e to the two theta d theta, like so. So up to a constant multiple, I want to be aware that that integral right there is in fact the original integral. So let's write that one more time. i equals negative one third e to the two theta cosine of three theta. Now if I distribute this two thirds throughout, you're going to get two thirds times a third. So we're going to get two ninths times e to the two theta sine of three theta. Likewise though, here we have a two times a third, so that's a two thirds. So then when we distribute that, we're going to get negative four ninths. And then once we take the coefficients out, we have an e to the two theta sine of three theta. That's the original integral again. So that's going to give you this i right there. So what I want to do is then add to both sides of the equation this four ninths i. Upon doing so on the other side, we have a nine ninths. You add a four ninths to it. That's going to give us a 13 ninths i equal to then the negative one third e to the two theta cosine of three theta. Then we get this two ninths e to the two theta sine of three theta plus a constant. And so then we're going to times both sides of the equation by the reciprocal of this coefficient. We can times both sides by nine thirteenths. We have to do this on the right hand side as well, nine thirteenths. And so then in the end our integral i is equal to what we distribute the nine thirteenths on the other side. You're going to end up with a negative three thirteenths e to the two theta cosine of three theta. On the next one, the ninths cancel out and you end up with a two thirteenths e to the two theta sine of three theta. And then you do times like arbitrary constant by a specific constant. That's just going to give you back a constant again. So I'm just going to still write that as a plus c. And if you want to switch the order, write the sine before the cosine, you can do so. But that then gives us the anti-derivative we're looking for. And we accomplish this using integration by cycles.