Right. So, I'm going to keep my talk fun and short, because I know everyone's dying to go to the pub, you know. And it's also one of the beginner series. So, to bring more new people in, you know, get excited about Ember. It's like the future. Okay. So, people ask why? You know, why Firebase? Why can't we just use, you know, Rackspace?   It's like, it's like, you know, most of the stuff that you see is happening, you know, today, is that you're essentially disaggregating from hardware, right? Which is what's happening, like, across industries. It's not just like hosting, you know.  And like, you know, you have like Airbnb has no, so basically it's like the most part of people in the world, they don't own anything, but they control everything, right? And that's kind of where the whole thing is going. And just, you know, so, my point of that is that the same thing is kind of happening with, you know, developers as well. And so, you know, this is an actual startup. It's called, yeah. So, my point is that which brings the solution of web apps, because that is an actual startup. And it's like, so everything becomes a commodity, including your phone itself. Because the way they make that technology work is they shine some lasers down down the arm.   And the innovation kind of begins and starts with software, you know, which kind of brings me to evolution of web apps. And it kind of had data centers, Samsung, and Heroku came along. And when I show Firebase here, I don't really mean Firebase just by itself.  And so we're seeing the trend that's this kind of boss, which is like backend as a service, right?  So, and the other side of the story is, you know, actually the evolution of the front end, if you will. And, you know, what's funny about this picture is that that's literally my evolution. Because I've gone through like, you know, pure JavaScript and jQuery, you know, then Angular and eventually got into Ember. And so if you combine the two together, what you have is, well, Ember on fire.  And so the maximum number of like child nodes you have is about 32. So, you know, it can go beyond that.  And, you know, one shout out can only be 10 megabytes because they store the whole data as, you know, Bay 64 encoded binary data.  But know that really stops that. And you can, you can have, you can write data from SDK in the 16 megabytes and tops and or from the rest, you know, it's up to you. But if you don't like any of them, because my whole idea of this talk is to provide a different perspective, right? Because most of the previous talks about controllers and we talk about, you know, all this kind of a traditional Ember thing, whereas the way I would tend to build things, I would just build a bunch of components and services, and I would just wire them up, you know, with the router. Like I wouldn't use controllers or avoid them all together, no injectors, you know, and I'm kind of like very Ember 2.0 future looking. And so, and so if you have a Firebase object, like in the whole SDK, and you don't want to use either of them, what you can do is just monkey patch the Firebase object with 20 lines of code, which essentially converts it into an observable. And so, and so what that allows you to do is essentially treat this the whole thing as an observable. And for the purposes of prototyping, it essentially allows you to, you know, build collaborating drawing apps in like four lines of code. I wrote this like literally in four lines, and it's just a bunch of observables, and they, in going through some pipe, pipe through some filters, and eventually just, you know, start some data on the Firebase.  If you're trying to build something, at some point you're going to have some data, you know, to show off.    And so, Zapier, for example, it has, I don't know, hundreds, it's not thousands of integrations.  And so, what it allows you to do is you can pick any integration you want.  So, you know, if you just created the record in Ember, and, you know, saved it to the Firebase, that would essentially trigger the Zapier. And the way, the way it would happen is you essentially register from the account, it's free, and, you know, you just put in the Firebase account, URL, you know, it's simple as that, and then register for a mail gun or mind drill or whatever your source provider says, just check in your APIs right there, you know, and then URL, and then set up some some, some kind of events. Because those things that I've recorded here, they automatically become accessible in here. So, you know, if you're trying to send something like personalized email to someone, that's unexpected. Right. So, yeah, you can, you can basically select what you want, you know, it's deducted from what you recorded.   And obviously, you can test this, the whole thing. And they provide very nice interface for that. And so, but it's Firebase good just for prototyping, you know, because that's, that's, that's kind of like, that's, that's how usually people start. That's kind of how I started.  And then some people say, it doesn't scale, or, you know, it doesn't have the features to handle, you know, all these other things and, you know, complex problems that they have. And so, I just like to have a look at it and say that, especially since the recent developments that are happening, and Firebase being brought by Google, and they do provide backups to all the people who are scared of losing their data, if you will, or just not having, you know, like, like, what if, what if Firebase goes away, you know, on all these kind of things. Although not likely. I mean, they do seem to be very active in hardware as well. I have been to the talk of, of Resin. And basically, it's, Resin is like Heroku, but for hardware. And so, if you combine that with Firebase, you can, you know, you can essentially build, well, an illusion of hardware products. And so, because what, what Resin does, it obstructs away all of the, you know, from writing code to deploying to all of your devices. And so, what you end up with a system is like with Tesla. Like, when Tesla reads their cars, and they had, they had like a flaw, right? What does Toyota do? They just recall the whole fleet, and just, you know, go into massive, massive loss, you know, millions. What Tesla did just pushed a firmware update over the wire to all the cars that are unavailable. So, like, Resin kind of allows you to do that. So, you know, even after you've sold your devices, or, you know, that kind of stuff.  And so, and because especially since they are going into the hardware and all this pervasive thing, it provides nice security features.    And everyone is always concerned about this.  And, you know, and this talk I've just been to, it's literally with the service workers, they managed to bring down the whole thing to, like, you know, nine seconds.   But also, if you combine with all the other technologies that are out there, like service workers and animation API, you can essentially, you know, build anything at incredible speeds, which is kind of good and bad in a way, because that means competition is pretty, pretty high because the lower bar is quite entry. And so, you know, I figured I'm just going to give some examples of how Firebase tried to handle the, you know, is it just for prototyping kind of question. And so, I have used to in the past, but basically, they have, you know, work was they have the graphing libraries, they have integrations with the elastic search, and, you know, ability to essentially import like ridiculously size JSON files into the Firebase itself, and using as a storage. And so, what you end up with is an architecture that looks very much like this, where, you know, you're essentially providing all of your clients like kind of real-time thing. Like, it doesn't matter where you go these days, everyone expects stuff to kind of happen real-time in push notifications.     And all these things, they, you know, they want to be kind of connected. And so, you know, at some point, you end up building applications, not just for, well, the web, really, but like for everything.    And so, I mean, I'm definitely a big believer in that, is that when you have very, very, very high concurrent applications, which is why you have, like, channels and go, and, you know, all these other things.  When you have, and it's pretty much a kind of a limitation of human brain, in a way, is that you just can't handle this much of a complexity in different things that happen at the same time. And so, abstracting your way of thinking and your way of writing code is kind of important.  You know, there's startups that provide load balancing as a service. And so everything becomes more and more commoditized. And like since the beginning, it's becoming desegregated from the hardware.  And so, probably the best example I've heard is there was a talk, and the city of Netflix was talking, and he was like, you know, saying how you're using SSD now, and, you know, and all, you know, to improve the speed. And so this guy at the end that says, he started like a big rant, how, you know, how SATA is much better, more stable, more robust, can store more data. And the whole round was like, I don't know, it was like 40 minutes, right? And the student just, you know, stands there, and he just, just listens, listens, listens. And like at the end of this rant, he's like, I don't care. I rent them.  Half like that.  And it's kind of, you know, get the first passion out. And, you know, it's kind of a bit of a prototypic along the way is going to save you a lot more, you know, towards the end of it.  And so, yeah. There's Ember Fire. If you're doing crowd operations, it's, it's really good. It became, became really good probably like, when I started doing ever, which is like six months ago. It started becoming really good in terms of, you know, when the first started out, Ember Fire had its own syntax, but there's now, they just use Ember Deer syntax. So, there's no new syntax to learn. And, you know, it's been like ridiculously active in terms of, you know, development and those kind of things.  So, you know, it's, I just use pure Firebase. It really depends what you're doing. You know, if you're, if you're, if you're, if you're using it by data, Ember Fire is definitely the way to go. Yeah. Yeah. Yeah. Well, I would tend to start an apps with, with Firebase, not to use like, you know, pretend there or Ember Sound Grid because, because Firebase copies the data from your front end. So, you don't have to implement the whole thing twice. So, you essentially have like a, you know, it's kind of, I think what the future should be is like, why would you have to implement every single piece twice? You know, in the back end, the same thing in the front end. And the Firebase kind of Olivia is that, because it just allows me to, and it's very easy to, to switch. So, like, if you built the whole thing and, you know, Firebase just switched the adapter.  It's like, the everyday that makes it very nice to be able to switch to different APIs without barely any code change. How would you tend to handle file upload in a prototype with Firebase involved? Say if I wanted to store my files on S3, for example, and then save in URL or something like that in Firebase, how would you, what set up would you go for that? They're coming with a feature that essentially allows you, well, they're building S3 for Firebase to solve that problem. But, you know, right now, it probably just uses S3 or something like that. You know, there's quite a lot of integrations where you would just store the URL on Firebase, you know, but the actual file, you know, on S3 or, you know, some other hosting service. They are building, I don't know, they haven't announced it yet, but they're going to have, you know, the whole conversion to Temnio and the whole thing. Yeah, it's like Firebase, but Facebook bought it instead of Google. Do you have a real time functionality in the Firebase service? No. Firebase isn't as full stack as, well, personal as full stack. Like, in terms of latency, push is probably the best, but they only provide web sockets. Whereas in terms of a number of features, Firebase is definitely the best. You know, in terms of, like, because that's the whole idea about prototyping and building things as quickly as possible.  It's just to build as fast as possible, as quickly as possible, as little as possible. And so, you know, it improves your decision making. It improves, you know, your ability to prototype stuff and, you know, build from there. It's kind of like, you know, for frameworks, which one to choose? You just build some applications of all of them. Then you pick one, right? Instead of just picking one, you know, you're going to make more of a decision. So, same thing. It's kind of, for me, it works to prototype stuff, like, you know, to build this stuff. And would you do it that way or that way, you know? And so, you know, which one will be faster?  But, yeah. It's really gone uneasy. A question. If we use back end as a service, does that make us cheap?  Well, you know, I just don't, like, yeah. It's just, you see the standard corporates, the corporate environment as well. Like, people who are now switching to EC2 or whatever. They stop having their own cyber box. It's always my cyber box, you know? Like, and they're building less secure systems than what EC2 would provide. Like, it's, I mean, it's work from corporations. It's insane. Like, they think they're more secure, but they're not. It's just, you know, it's like trying to build their own number from scratch. Probably, you know. It depends on the organization. So, some of the clients I work with are in control, and those have certain data where they need to be much more aware of what's going on with that data. And then using a service like EC2 or Firebase or whatever is easy and flexible for them because the risk of data loss or any sort of elk ride because of it is very low. Yeah. I mean, I think I've said this before, but I truly believe that everything in the middle will disappear.  And, you know, they provide the back end of the service, and the developers provide the innovation part. And everything between can't compete with either.   So, you know, it's like, and so this is kind of like, you know, this is if you're any developer instead of you're building Google. Can I get a show of hands who's using a platform as a service like Firebase in an app today? And everyone else, you're building your own back end infrastructure with Rails or .NETs or something like that. Lots of those are stuff because our data is in the data center. They're obsessive security. Even trying to get hold of that data, you have to go through three different layers to actually get to it. So, the idea would be to use Firebase. I would be looking at Firebase to for real-time. And that real-time service to a customer is great because that's that's what you want to see.  You want to say that and then you're back on your site. You want to see the prices change. You want to know straight away. You don't want to wait like our back end systems do to date or two weeks or whatever it is. You take to that process. So, you'd want to have something like Firebase, but it's, again, we have a limitation which is security. And they're obsessed. They are, like, legally obsessed with the firewalls and which the data is going through the firewalls. And that's what I think this issue is. We can convince them, okay. That's always the opportunity to get rid of it. They're going to move, aren't they? There's a contention around personal information. Yes, it's DPA, data protection. You don't want to be giving that all that stuff away. And this is where it becomes an issue. So, Amazon, we've been looking at using Amazon as a, again, as a place to get the stuff up quick, get the servers up, running. As soon as you start saying, well, you've actually got to now make sure that the firewalls are all protected. A lot comes out. PCI compliance, you stop and then it starts loading on the services. You start loading on the extra services. They exist. You can buy the extra service on it and you start actually costing it up and it's actually more expensive up to a point. It's up to, when you're not, I'm not saying it started to worry about DPA, but most of all, and once you start crossing over into corporates, data protection, PCI compliance, Amazon, they are compliant. We've got compliant systems, but then if you then don't follow the rules, a compliant system can uncomply very, very quickly. For example, back in its service, brilliant. We were looking at it a while back, and it's just that extra level that kills us. Because we want to be fast. We want to be quick. We want to be innovative and Firebase is great. And we use Apogee. Apogee was a brilliant thing for building our first APIs. It was a proxy, very, very quick. It exposed our crappy APIs that we'd build in the post and get servlets. Very, very quickly, we build up an API and build calls into it. Apogee, brilliant. You say, oh, I want an enterprise version of that. It's about segregated our new PCI compliance through it. The cost went from zero, which is what Apogee was, the free version, up to £100,000 a year. Just go from no security, enterprise security. And it's all running on AWS. Apogee runs in AWS, but they've got an enterprise version of the enterprise version, £100,000 a year. Brilliant to print site. Pretty expensive, so you actually start to actually look at it as a corporate, more fortunately. Good for Princeton. You still use it, but that takes. All right, any more questions? Okay, give them a hand.


So we're here at the blue boo and who are you? And here you have Android wear this is a mock-up, but it's Android wear and is it with MediaTek Yes, it's Android smart watch MediaTek Android wear. Yes, but it's mock-up But how soon is on the market and how much we are come out at the end of November End of November. How much the price? Very cool price and we'll have a heart rate monitor On the back and the pro-go pin charger and how long is the battery life? Maybe it will be long Hopefully we will see next month. Yes, and let's check these phones. You have out here This is the blue boo X touch. This is a octa core 6753 This is the one here You have different color also. You have a white one white one and a black one Let's check the white the white one Here and can you show around?  Let's compare the two So white and black huh and what's the price for octa core? $149 Where where can people buy this? Sony camera So that means very good camera and this full HD IPS. Yes, what is it the on-sale? OGS yes, OGS technology right here and This this is a this is here and it's 3 GB RAM 32 GB RAM All right, and how about this one? 125 this is the X 55 500 this is HD display quad core LTE Big battery big battery you can turn off the brightness a little bit Can we see how big is the battery? 5000 battery 5000 battery It's 300 can you open? Can you open in the back? Huge battery inside Yeah, no problem. No, it's okay. Don't break your nail and Yeah, and then you have SIM card slots here dual SIM Yes dual SIM card and on this one also Can you open the SIM card slots? You show you have dual SIM card slots One micro SD and they can be a two SIM card one go here and one go here Mike nano and mean micro SIM card. All right, and you have the x6 plus coming also Is this real? Yes, yeah, and this is a octa core Size of the screen 5.5 inch full HD None air gap. What does that mean? It's on sale On sale Can you take off? Yeah, and like this All right, they all come with a lollipop Android was it camera on this one. Is this Sony also? Sony also Yeah You can go in here. It's all the latest version of Android 5.1 What's the price on that one? 125 125 also yes, but it's a full HD. Yes octa core. Yes, so it's the same price is that one Same price as this Big battery, okay, so 125 you get Why is it not Three why is this one cheaper than this one? This is only 2 GB Ram. Yes, there's also three here at 16 16 Where can people buy this in Europe? Yes, do you sell in the USA or no?


OK, welcom everybody. I think we're going to start. We may be joined by other people coming in, but that doesn't matter. We'll get going to keep on time. I'm delighted to have with me here today Dr Abbey Bang, who I first met several years ago through the work, the collaborative work that we were doing together and continue to do together with Save the Children, and that the organisation that Dr Bang founded together with his wife 26 years ago, an organisation called Search, which stands for the Society for Education, Action and Research and Community Health in an underdeveloped area in the state of Maharashtra. Dr Bang and his wife work with 120 villages to provide community-based healthcare but also critically to do research. They've developed a village healthcare programme, which has now become nationally and internationally famous model that has influenced healthcare policy both here in India and in many other countries around the world. I think part of that is because of the power of the research that has all been documented in publications like The Lancet. It's a very persuasive model, not only on the ground, but in terms of being able to prove that it really does work and it's affordable and can be scaled up. Dr Bang was also appointed as a member of the high-level expert group appointed by the Prime Minister here in India to prepare the blueprint of universal healthcare for India and may have some views on that if we have time. He was also anointed by Time magazine in 2005 as the global health hero. He's certainly one of my heroes and it's just a pleasure for me to be able to interview you. Dr Bang, I wonder if you could start by telling us a little bit about how you've managed to achieve these quite startling breakthroughs in terms of reducing child mortality rates. Particularly interesting in the context here, we are hearing about how India is failing to at the moment be on track for its Millennium Development Goal 4 to reduce by two-thirds the number of children dying before their fifth birthday. And yet you've been able to pioneer and prove a model that is bringing those rates down quickly. So can you tell us a little bit about what you've achieved and what you've learned? Thank you Jasmine. It's not the first time that we are getting late in India in this room, but we are late in even achieving Millennium Development Goals. And the delay that would happen in achieving MDG 4 would mean for India alone 2 million excess child death. So delay is a major factor. As you said mentioned earlier, the place where I work called Garichiroli, we are more known in India because of the Maoist activity and the violence in our district. It's a remote district, very poor, tribal, covered with forests and nearly 27 years ago Rani, my wife and I decided to go there and started this organization, our own search. After a few initial blunders, we realized that a doctor or a researcher should not begin with what he thinks is needed but must begin with what people think is needed. So we started organizing people's health assembly every year and then people told us what research we should be conducting. So one of the first four priorities that they mentioned, we mentioned, our children are dying. And around the same time, one very major but unfortunate thing happened that on one rainy season night, two tribal women knocked on our home and with a very sick child in hand. And within two minutes that I could examine, child had pneumonia, dehydration, malnutrition, two month old child and before I could do anything, the baby died. Now this woman and this child had come only from a distance of four kilometers from our hospital and I could still from their history, from their story, I could count that there were 18 causes why this child died. Distance, poverty, literacy, no bridges, no doctors, et cetera, et cetera. How can we save these children if there are 18 causes pitted against those helpless children? One solution that we could think of was if babies cannot come to hospital, hospital must go to where the babies were. And that's how this idea which was later on named as home-based newborn and child care that emerged. Why not train if doctors are not willing to go to villages? Why not train a literate village woman to become a newborn and child specialist of the village on the lines of barefoot doctor in China?  The IMR was 121 at that time. Pneumonia and pneumon deaths were the most important causes of mortality. So we selected village women, we call them ROGADUT, which literally means messengers of health or angels of health. So these village women who are trained and certified by search, they go from house to house, educate mothers about how to take care of health, of their own health, of baby's health. When the babies are born they are present at the time of delivery, if it is home delivery, they start immediate breastfeeding. They take care of mother's health as well as baby's health and then subsequently provide support to newborn baby. As we all know, the first one month of life of a human being is the riskiest period in human entire life. And the risk of death is enormous. At that time it was 60 newborn babies died within first one month out of the total 1,000 babies born. Some of them were sick also. Now again, no doctor would reach there. So we had to train this village worker ROGADUT even to treat sick neonates, which was considered a very bold thing, a lot of medical opposition. How can you train semi-nutrate women to provide treatment to newborn babies? World Health Organization used to say in those days every sick newborn baby must be hospitalized, but there were no hospital within 300 kilometers of where we were working. This approach we conducted a rigorous field trial and it reduced newborn mortality rate by 70%. If reducing newborn mortality rate is considered a very difficult challenge, if you reduce by 5% in developed country it becomes headline in newspaper and television. Here it was reduced by 70% and in that area remote, difficult, poor, illiterate and still the infant mortality rate because of these women and the healthcare provided through these women, IMR reduced from 121 to 30. And mere coincidence, but India chose that as the national goal subsequently to reduce IMR to the level of 30 in the next 10 years. These women had achieved it ahead of the national goal. Now this method we published in the Lancet, Lancet not only published but later on selected this research as one of the vintage papers in the Lancet ever published in 180 years history. The main reason is that problem is not only local. Deaths of newborn babies and children, even today nearly 8 million children die worldwide every year. One and a half million die in India alone. So how to save them with limitations of hospital based approach. So this approach probably showed the way that no these newborn babies need not die and they could be saved. With this global need and the strong scientific evidence, it was picked up by journals, academicians, but also organizations like Save the Children and through a very good shake hand of search and Save the Children and later on with Government of India. This model was scaled up. So now this has become the national policy in India. Health Ministry has made a national program out of this and ASHA is a new community health worker in India. 800,000 ASHAs are being trained in this gradually model and how this is the bag. This is really the power bag which is used to empower that village woman community health worker. If you can see, there's a logo here, that woman who is in that home with a baby in her hands, helpless, her baby could be sick. But you empower that woman with some knowledge, some training and these equipments and she can go from house to house and she literally makes every home and hut turns the home and hut into a newborn care intensive care unit. Because the results are so dramatic. So this has now become not only a national model in India, but nine countries are emulating it in different parts and in 2009, WHO, UNICEF, USAID and Save the Children came up with a global guidelines that in developing countries where there is no access to hospital based care, this is the way to reduce newborn child mortality. So two questions following on from that great story. You mentioned opposition from the established medical profession. Can you tell us a little bit more about that? Why wouldn't they want this to work? I mean we're all working on the same things here. And my second question is what's inside that power bag? That's a secret. The medical opposition was not so much because of Western interest because newborns in rural areas where nobody's Western interest. They were not providing business to anybody so nobody was going to lose business by training community health worker. It was more, a medical mindset always say, believes that only doctors can deliver best care and nobody else should ever deliver health care. This was in a way sort of violating those norms. But I must admit that the pediatrics leadership in this country had been very generous. It looked at the evidence, it looked at the national need and then subsequently pediatrics and the neonatalogist leadership of this country have vigorously supported this model. Now this bag consists of few equipments and things which altogether cost not much really just $30. But this is health education flip chart. We call it dialogue with mothers. This is almost like a knowledge vaccine. Using this, a mother can be educated by community health worker as to how to take care of her own health. This is a warm bag. Babies who are preterm, low birth weight or hypothermic. How to keep them warm at home in cold winter or rainy season? They don't have electricity, they don't have heaters, there are no incubators.  And then babies who are born at home, but who don't breathe immediately, they need immediate breathing support. If you don't provide them breathing support within next two minutes, they are dead. So this is called AMBU bag which is usually used by anaesthetists for emergency oxygenation of patients who are unconscious. She is trained to use this and give breathing support to baby. This is the weighing scale. So there are some equipments which allow thermometer weighing scale, which allow examination of the newborn baby. And some which allow to take care of the baby and keep baby warm, early breastfeeding, and then if it's sick, treat. And tell me a little bit more then about training these, as you say, illiterate women often in the village to be able to perform these functions. I've just come from the plenary session on missing women and in fact one of the points that came through was the status of particularly rural women. And how it's a problem on the one hand but also potentially a huge opportunity. Tell me about, you presumably see these women more of as an opportunity. Tell me about that. It's an enormous opportunity. And the type of women who can reduce child mortality, a problem with some, a government of India or society as a whole is unable to handle. And these women are able to handle. These women are mothers, grandmother, traditional birth attendant. And this new worker, as I mentioned, messenger of health or ASHA now at the national level. She's from the same village. She's not brought from abroad from outside. So she's not posted there. She's not paid salary. She's selected from the village. She's selected from the village. She's serving her own community. And she receives 26 days training. At the time of selection, we look for certain qualities, certain attributes, which is most important. Her literacy is not that important as their attributes are. So we look for certain attributes. After 26 days training, this training is divided into multiple small parts. So every month she receives three days training and then works in her own community. So her own community is practically her training laboratory where she weighs baby. She examines them, takes their temperature, talks to the men, explains them. That's how gradually over a period of one year her skills are built up. She goes through rigorous evaluation. A supervisor visits her once in every 15 days. And then finally, when she passes that evaluation, the training method standardised that we have standardised in that we found that 92% of village Arogeddut scored more than 70% marks. Here in India, I became doctor if I score more than 50%. But for Arogeddut, we have kept it a little higher. It has to be 70%. She's going to deal with sick babies. 92% Arogeddut performed extremely well. So this method of training is now standardised. And as I said earlier, 800,000 ashras in India are being trained using this method to provide home-based newborn and childcare at the doorstep in Indian villages. That's very impressive. So you mentioned about when you became a doctor. What is it that made you decide to take this slightly alternative route rather than becoming a highly paid consultant in a hospital or perhaps go overseas? What inspired you to take this route and to dedicate your life to this area of research and development? It's a little long story, but I'll cut it short. Nearly 65 years ago, my father who was a professor of economics. And he taught in one of Mahatma Gandhi's college. So he wanted to go to the US for studying economics further. Before leaving for the US, he went to see Mahatma. And then both to him asked for his blessings. And Mahatma Gandhi looked at him for just a few seconds and then said, If you want to study economics, go to the villages of India and not the US. Right there and then he tore away his travel documents, his admission papers in the US. And within one month, he started with his students. He went and started living in a village. So when I finished my medical education, post graduation, et cetera, et cetera, his words were still ringing in our ears. And commitment was that we must be able to provide health care to the villages of India. The unknown path did not know how to do that. Did not know even what the main problems were. And that's why when we went to Garichiroli, then we thought that if we anyway want to do this, let's go to the place which is least served, which is the most difficult. If something works here, it ought to work everywhere in India. So we chose Garichiroli. That's why we named our organization search. We didn't have answer. We were not lights. We were searching in the dark. So the place we live, our headquarter campus that we have started there, we call it Shodha Gram. Indians here would understand the word quickly. Shodha means again search. So it's a search village, searching in darkness. Now that's how my journey is. Look, my childhood was spent in Mahatma Gandhi's ashram. And that ashram is called Seva Gram, which in Indian language means a village for service. So I started from Seva Gram and ended up founding Shodha Gram. And you were fortunate enough to find a wife who clearly wanted to achieve the same things in life as you? Well, we were classmates. We fell in love with each other mainly because we had similar dreams. How wonderful. What a lovely story. So now tell me at the World Economic Forum, as you know, one of the big focus of discussions is around how multi-sector collaboration between different types of organisations, government, businesses and NGOs can work together. I believe you've got some thoughts in terms of how NGOs, organisations like Search can work together, particularly with business. Can you tell me about them? Look, for any collaboration, I believe that mere convenience is not enough. There must be matching of values and goals and then subsequent practical issues. So the first thing which has to occur, do the values and goals of corporate sector and NGOs match? That's a big question. And I think we must begin little bit philosophically there because without that clarification, mere convenient working together won't last. Charles Handy, who, I don't know whether he's still alive, but he was a very well-known management guru. He once beautifully said, he said that communism had a beautiful dream, but it did not know methods how to bring that dream into reality. And then he said, capitalism has wonderful methods, but it has no dream. And if capitalism has no dream, then we'll have to invent. Capitalism needs a soul. It needs heart. Later on, as the corporate social responsibility came into vogue, I think it's a very good beginning. It's a very good beginning, but there again that social responsibility remains peripheral for the corporation. The main job is earning profit. Michael Porter has recently written a cover story on Harvard Business Review and he has put forward this concept of shared value. To quote his words, he said we'll have to reform capitalism. Not only at the periphery, but the very purpose of capitalism probably has to change and it has to become shared value so that the corporates and the people, the customers, as well as employees, all they share similar value. To take this little back, I'm very surprised, but Mahatma Gandhi proposed something nearly 70 years ago which now Michael Porter and Bill Clinton and Bill Gates are equalling. He said that, look, a corporation or company has to be run like a public trust. A trustee of a public trust is dedicated, he's committed, he has passion, he works very hard, he or she, but he doesn't own it. Actually modern corporations also are more or less run in a similar fashion. The CEO or the managing director doesn't own that company, but still he runs with dedication and passion. So a little shift in the outlook that corporations companies need to be run like a public trust. Then that immediately can, it can reduce distance between NGOs and corporates and both may share similar value and similar goal. And there are n number of ways in which companies and NGOs can work together on social problems. We are talking a lot about India, economic superpower or fantastic growth story, et cetera, et cetera. But I'm sure business leaders here very much realize that unless economic growth is accompanied by inclusive growth and also social growth, the other way social problems can greatly undermine the economic story. It's not only about economic growth issue, it's also that health is a precondition for economic growth but more than that good health is the goal of growth. Why do we need money if you don't need health if you are not going to achieve health? So health is not a means for economic growth, it's an end for economic growth. So how can we work together? My all experience in the field of health, so naturally I'm going to take examples from the same field but one let me start from a small thing, as I said earlier, this is the power bag. And there are many such innovations and products which if scaled up through social marketing or through other ways which corporates would know better than I do. But if they are scaled up and made available in large number where they are needed, that could very rapidly reduce. So this bag for example at the moment is put together by your own organization, is it? It's not as if one company is contributing to creating it. No, we buy products from various other companies, we assemble them and search looks for certain quality and search has good credibility so people really use it. So it can be done by others as well but we don't have any sort of patent on it. But my point is that this kind of power equipments which will empower people for self care, for community based care so they don't have to wait for doctors and hospitals to either arrive or where they would never reach. And so propagating this kind of products and solution in large number, that's where skills and resources of corporates could be enormously useful. There are other ways in which they can help just for example providing service to one mother, newborn and child in a village would cost in Indian terms about 500 rupees per year, 10 dollars per year. So one mother, one newborn, one child and then depending on your economic willingness to offer one could adopt thousands of mothers, newborns and children, not feeding them yourself but empower them, empower those village women to take care of mothers and newborn children in their own village. So I would say multiply empowerment and then of course one could go even further. We have recently proposed model of universal healthcare for India at a very small cost, 0.5% of per capita GDP. At that cost one can provide universal healthcare at the village level. Which would mean about 4 lakh rupees per village per year, 400,000 rupees per village per year. And you can provide from self care, health education, community based care and primary health care and early secondary care. Everything can be provided at such smaller cost. So corporates can really join hands with NGOs, with the social sector, with organizations like Savory Children, so that we can multiply this process unless we achieve women's empowerment, unless we achieve knowledge, health literacy and unless we achieve what I use the word from Indian languages, ROGS, which literally means our health in our own hands. So we need to empower people for that and that can only ensure that Indians are healthy, young people are healthy, that only can ensure economic growth. That's a very compelling vision. I'm assuming you're optimistic then in terms of now that the government has taken on and committed to this new roll out of the breakthroughs that you have pioneered, that there is now a vision in place for universal health coverage. You obviously have great ideas for how corporates can contribute to that. Are you optimistic that India is now going to get itself on the right path and perhaps catch up towards meeting its Millennium Development Goal to stop children dying before their fifth birthday? Well India is certainly not going to achieve Millennium Development Goal by the year 2015, but I guess as far as the child mortality goal is concerned, we'll achieve it by let's say about 2020. So we'll be five years late, which would mean two and a half million excessive child deaths, which is unfortunately sad. But then there are many, many positive things happening in India. So even if we'll be late for Millennium Development Goals, but one thing I find is that education has empowered Indian women, girls and women to a large extent. The self-help group movement, especially in the southern part of India, up to Maharashtra, not so much to the north of Maharashtra, but in southern India up to Maharashtra, self-help group movement. And what Chavi was saying today, this representation of women at the grassroots political institutions called Panchayatraj institutions, these are silent changes occurring at the grassroots. You won't find much in the media. There is not much corruption in it. So there are no scandals. So it's not really flashed in the national headlines. But these are the changes which are going to change India. Let me mention two more things. One is youth, power of youth. And India is more endowed than any developed country as far as the power of youth is concerned. And if at all India will become superpower, that's not my dream, but I'm saying if at all India becomes economic superpower, it will be only because of the youth and women. And that's why, look, you can see my beard is grey now. So I know maybe after a few years, Rani and I may or may not be able to work, but we must create a new generation of young social change makers. So six years ago, we started a new organisation called Nirmann. And Nirmann really is trying to sensitize young professionals' youth from Maharashtra state to the social realities, social challenges. And trying to empower them and also encourage them to take up this mission. And nearly 50 youth in different parts of Maharashtra have already started working in different parts. So one solution at one level or only in Gaduchul is not enough. We need to multiply youth and education. These are the multiplicatory power. Now I must mention in the end, but apart from what we read about poor governance and corruption in the politics, which are major, major threats for India's growth story, but something other disturbing emerging is non-communicable diseases. Indians are dying at a very fast rate at earlier age because of coronary heart disease, stroke, cancer, diabetes, et cetera, et cetera. One reason is our unhealthy lifestyle and another reason is consumption of tobacco. On a very large number, a small district Gaduchuloli with a population of only 1 million consumes 730 million rupees worth of tobacco every year. Look at the amount of economic loss plus the decisions that would create. So the changing lifestyle is a major threat to the health story of India. So we need to struggle on that front, but I'm very optimistic, especially because of women and youth of India. That's wonderful to hear you present women and youth as the opportunity for India in terms of its growth and its future and I think I would certainly agree with that and I think it's been coming through slowly but hopefully more powerfully in the sessions at the World Economic Forum more generally here in India. That's been really fascinating. You've covered a very large amount of ground in a small amount of time. If there was just one thing that you wanted to leave with us, what would that be? Well, when similar question was asked to Mahatma Gandhi, I'm just going to echo his words. So it's not my message. It's coming from him. And he said, be the change yourself that you want to see in the world. So all of us, whether social workers like me or corporates, must live the life that we wish we want the future to become reality and that reality starts happening. Wonderful. Thank you very much indeed, Dr Bang. That's been a pleasure to be with you. Thank you, yes ma'am. Thank you everybody.


What shoes are you rocking and how much are they worth? When I'm rocking right now, Shattered Backboards. I would say right around like 15. I got them for a steal, I fit eight. Shee! What shoes are you wearing right now and how much are they worth? These are the Desert or Jordan 1 Lowe's. I don't know honestly, I'm gonna say like 300 bucks. What are you rocking right now and how much do they cost?  Travis Scott, the Mocha Lowe's. I think I got these for like six or 700 bucks. What are they worth? Worth, probably brand new, probably like 17, 1800 I would say.


Nature and wildlife are what makes many countries so special. At the same time, animals in a thriving environment are vital to the economy and to people's livelihoods. And that's the dilemma. As population numbers increase and agricultural land expands, how can people and wildlife exist together? In Kenya, for example, the places often affected the most are the rural areas that are so important for wildlife tourism. Animals, particularly elephants, are increasingly sharing the space where pastoralist farmers and their families live. The result is a clash of interests, with wildlife causing injury and physical damage to buildings and to crops. In return, people's anger and frustration leads to elephant deaths. And it's a problem for Sri Lanka too. Human-elephant conflict is a huge socioeconomic issue in Sri Lanka purely because of the human population pressure and the expansion of agricultural lands. Therefore, human-elephant conflict has escalated in the past several years, especially in the past decade. 44 percent of Sri Lanka has elephants and humans occupying the same space outside protected spaces. On average, the past few years, we've been having about 400 elephant mortalities and about 100 human mortalities, which are the highest numbers recorded for conflict globally. This competition for the same space is not going to go away. A solution must be found, which works for humans and for wildlife. That's where private insurance comes in, a scheme that covers the cost of farmers' losses and enables them to get on with their work, while allowing elephants and other animals to seek what they need to survive. Conservation organizations and governments for whom human wildlife conflict is an issue must start to think how they could work with insurance companies to resolve the problem. These companies have specialist knowledge of managing risk-based schemes and are skilled in reducing administrative costs, leveraging technology, making payments efficiently and setting up anti-fraud measures. In Kenya, the government is exploring whether it could hand over its wildlife compensation scheme to the private insurance sector to manage. In Sri Lanka, they are testing the idea too. This approach being piloted in Kenya and Sri Lanka to allow people and animals to thrive in close proximity and for nature to be conserved could be an important way forward. The government wildlife agencies and conservation NGOs in other countries could implement private insurance as well to promote the coexistence of humans and wildlife.


Thank you for the organizers for the opportunity to present this work here. I'm going to present two pieces of work today. The first is brand new. It will come out as an IMF working paper within the week or two. And it is empirical work on the future of the world oil market. And the second part will be about a slight extension of the wheel work that I presented here in October last year that's using the IMF's global economic model to think about different scenarios for the future of the world economy. Here's the usual disclaimer. So by way of introduction, when it comes to predicting future oil prices, conventional models have great difficulties with that. And when I say conventional models, I mean econometric models that are out there and have tried to forecast oil prices, also surveys of expectations, futures markets, they cannot consistently beat a random walk. And a random walk says that the best predictor of tomorrow's oil price is today's oil price. So that's not a very good forecasting performance. And part of the reason for that is that econometric models tend to pay very little attention to oil supply. That has two problems. First, they cannot capture temporary oil shocks very well. But more importantly, especially at the current juncture, they cannot predict an upward trend in the oil price because these models tend to be demand-based and mean-reverting models that will always predict that the oil price goes back to some level and to have a trend that persists over a decade, which is almost what we have by now, is hard to explain for such a model. The alternative is to take the geological limits to the oil supply more seriously than these models do. And then the oil supply constraints are front and center for determining the future of oil production. But then in that case, there's no role for oil prices. And as I will show you, this is also not consistent with recent data. So what is needed is something that's in between. And the model that I will present in this paper combines both approaches, where geological limits will turn out to be very important to explain the upward trend in oil prices that we're in the middle of. But demand shocks through higher prices, by causing higher prices, can increase production as well. And that is also something that we have observed, as I will show you. Because this is a statistical model that we evaluate with state-of-the-art techniques, we can then say something about the uncertainty about shocks and also about key parameters that we can then directly evaluate. A few words about historical forecasts of world oil production. The point of the exercise is I will show you that the mainstream view has tended to overestimate where oil production is going. The peak oil view has tended to slightly underestimate where it's going. And these have been coming together like this. They're still very far apart, but they have been coming together. And so here are the EIA's projections made between 2001 and 2010. And it's a bit hard to see because there's so many of them, but it's an almost continuous downward revision year by year by year. These are projections out to 2020 with different starting points. These are the different years in which the projections were made, an almost continuous revision by a very large amount of more than 25 million barrels a day in 2020. So these are very large numbers. This started in 2003. What happened in 2003? In 2003, the official OPEC spare capacity took a nosedive. This was in early 2000. This was around the time of the Iraq War. And that triggered the beginning of this upward spike in oil prices that lasted all the way to the beginning of the Great Recession. It then dropped. And this was because there was demand destruction.  But now look at what's happening. Spare capacity is trending down again. And oil prices are trending up again. And so that's the picture as far as the official view is concerned. Here are three of Colin Campbell's forecasts. It's a slightly different aggregate of oil. It's regular conventional oil. These are the actuals again. And these three lines are three different forecasts made between 2003 and 2010. And again, until 2020. And there's a slight upward drift in those forecasts as well. Not as well in those forecasts. So this goes the other way from the official view. Now Colin Campbell's work is very much bottom up looking at individual oil fields with a lot of engineering knowledge. There's another approach that proponents of the peak oil view have used. That's a curve fitting, the DeFe model. That was done in 2005 with data up till 2003, predicting this curve here and this production profile here for future oil production. What happened? Because we just saw the data in 2003. What happened from that year onwards is that oil prices jumped up. And look what happened. There's significant deviations from the phase forecasts from that line that have lasted to the present day. But these deviations, nevertheless, have not led us to resume the historic growth rates. They have kept us on a plateau. So we want something in the middle of this. And so we built a model that I do not have time to go into great detail about. The only thing that I want to say is that we basically built a model with demand and supply curves for the world oil market where the demand curve specification is very conventional. And then there's another set of equations for potential GDP and the output gap, excess demand. All that is conventional. The supply curve is not in that it combines the DeFe specification of the peak oil view, which is called habit linearization, with price sensitivity of oil supply, where higher prices can make the oil supply go up over time. And that is basically the combination of both views. And have a look at what that does to the forecast accuracy of our model. And so here the table, I'm sorry, it's a little bit small. I should have made this bigger. But I'll tell you what's happening in words. These are out of sample forecasts for our model versus the closest competitor out there. And these are one year, two year, up to five year ahead forecasts. And what is shown here is the root mean square error. So when those numbers are large, it means the forecast is bad, relatively speaking. And what we're seeing is that for the real price of oil, our model does better than the random walk at any horizon. And especially at longer horizons, the forecast error is a quarter of the random walk. And as I told you earlier, the random walk is something that conventional models have difficulty beating. For oil production, these are the EIA forecast, root mean square errors. And these are our models. And our models are about half of what the EIA's forecast errors are. And so, again, on oil production, the model does very much better. I'm not going to go into the GDP numbers. Here's a little story. This is a decomposition of history where we're saying, let's start in 2002. Let's run our model forward from that point onwards. And this red line is running it forward without any shocks. And this blue line is running it forward with the estimated shocks that we estimated. We're using Bayesian non-linear estimation techniques, high-tech stuff. And this basically is the model with all shocks that fits the actual evolution of oil prices. And these blue lines and these other subplots decompose the contribution of different shocks to what happened to overall oil price deviations from this trend. Now, the critical thing is that this trend, even without any shocks, is up. And that is because of the Hubbard feature in the supply curve, meaning that even if no oil demand or oil supply shocks hit this economy, on the basis of estimates up to 2002, this model would have predicted an upward drift in oil price because of this peaking nature of the supply curve. But then, there were significant deviations. And where did they come from? Well, there were oil demand shocks in the early part of the 2000s as the economy was doing well and also output gap shocks a little bit towards the later part of that period, but mostly oil demand shocks as the world economy was booming. But then from 2005 to 2008 and also more recently, the last one or two years, oil supply shocks explain a lot of the action in the actual oil price relative to the trend. And that, what happened in 2005, we reached the plateau in world oil production. And we've been on it ever since. And so this is beginning to have a big additional effect. And output gap shocks, the great recession led to demand destruction. And that is largely explained by output gap shocks. Let me skip over this one in the interest of time. So that was forecast, out of sample forecast in history, now what we're doing is, let's take history as given and let's say, what does the future hold? So we're saying, we're in 2011, we have estimated this model up to here with uncertainty about shocks and parameters, et cetera. What does the future hold? Well, the point forecast of our model over the next, this is actually nine years, not 10 years, but roughly 10 years, has output growth of roughly 0.9% per annum. And if you look at the very latest EIA forecast, it's in the ballpark. That's more or less what they project. But I want you to also notice that there are very wide error bands around this. They reflect our uncertainty about what are going to be ultimately recoverable reserves and elasticity of demand and supply. And the flat output path for the next 10 years is within the 90% confidence interval. But let's not concentrate on that for now. Let's focus on the next one, which tells us, okay, what oil prices are going to be necessary to make this happen, to make this 0.9% output increase happen. What the model tells us, again, with great uncertainty because there's so much we do not know about the oil market, but our best guess is that the real oil price has to nearly double over the next decade. It's a little less than double on the point forecast, but it is in the ballpark of having to nearly double. And this is because we're always working against this geological constraint now that wants to drive production down. And if demand is to be satisfied through supply, it can only happen through higher prices that have to be quite significant. And depending on if you have, for example, very much lower elasticities, you would move to this part of the confidence bands to even higher oil prices. And given the historic performance of our model in forecasting oil prices out of sample, this is something that we are taking somewhat seriously. Conclusions, the objective was to evaluate a model that encompasses two diametrically opposite views of the oil market, the resource constraint view, and the view that prices are ultimately decisive, which is the economist view. The model performance, in terms of history, our decomposition into trends and shocks is very plausible. It tells a story that intuitively sounds right. For forecasting, we have a far better performance than competing models. What do the forecasts say? First of all, the EIA's latest forecast of 0.9% annual supply growth may be feasible, but the real oil prices would have to nearly double over the next decade, but that's subject to very large parameter uncertainty. And then there's one very important thing here. The effects on GDP are here in this model, and I didn't discuss them very much. There are negative effects of higher oil prices on GDP, but they're not enormous. They don't make the economy collapse. And that's based on historical data, where it's kind of hard to argue that that has ever been the case. There have been temporary blips, but to say, we have very little to go on in the data that would tell us a very persistent supply constraint would lead to a big collapse in GDP. We don't know that, right? And our model tells us the effects on GDP on the basis of the data are not too dramatic, but we think that there may be non-linear effects on GDP once oil prices breach a certain pain barrier, but we don't know what that is. And so our future research will be very much on that question. Now, that's where I'm connecting to the WIO that came out last year, and I'm going to present a succinct version of the simulations that were in there, because what we're doing there is we're basically using a model laboratory style environment of our global economic model that we're always using for policy analysis, not for forecasting, but for policy analysis, scenario analysis, et cetera, of which I am responsible for the theoretical development and the latest theoretical development is to put oil in there. And so we need to understand two questions about oil. First, what is the outlook for production and prices? And I just talked about that, and there's more work to be done here, but we have at least some idea now. The other question concerns GDP, and I talked about that at the end of the previous paper, how might oil scarcity effect output? The WIO gave some very tentative answers, but we feel that we'll need a lot more work. So a brief overview of the GMO, the IMF oil version. GMF is a choice theoretic dynamic business cycle model. As I said, it's very frequently used at the IMF for all sorts of purposes. I only want to talk about how the specification that I'm going to use today differs from a version without oil. We have an oil demand function where there is a very low short run and long run elasticity of substitution between oil and other factors of production, a low cost share, because that's what the data say. This is also what the data say. The output contribution of oil is equal to the cost share in the baseline, but we then experiment with a version where oil makes actually a very much bigger contribution to output than its cost share would indicate. And there is a justifiable, academically justifiable specification of aggregate production in the model that makes sense of that assumption. For oil supply, we treat oil as an exhaustible resource whereby it's mostly an exogenous endowment, but there is a price elasticity of supply of 0.03, so that's low. The price response is low. We have five scenarios. First one is reduction in oil output growth by 1% per annum relative to trend. This would be going from 1.8% per annum to 0.8%. The alternative one is to have these larger output contributions of oil. So if I don't have enough oil, it makes much more difference to how much output I can produce. Alternative two is to have a reduction in oil output growth by 3.8% per annum, which would take us to an absolute decline of 2% per annum, which is sort of like the more pessimistic peak oil scenarios that I've seen are more or less that order of magnitude. Then, and this is the wheel up to here, and just for the sake of argument and sort of to drive home what's at stake, for this presentation, just combine alternative one and two and to go through what the model tells us what would happen there. And then I've also combined this alternative three with a zero elasticity of substitution between oil and other factors of production, just to have an extreme case to illustrate what would happen. Now, so here we have all these scenarios in one graph and from the baseline to it gets worse as I go down this list. And what we have here is GDP absorption and current account for oil exporters for the rest of the world. Here we have the oil supply, the price of oil and the real interest rate. And so first of all, the output effects range from 0.2% per annum less growth to over 2% per annum in the worst case scenario. But these scenarios are really much worse than what's in the wheel. The worst one that was in the wheel had a 0.75%, I believe roughly, annual loss of growth over these 20 years in the projection. So that's one thing. Current account effects in the oil importing countries for less than 2% of GDP in the baseline to 10% of GDP in the somewhat crazy last scenario that I'm putting out here. So I don't want you to take that too seriously. This is just sort of playing with the model and say, if there really wasn't a substitution possibility between oil and other factors of production, how bad could it get? And next, the price of oil. The baseline for the price of oil, which is that blue line, is actually relatively close to what I've just shown you in that empirical model. 100% after 10 years and another 100% after 20 years. For different reasons, the models are not strictly comparable, but it sort of gives me comfort that I might be in the ballpark with the baseline. But those are already very large numbers for the increase in oil price. This green dotted line is what we also had in the wheel, 800% after 20 years. That is a number that is so large that I think, in my mind, there is no doubt that there must be some nonlinearities for output, but the model doesn't have those nonlinearities. So the model just basically says, well, there's an output effect, yes, but most of the effect of oil scarcity is sky-high prices. If you had a link from these sky-high prices to more of an effect on output, then you would get demand destruction, destruction of demand for oil on a larger scale. The final point, real interest rate, don't even look at the bottom two lines, they're just too crazy. What would happen is when this large increase in revenues to oil exporters happens, we assume in the model that they accumulate that in an oil fund, that they don't spend right away. This would lead to a very large increase in world savings, and that increase in world savings for given world investment would drive down the world real interest rate to a point where the real interest rate would become so low that nominal interest rates would have to sink too close to zero, meaning monetary policy would be constrained by the zero lower bound on normal interest rate. So apart from leading to all sorts of current account imbalances, it would also lead to problems for monetary policy if the worst case scenarios were to happen. So the conclusion, the oil price effect in the benchmark is similar to our empirical paper. Output and current account effects in the benchmark are modest. The alternatives introduce assumptions that could lead to much larger effects, but these are at this point, they are just sort of, we're just playing in a laboratory style model environment and we need to link that to data more and that's what we're starting to work on. The output effects get larger but are still not enormous but the oil price effects are enormous under those alternative assumption and the key question just like at the end of the previous paper is at what level does the output response to higher oil prices become non-linear in the real world because in the model it is approximately linear and that's all I have. Thank you. Thank you. Thank you.


In the other semifinal matchup, Duluth Marshall taking on Aitken, early on gobblers on the far end, McKenna McDonald on the low post, muscles are way to two points, Hilltoppers respond in transition, Deja Starks for two, Aitken answers, Kasia Davies turn around fade away is good, but here come the Hilltoppers pass to Starks, no stopping that, Aitken's season comes to an end tonight with a 78-64 loss. If you enjoyed this segment of Lakeland News, please consider making a tax-deductible contribution to Lakeland PBS.