So, hello everyone again, I forgot to introduce myself before, I am Monica Jain and I am a professor for the Center for Urban Science and Engineering at the Indian Institute of Technology Bombay. So, I will be giving you a macro level overview of buildings and energy in India and what we mean by green buildings. So, I will talk to you about what is the big picture, why are we talking about energy, why are we talking about buildings, what do we mean by green buildings and then sort of wrapping up into the larger context of urban sustainability. So, why are we talking about energy? There are sort of threefold reasons to that.  So, use of fossil fuel energy leads to emissions of greenhouses which in turn are responsible for the global warming, which gives rise to unpredictable weather conditions, floods, droughts, heat waves, hurricanes. So, all kinds of weather that is very unpredictable and can be very harmful. Diminishing resources, we know that the mother earth do not have a infinite amount of fossil fuel resources that we are using. So, we need to have a deep thought regarding how to manage the increasing energy demands of the future. And the third aspect is really urbanization and it applies very much to India because we are in an increasing population and a lot of people are migrating to the urban areas for job opportunities and for a better quality of life. So, these are, this is kind of a big picture, why we are talking about energy. So, just a very brief overview of what we mean by global warming, the global solar radiation that reaches the earth surface, some of it is reflected back by the, by this layer of greenhouse gases and some is absorbed by the earth surface. And I am giving this as a very sort of a simple explanation, but when the amount of greenhouse gases increase the solar radiation that is trapped on the earth surface increases, that in turn gives rise to the temperature, the overall temperature of the surface and that has been responsible for melting of the ice caps at the poles and increasing the sea level and that in turn is responsible for the unpredictable weather events. So, that in a nutshell. So, and all of this is the result of basically after industrialization this has increased and this is a result of the increase in the fossil fuel use. So, this is the chart that shows the greenhouse gas emissions, what are the different kinds of gases that when we say greenhouse gases and carbon dioxide forms the biggest chunk of this greenhouse gases and if you see in blue almost 60 percent of the greenhouse of the carbon dioxide emissions. Carbon emissions are due to the use of fossil fuels and by fossil fuels we mean coal, petroleum, natural gas things like that. Here are the different sources that produce these greenhouse gas emissions and so that includes agriculture, forestry, industry, but I would like you to focus on these three sort of these three sectors where energy supply transport and buildings form almost half of the greenhouse gas emissions that are emitted through these three sectors and this is basically where very directly correlated to the human beings and the increase in population and the buildings that are coming up. So, and this is the distribution of these emissions by country and India actually comes in the top four or five when you compare the entire world, but still it is one fourth of what China produces, but we, but and mostly this is because of the supply of power is through use of coal, but although at this point or in 2008 this was the distribution we are rapidly urbanizing. So, this is a chart that shows in red it shows the urban population increase and this is 2050. So, by 2050 if you consider the world 80 percent of the people will be living in urban areas currently in India it is around 30 percent that are living in urban areas, but in the next few decades the increase in Asia will be the maximum in terms of the immigration from rural areas to urban areas and India itself will be adding around 500 million people in the next few, next three to four decades which is equivalent to hundreds of tier two cities or the we are in Mumbai. So, I compared it to Mumbai 38 Mumbai cities. So, that is what does that mean that means that you are adding lot of cars to the roads which in turn means increasing the amount of fuel that is being used and greenhouse gas emissions. There are there is rapidly increasing construction sector that is booming. So, you are adding buildings you are using the building materials and air conditioning loads and other kinds of energy consumption is being added. So, the in future electricity consumption in India is expected to rise to around 2000 to 80 billion kilowatt hour in 2020's and it will double in the next 10 years. So, this is this is a cause for concern and that is why we are talking about energy and buildings in India particularly. This chart shows you the energy consumption in buildings in India and you see from 70's to 2010 it has been rising continuously and there is there will be a sharp increase when we go in the next few years because of the urbanizing population. And if you see in 70's 15 percent of the electrical consumption was attributed to the buildings in 2010 to 11 it is more than it is almost one third which is equivalent to the industrial sector which includes the power generation through coal. And among this 34 percent 28 percent is attributed to commercial and 72 percent is attributed to residential. So, this is again an important number where more than three quarters of the energy or around three quarters of the energy is attributed to housing. And so, again that becomes an important number that when we are thinking about accommodating the increase in population and increasing the number of households we have to consider what kind of energy efficiency measures we can incorporate. This chart I thought is an interesting chart this is mapping the quality of life of people in different countries with the energy consumption per capita. So, in the green you see are the countries that have a very low quality of life and the quality of life is measured through health through GDP and various other factors. The red is the average quality of life and the blue is mostly the developed nations where the quality of life is the highest. So, the blue line shows you that this is kind of the point where this much energy is needed to have a quality of life that is a improved quality of life. And India is somewhere here where 540 kilogram of emissions are emitted per person. So, that is the amount of energy and we have to we will be reaching there if we want to be a nation with a good quality of life. So, this there is a direct correlation between the quality of life and energy consumption. So, this is also something that we have to keep in mind when we think about improvement of quality life of the humans in the country. So, let us come to the sort of the details of where the energy is used in buildings. So, the first part is the building operations throughout the life of the building you are using your lights, your fans, air conditioning, coolers, refrigeration. Now, there is an increase in electronic equipments that we use and so many different things. So, this is a division for residential and commercial buildings. And if you notice that most of the big chunk of the electrical electricity consumption is by lighting and cooling both in the residential buildings and commercial buildings, the lighting forms almost 60 percent of the part and the rest of it is the air conditioning load. So, these are the two lighting and cooling loads contribute to maximum to the energy consumption of buildings and hence this these are the areas that need great focus in terms of how we can conserve energy and think about alternatives to provide a comfortable environment in buildings. And today one-third of the energy consumption is attributed to buildings, 20 percent to transportation. So, both the buildings and transportation is related to the urbanizing population and here in the picture I show the kind of buildings that are being built usually there are glass facades. If you see the shopping malls or the offices that are being built are usually glass facades and designs have been copied directly from the western countries which have much colder climate. And in India most of the places you would not the climate only in the north is colder. So, you have to be climate sensitive when the buildings are being designed and there are multiple factors that affect the efficiency and comfort of the buildings. So, here I list a few of them, building envelope and I will talk about some of them in a little more detail. Building envelope is basically the outer facade of the building that separates the external weather from the inside conditions. Building materials what kind of materials we use are they sustainable locally available. Energy harvesting, thinking about alternative ways in which we can capture energy. So, solar energy, wind energy and also using the waste that is produced as a alternative source of energy. And then the last picture shows that you have to the climate although there are 5 climatic regions in India, but the micro climate which is what surrounds a particular area. If you have a lake or trees around you the you will feel the difference in climate as opposed to when you are in a situation where is where there are buildings in traffic. So, the micro climate has to be considered while designing a building and how the building orientation and windows and other things have to be placed. So, again as I mentioned building envelope would include external walls, windows, skylights, external doors, roofs, floors, foundation systems. So, any anything that is interacting with the external climate and these are the elements from which you can either lose heat if you are heating your inside rooms or you can gain heat through the solar radiation. So, this has to be designed in a way that it basically creates a comfortable climate in terms of temperature, humidity, ventilation and if that can be achieved through passive means or minimum artificial building systems. Then comes the building materials. So, we talked about the building operations which is what you are using throughout the life of the building, the building envelope and then comes the building materials. So, it has when we talk about building materials we have to consider from the beginning where is the raw material coming from what kind of energy is being used in manufacturing of that material extraction, processing, packaging, shipping. Then the energy used while construction and installation of those materials and then what happens to those materials after the life of the building say 50, 60 or 100 years life of the building. So, the best scenario would be if the building material can be reused to build another building which will decrease the amount of energy that is being used. The second best would be if you are able to recycle the material and create a new material for building the building, but if it goes to waste then there is no recovery of energy. So, those are also the aspects that you have to keep in mind when you are thinking about what material to use and this chart shows you a general overview of some of the common construction materials that are used and what is the embodied energy. So, embodied energy is the sum of all the energy that is required to produce the materials. So, the phase one that we saw in the last diagram. So, steel has the highest embodied energy followed by cement. If you see the common materials used in India concrete and bricks, but this is giving you a kilogram carbon emissions per ton. So, the amount of material that is used concrete and bricks actually is a lot more than steel. So, there is a high component of embodied energy in the materials that we are using today in the building industry. And here this shows how transportation adds to the embodied energy of these materials. So, this is this was a study done in UK and so that is why if UK is getting the natural stone from the nearby places and the embodied energies is less, whereas if it is getting it from China then the transportation element adds a lot more to the building material energy. So, transportation of materials. So, we should try to see if we can get locally available materials which will make our buildings more sustainable. So, that was sort of a background leading to how do we want to define green buildings and this is this is the overall picture if we can we talked about the building operations which is using different kind of equipments lighting etcetera throughout the building life. The building materials that we choose which incorporates both the embodied energy and the local availability and the design of the building. So, if we can optimize on all the three and make buildings that are context and climate sensitive that is how we will define green buildings. The buildings that can conserve energy, water use and reduce waste through the life cycle of the building. The buildings that can use passive resources for building operations and the most important one is that it can provide health and comfort while optimizing the amount of energy and water that is being used in the buildings. Some of the ingredients and benefits of green buildings. So, by designing your envelope you can save energy you can reduce the amount of utility bills, the electricity bills that you get in the water bills. You can also produce energy by installing solar photovoltaic solar thermal or wind turbines in the buildings save water conserving water through efficient faucets and through rain water harvesting which is capturing the rain water and using it for different purposes. You can plant the areas on the roof or around the building so that the rain water can be captured. You can produce food basically you can grow vegetables and plants in your building. So, all of these features combined define what green buildings could be and this not only provides savings and health and comfort to the individuals who are in living in the buildings. It also reduces the burden on the municipal infrastructure like the electrical grid or the sewer system because you are not drawing more energy or producing more waste to be that burdens the system. And this also brings you closer to the nature that you have greenery around you and it improves the biodiversity around the buildings and improves the air quality. So, that is how we define the green buildings and that was more in a subjective manner, but there are evaluation systems that have been developed to evaluate how the buildings perform and what can we call a green building and there are different kinds of ratings that are given to these buildings and the performance is evaluated during the design construction and operation of these buildings. So, I have listed some of these systems that are in place and I would if you are interested you can read more about these systems which will give you a deeper insight into what kind of factors are considered when evaluating the building. So, LEED which is leadership in energy and environment design was developed in the US and that has been adopted in India by the IGBC Indian Green Building Council. Other things like green, green globes, Caspi. So, there are lots of these systems where each country adapts it to their own context. GRIHA is a system that assesses the habitat and then there are other systems which actually are much more rigorous and intensively living building challenge and life cycle analysis. So, if you are interested you can look these up and understand more about it and as I mentioned in the introduction if you want to learn more about any of these aspects please give feedback to us through the model. So, just going back to just wrapping up and sort of giving a bigger picture. So, although there are these rating systems which will give rating of say silver, gold or platinum, but if you just consider the building. So, here is an example of a building that has all the green features that we talked about. It has solar PV, it has a good envelope energy conservation everything, but if everyone drives to this building, if everyone uses the cars then they are adding a lot to the carbon emissions and if you look in a larger context this is not really a green building. So, we have to think about a larger context and that means the urban sustainability. So, it is and I define it as a network of buildings and services and services would include roads, water services, energy transmission, access to education and health that can be arranged in a way that can improve the quality of life of people. And I want to end with this that what do people really need if you think about it in their daily lives. They want access to all the daily needs like grocery, workplace, going to school, amenities like open spaces, parks, recreation and necessary services like water, food, electricity and then they want these access with improved health safety and aesthetics and which leads to good quality of life. So, that is all I wanted to say. So, you focus on the building part of it, how can you conserve energy and then think about the larger context when your building sits. Thank you.


Apple also like to ask you situational-based questions that specific to your past job or your future job. They're going to ask you questions like this. Question number 5. Expand the time when you have to do X. Question number 6. What means through your resume? Question number 7. How many projects have you worked on? Question number 8. What inspire you to reach your full potential? Question number 9. Why are you leaving your current job? Question number 10. Think about yourself in 30 seconds. And those questions look like it's just a storytelling question or general overview of your past experience. However, once you give a specific example, they like to dive deeper, really deep. For example, when you give an overview of a different project you work on, it's going to pick one of the most difficult projects and dive in and have you tell more about specific capabilities you'll be used in your new job and how it's going to be translated for your past job.


Sound off for Chesterfield. Chesterfield, the only cigarette in America to give you premium quality in both regular and king size, brings you dragnet. Ladies and gentlemen, the story you are about to hear is true. The names have been changed to protect the innocent.  You're assigned a forgery detail. A check forger has been hitting the merchants in your city. From the MO she uses, you know she's an expert. You've got a description. Your job? Get her. There's only one premium quality cigarette in America available in both regular and king size, and that is Chesterfield. Premium quality in a cigarette means the world's best tobaccos, the best ingredients, the best cigarette paper. Only Chesterfield gives you this premium quality in both popular sizes. King size Chesterfield contains tobaccos of better quality and higher price than any other king size cigarette. That's certainly important to every king size smoker. Of course it's the same fine tobacco as in regular Chesterfield. There is absolutely no difference except that king size Chesterfield is larger. It contains so much more of these premium quality tobaccos that you get more than a fifth longer smoke from king size Chesterfield. Yes, the modern way to sell cigarettes is the Chesterfield way. Premium quality, both regular and king size. And either way you like them. Chesterfields are much milder. Chesterfield is best for you. Dragnet, the documented drama of an actual crime. For the next 30 minutes in cooperation with the Los Angeles Police Department, you will travel step by step on the side of the law through an actual case transcribed from official police files. From beginning to end, from crime to punishment, Dragnet is the story of your police force in action. It was Wednesday, February 6th. It was cool in Los Angeles. We were working the day watch out of forgery detail. My partner, Frank Smith, the boss is Captain Welch, my name's Friday. I was on my way back from the forgery office and it was 10, 22 a.m. when I got to the mug room. I'm sure about it, officer. If I ever see that woman again, I'll know her. Won't you have any doubt about it? I'll know her. Yes, ma'am. Now if you'll just look through this book, please. Have you seen anyone who might be the woman, Ms. Parkinson? No, not yet, Sergeant. But if she's got her picture in here, I'll find it for you. Never forget that face. Those weak little kind. They sort of reminded me of my mother rest or so. I think that's why I cast a check for her. I never would have done it if there hadn't been something like that. Yes, ma'am. I wonder if you'd mind running over it again for us. It might have been something you forgot, maybe? No, no, no. I wouldn't forget anything about her, but I can tell you about it if you'd like. All right, fine, Ms. Parkinson. If you just start at the beginning again. Fine. Would you mind calling me, Ethel? I don't much care for formality. Feel better when people call me by my given name. Yes, ma'am. If you go right ahead, please. Well, this morning's when I found out about it. I liked to keel right over when the check came back from the bank. I opened up the other mail. Most different people want to sell me things for the store and there it was. Letter from the bank with a check inside. Staple to one of those forms. You know the kind they just check for the pencil? Uh-huh. Well, like I said, there it was. The place that was checked said the account was unknown. Well, you can just bet I got on the phone and called the bank people. Yes, ma'am. I understand. I told them they'd made some sort of mistake, that they'd better said it right. I was so sure that you wouldn't do a thing like this. Well, you know how banks are. They said they'd check it for me and I waited on the phone while they did. And they said it wasn't any mistake. Well, you can just bet that I was hopping mad. Yeah, well, what kind of identification did the woman use to get you to cash the check? Well, she had several letters from her son. At least that's who she said they were from. I bet she hasn't even got a son. Well, sir, I bet she hasn't. Well, do you usually cash checks for that little identification? No, I don't, as a rule. I usually ask for a driver's license and a social security card. I figure that if a person's got one of those, that means that he's working. Figures that the check is good. Well, that's not always true, you know, ma'am. Don't I know it now? You just bet I do. Last time I cashed a check for anyone that I haven't known for ten years. Had you seen this woman around your store before this time? I mean, try to think about that. The shop isn't very big, but we do a pretty good business. Sometimes there are several people waiting.  Yes, ma'am. It seems to me I've seen her in this store before, but when I stop and really think about it, I'm not too sure. You know how that is? Yes, ma'am, I do. When you boil it right down, I don't think I have seen her before. She just had one of those faces that you figure sure you know. Looks like such a lovely person. I see. About how old do you figure she was, ma'am? Like I said, I guess about 62, maybe a little older. Might have been 65. Not much over that, though. Such pretty hair. Pure white had it fixed in a real soft wave over her forehead. Old-fashioned kind of. Wart and a bun, you know. Bun had the hair all rolled up and then pinned up back here. Back of her neck. It was white, you see. The hair was white. Yes. Looks so nice to see a woman act and look her age. So many of them tried to look younger, you know. Yes, ma'am. How about her clothes?  Looked kind of like it might have been cashmere. Looked real nice. Little spring gloves and all. You say she was a small woman. Is that right? Yes, she was little. She stood real straight, you know, shoulders back, but she was a little one, not more than five foot one or maybe two. Would she be slight or heavy? Big pardon? Well, how much would you say she weighed? Maybe a hundred pounds. Say she wasn't much heavier than that. No, sir, a hundred pounds. Was there anything unusual about her? Anything that might make her stand out? No, no, I don't think so. Maybe it was the perfume. Ma'am. The perfume, you know, how you kind of expect a little old lady to wear something kind of mild like violet, maybe. Some light. Yes, ma'am. Well, she had a real heavy perfume on. It smelled kind of like a French scent. Real heavy, like I said. It was one thing I couldn't figure out. What's that, ma'am? Well, she did have nice clothes and all, but all in all she didn't look like she had a lot of money. Just moderate, you know? Mm-hmm. Well, that perfume must have been expensive. Must have cost a lot. Well, I guess she's making enough to afford it, ma'am. 10.34 a.m. Mrs. Parkinson continued to look through the mug books. She was unable to identify the woman who had passed the bad check. The merchants of the city had been victimized for the past three weeks by a forger. All of them described her as a kindly old lady using letters from her son in the East as identification.  The stats office had made several runs on the M.O. and all leads furnished by them had been checked out, but they let us know where. We'd obtained copies of the forged checks and they'd been processed by Don Meyer in handwriting, but he'd been unable to offer us any new information. The names on each of the checks were different. We'd checked each of them out, but the leads went nowhere. All of the stores in the central area had been alerted. Descriptions had been distributed to the neighborhood merchants, but the check passing continued. We checked with our informants, but they failed to come up with any information. Two weeks passed. The woman hit 12 more times. Her take was estimated to be over $2,500. The checks she passed were always for the same amount, $50. When it seemed necessary, she would purchase merchandise in order to cash the check. The articles she chose were in a price range so that the store owner would often cash the check rather than lose the sale. On February 21st, 8.34 a.m., Frank and I got back to the office. I get it. Forgery Friday. Yeah. All right, where? How soon? All right, now we'll see you there. What is it? Harry Allinson. Informant? Yeah, says he wants to see us right away. Yeah. Says he knows the woman we're looking for. The working detective knows that he's usually only as good as his informants. Quite often, when all other means of bringing a case to a successful conclusion have failed, the only thing that will break it is information supplied by an informant. A detective will protect his informant. For as long as the informant can operate, the detective is assured of a steady flow of information. 9.45 a.m., Frank and I drove over to the coffee shop at the corner of Crawford and Spring Street. Harry Allinson wasn't there when we arrived. We sat down in order to cup of coffee. Oh, that's good and hot. There it is. Pass the sugar, will you, Joe? Yeah. There you go. Thanks. Okay. I wonder where Allinson is. What time do you say he'd be here? 9.45. Well, it's only a couple of minutes after that. Now he'll be here. I wonder how righty his story is. What did he tell you on the phone? Nothing, just that he knew what we were looking for. He said if we'd meet him here, he'd fill us in. There he is. Oh, yeah. All righty. Harry? Sit down. Yeah. Sorry, I'm late. Got hung up on traffic.  No, a Mrs. Street car. Had to wait for another. Say, you guys had breakfast yet? Yeah, we did a little earlier. You mind if I have something to eat? Oh, go ahead. Where's your waitress? Well, she was here a minute ago. I don't see her now. I'll go get her myself. I'm sure you guys don't want anything to eat. No, no, thanks. Just the same, Harry. Okay. Be right back. Well, here we go again, Joe. Yep. Last time we met him, his meal cost $250. How much dough you got on you? Oh, I got a couple of bucks. How are you fixed? Well, not much better. Let's hope he doesn't order too much stuff.  No, no thanks, Harry. I'll be up in a minute. All right. How about this information, Harry, about the paper hanger? Oh, yeah. Funny the way I got it. That right? Yeah. I was up in Jack's bar last night. You know, just having a beer, shooting the breeze. All of a sudden, this old girl comes into the place. Had to set everybody back on their heels. It looks so nice. Yeah, go ahead. Well, she slides up on one of the stools and orders a drink. Even Jack was taken in. Changed his apron and all. Anyway, she climbs up on the stool and orders some sherry. Made a big thing of it. What do you mean? Well, Jack started to pour some of it for her and she stopped him. She said that she wanted California sherry. She said that she didn't want any of that imported stuff. She said her family was one of the first ones in the state and that she believed in using homegrown products. She was kind of cute about it. Real little woman perched up on that stool. Looked a little like a cartoon. You know, the ones with the little old lady guzzling and martini. Yeah. Oh, say, hold on a minute, will you? My food's ready. Be right back. OK, Harry. How do you like that guy? It takes him five hours to get a point. Oh, there's nothing you can do about it, Frank. He's got to tell it his way. I suppose so. Nothing like a big breakfast. I always say if you're stoke up in the morning, you've got it made for the day. Yeah, that's right, Harry. Farm breakfast, they call this. Tell you that's easy. Oh, look at that sausage. Fried real good. I like it when it's like a rock. Can't stand pork that hasn't been cooked enough. Yeah. You want to go on with the story? Oh, yeah. Don't mind if I eat to you. Got a big day today. A lot of things to do. You go right ahead, Harry. All right. Well, like I said, this old broad ordered the sherry. Uh-huh. A lot of time went on. She must have had three or four of them. Yeah. A couple of other guys came in and I moved over to make room for them. I ended up sitting right next to the woman. Say pass the ketchup, will you? Oh, yeah. There you go. Eggs aren't much good without a lot of ketchup. It gives them real flavor. Yeah, Harry, could you get to the point maybe? Oh, well, first off, I noticed this perfume this broad's wearing. Well, now I tell you, it's been a long time since I smelled anything like that. Real heavy. Like the stuff they sell in France. Yeah. It didn't fit the woman. No, sir, it didn't seem to go with the rest of her. I tried to strike up a conversation, you know, talked about the weather, stuff like that, but she wouldn't have none of it. She didn't actually tell me, but I could tell the way she answered me. You know, kind of cool. What makes you think she might be the one we're looking for? The way she looked. The way she worked. What do you mean the way she worked? Well, I'm getting to her. Anyway, after she's had the sherry, she reached into her purse to pay for him. Humbled around in it for a while. Well, I couldn't help seeing what was in it. You know, what was sitting right next to her and all. Yeah, sure. Well, she don't come up with any money. And she starts going through her pockets. Still can't find any money. Finally, she asked Jack. Who's that, the bartender? Yeah, yeah, Jack. He owns the place. She asked him if he'll cash a check. Yeah. Well, now I asked you. Either one of you guys know Jack? No, I don't think we do, Eric. No, I don't. Well, Jack wouldn't cash a check for the treasure of the country. Not even if you had the president to vouch for him. You've been stung too many times. Yeah. Well, this old gal guest room, see? I can see him start to go. He kind of hems and haws around all the time. He's trying to figure out a nice way to say no to her. Mm-hmm. Finally, he just ups and says it.  But she doesn't. She just kind of punches her shoulders and then starts digging in her purse again. Takes everything out, puts it on the bar. Yeah. Well, it happens that her driver's license is lying right there on the bar in front of me. Couldn't help but read it, you know. Yeah, we know it too. Well, I saw her name. And I asked her if she'd let me buy the wine for her. Mm-hmm. What she did of that? Well, when I called her by name, she acted kind of startled like she didn't expect it. And then she kind of smiled and said she was financially embarrassed at the moment. Something about coming away from the house without any money. But she said she thought it'd be very sweet of me if I take care of the tap. So all I paid Jack the money. And I asked her if she'd like another one. And she said she didn't think so. And then she got all her stuff together and put it back into her purse and thanked me. Then she got up and left. Yeah, well, what was the name on the driver's license? Do you remember that? Yeah, yeah. Got it written down here somewhere. After she left, Jack and me got talking about her. And it hit me that she might be the one you're looking for. So I jotted down the name. You ever see this woman before, Harry? No. Never laid eyes on her before she walked into Jack's last name. Now, here it is. Well, thank you. Yeah, that's the name at the top of the paper. Right under her, that's her address. The name on the piece of paper was Lillian Halstead. It was a new name in the case. It gave an address out near Bell Air. Frank and I called the name and R&I, but they had no record on anyone answering that description. We paid the check and thanked Harry Allinson for the information, and then we drove out to the address.  Mrs. Halstead wasn't in, but the maid told us that we'd find her husband at the Halstead School of Dramatic Arts. She gave us the address, and Frank and I drove out to the school. It was located in the large modern building out in Wilshire Boulevard. When we got there, Mr. Halstead was working with the advanced class in the drama section. We took a seat at the rear of the auditorium and waited for him to finish. You gentlemen wish to see me? Yes, sir. You're Mr. Halstead, are you? That's correct. Police officer, sir. This is my partner, Frank Smith. My name's Friday. How do you do? I do. What is it that you like to see me about? Well, can you tell us where your wife is, sir? Lillian? Yes. Well, she's out of town. Why, what do you want with her? What if you could describe her for us? Certainly, I don't understand what this is all about, though. Oh, it's just a routine investigation. Routine? What's that mean?  We're just checking it out. Now, if you could give us a description of your wife, please. Yes, well, let me see. Lillian's 36. Yes, I would say she's, um, five feet six and one half inches. Ways, perhaps, 130 pounds. What colors are here, Mr. Halstead? Well, before she left, it was sort of an auburn. Lillian said something about dying in red. Might have done it since she's been gone. Where's your wife now? She's back in Washington. They're holding a drama festival and she's back there looking it over. Do you have a picture of your wife here, Mr. Halstead? Yes, sir. I have one on my desk in the office. What if we could take a look at it? Well, certainly, you can go out this way. Fine, thank you. Here, down this way, please. Thank you. Uh, you tell me what this investigation is that you're working on. Well, no, sir, not right now. We can't. Oh, you can. Uh, cloak and dagger stuff, eh? No, sir, it's not exactly that. Oh, here, I'll get the door for you. Thank you. Yes, sir, right this way. Excuse me a moment. All right. Here. Here's the picture. Lovely woman. Been a great help here at the school. Yes, sir. How long ago was this picture taken? Several months ago, I believe. And Mr. Halstead, how long has your wife been out of town? Perhaps a week. Ten days, perhaps. There's something like that. Your wife driver car, Mr. Halstead? Yes, sir, she does. Oh, I understand. The license. Sir? Lillian's driver's license. That's what you hear about, isn't it? Well, I don't understand, sir. Oh, you don't have to be cagey with me. Lillian lost her driver's license some time ago. Asked me to get her a new one. I didn't quite get a chance to do it. You found it. That's it, isn't it? No, sir, that's not it. We think your wife's license has been used as identification by some check forger. You haven't to know where your wife might have lost the license. Why? No, we don't know exactly. It must have been about three months ago. She says that she dropped it here at the school, but I've looked all over for it, haven't been able to find it. I think she just left it someplace. She's terribly careless about things like that. Yes, sir. Is this about the old woman that's been forging the checks? Why'd he ask that, sir? Well, that's another thing that I've been meaning to call you about. I was reading the paper one night, and all of a sudden it hit me. Sir? Well, I could be wrong, but I think I know the girl who's doing this. You are listening to Dragnet, the authentic story of your police force in action. The modern way to sell cigarettes is the Chastrophil Way. Premium quality in both regular and king size. And we're the only one that does it. We tell you what Chastrophils are made of to give you that premium quality in both popular sizes. Our scientists select the best materials. They select for Chastrophil the world's best tobaccos, blend them just right. And they keep Chastrophils tasty and fresh with the best of moistening agents. Now, here's something else that's completely modern about Chastrophil. People smoke Chastrophil and we tell you what happens, scientifically but simply. A medical specialist is making regular bimonthly examinations of a group of people from various walks of life. 45% of this group have smoked Chastrophil for an average of over 10 years. After eight months, the medical specialist reports that he observed no adverse effects on the nose, throat, and sinuses of the group from smoking Chastrophil. I'd say that means real mildness. And finally, we ask you to try Chastrophil and prove what we say. Chastrophil is best for you. They're much milder to give you all the pleasure that the modern cigarette can give. 2.37 PM. We ran the name Bert Halstead through R&I but we got no make on anyone answering his description. Halstead told us that he thought we might be looking for a girl he identified as Peggy Small. He told us that the small girl had enrolled in the dramatic school over a year before. We asked him if he had a picture of her that we could have. He told us that he thought there was one in the files. He took us down the hall to the registration office and checked his files. He located a picture of the girl and handed it to Frank. Just why do you think this might be the girl we're looking for, Mr. Halstead? Well, it's the oddest thing, Officer. Peggy. Oh, that's Miss Small. Yes, sir. Well, Peggy came to us about a year ago, as I said. She came out here to the coast from some little town in Idaho, I think it was. I'd have to check her entrance application to be sure, but I think it was Idaho. Yes, sir. Well, instantly I knew that this girl had talent, real talent, deep down, talent. Right off the bat she had the feel would have been a fine character actress. Why do you say would have? She didn't want to work. Wasn't interested in anything but learning how to be an old woman. Sir? All she was interested in was learning to act like a little old woman. We have a theory here, Halstead. Don't act, live. She did just that. Learned the make-up problems, dress, walk, everything. She even used to practice writing like a woman of 60 or so. I used to see her practicing by the hour. Does she ever give you any reason for all this? No. I asked her once, but she said that this was the way she wanted it. Now, I thought that she was trying to tell me to keep my nose out of her affairs in a nice way, so I didn't ask her a game. Now, we have presentations here, you know, each term the class presents a play that's been written and produced by the students themselves. Peggy would always do the oldest female part in them. Never was interested in anything else. She had several good offers, but for some reason she did not take them. What do you mean by that, sir? Well, one night a talent scout from one of the majors came out to see our play. He was quite the majors, oh, the studio. He was quite impressed with Peggy, offered her a term contract, good money. She'd have done well, but she just was not interested. I just can't understand it. Well, do you know where she is now? No, officer, I haven't seen Peggy since she left here. That was about, um, four months ago. I wonder if you could tell us where she lived when she was enrolled here? Certainly. I have the address on her enrollment card. Well, that's fine. We'd like to have the names and addresses of any of her close friends, too, if we could. Oh, certainly glad to help. You think it could be her, Peggy, the woman you're looking for? Well, it could be, yes, sir. I was thinking about it when I read about it in the papers. Right away made me think of Peggy. How she used to talk about acting. Well, how's that, sir? Well, she used to always say there was only one reason for doing anything, and that was to come out on it. That was the trouble with most people. They just didn't know where they wanted to end up. But she knew where she was going. Well, maybe she was right. I beg your pardon. She's the one we're looking for, we know, too. We got Peggy Small's address from Mr. Halstead and then we went back to the office. We ran the name through R&I, but there was no record on the girl. 402 PM. Frank and I drove out to the last known address of the small girl. It was a boarding house on 92nd Street. Peggy Small wasn't in, but the landlady told us that she usually didn't get back from work until 7 or 730. We asked if she knew where the girl worked, but she told us that she didn't. We arranged for a stakeout on the house, and at 4.37 PM we checked back into the office. You want to check the book? Right. Anything? Don't think so. There's a call from Faye. She wants to know if I'll be home for dinner. I better give her a call, Joe. Faye's got a little hacked at me. Was that so? Yeah. Last three nights she's waited dinner for me, and I didn't make it. Hello, honey? Yeah. Well, I don't know yet. Yeah? Well, I think so. I know, I know. Well, maybe another hour or so, I'll know. Yeah. It's OK, honey. Bye. If I don't make it tonight, she's going to scow me. I get it. Forgery Friday. Yes, ma'am. What's that address again? All right. Yes, ma'am. We'll be right there. Well, your dinner's going to have to wait again. Why? Dry goods store out on Main. Forger's there now. In the process of the investigation, the police department had alerted the merchants throughout the city to the method of operation of the woman forger. Thousands of printed circulars had been distributed, bearing her description. An artist's conception of the woman had been published in the daily papers, and the drawing had also been broadcast over the local television stations. The clerk in the store we'd gotten the call from had noticed a similarity between a woman waiting to cash a check and a description. From the information we'd gotten on the hotshot, the woman was waiting for an authorization for the check. When Frank and I got to the store, we met a small elderly woman. She produced identification in the form of a driver's license, bearing the name Lillian Hallstead. Frank and I asked her to go with us to the city hall for questioning. A police woman was called and the interrogation started. One look at her and you could see that she was covered with a heavy makeup. I want you gentlemen to know that I resent the implication you're making. The idea trying to make me out of vicious criminal. Ma'am, we're not trying to embarrass you. We just want to get to the truth here. I'm giving you that. I'm telling you what you want to know. All right, now let's get it over with. What's your name? Lillian Hallstead. Is this your driver's license? Yes, it is. Then the thumbprint on it should be yours too, is that right? I'd imagine so, yes. Well, then suppose we go down to the hall and take your fingerprints and compare it, huh? You look here, young man. I know my rights. You're not dealing with some little schoolgirl this time. I've lived a long time and I know just exactly what you can do and what you can't do.  If you want to make a fool out of yourself to that extent, then you go right ahead and do it. And mark this way, young man. I'll sue you for every nickel you own. I'll let the papers know about this. They love to know how you treat old women. They just love to know. Have you ever been mistreated in any way, ma'am? No, and I don't intend to be. There's a man on the way down here. Ma'am, the name of Hallstead. Wife's name is Lillian Hallstead. That driver's license we found in your purse, the one you claim is yours, that's registered to his wife.  Now, why don't you save us all a lot of trouble here? Why don't you admit that you're the woman we're looking for, that you're Peggy Small, you're no old woman? Come on, how about it, Miss Small? All right, I lose. I guess I should have known. Mind if I take this wig off? It's kind of warm in here. We've been kind of waiting for it. Go right ahead. It was a good rack while it lasted. Crummy driver's license I was doing all right as long as I used the letters. They should have been good enough for me. I should have known. What'd you do with the money? I got it all, every last nickel I would... I almost had enough, too. Enough for what? Leave this lousy town. Get out of here.  A couple more pieces of paper and I'd had it made. I could have left. Almost showed them. Showed them good. Ma'am. Phony town. Months I pounded on doors talking to agents, casting directors, talking to anybody who'd listened to me, trying to get a job, trying to get a break in pictures. None of them would talk to me. They wouldn't even see me as a phony town. Yes, ma'am. They wanted character women. Didn't want any young women, character women. That's what they wanted. But I got to be the best of them. They didn't want me the way I am. I didn't want to work any other way, none. Had to fool, didn't I? Had the whole town fooled. All of them. Phony place. I was going back east, back to New York. They know talent back there. They recognize it.  They know it there. Yes, ma'am. We know it here, too. The story you have just heard was true. The names were changed to protect the innocent. On June 19th, trial was held in Department 89, Superior Court of the State of California, in and for the county of Los Angeles. In a moment the results of that trial. Now here is our star, Jack Webb. Thank you, George Veneman. Friends, only the modern cigarette Chesterfield gives you this scientific evidence on the effects of smoking. No adverse effects on the nose, throat, and sinuses of the group from smoking Chesterfields. And only the modern cigarette Chesterfield gives you premium quality in both regular and king size. Now I know Chesterfield is best for me and best for you. Buy them regular or king size. Either way, they're much milder to give you all the pleasure the modern cigarette can give. Peggy Janice Small was tried and convicted of forgery ten counts. She was sentenced to the California Institution for Women at Corona, California for the term prescribed by law. Forgery is punishable by imprisonment for a period of from one to fourteen years in the state penitentiary. You have just heard DRAGNET, a series of authentic cases from official files. Technical advice comes from the Office of Chief of Police W.H. Parker, Los Angeles Police Department. Technical Advisors, Captain Jack Donahoe, Sergeant Marty Wynn, Sergeant Vance Brasher. Heard tonight were Ben Alexander, June Whitley, Jack Krushen, Jean Tatum. Script by John Robinson. Music by Walter Schumann. Hell, give me speaking. Sound off for Chesterfield. Either way you like them, regular or king size, you'll find premium quality Chesterfield's much milder. Chesterfield has brought you DRAGNET transcribed from Los Angeles. Tonight it's adventure with Barry Craig, confidential investigator on NBC.


Does the partner have a track record? Is this their first time like trying to buy a house and renovate it or do a new development or buy a shopping center or whatever? Or have they been doing this for 10, 20, 30, 40 years? Because really track record, again, we've all been through this. Would you take lessons from a baby that was literally learning to walk or would you take lessons from an adult that's been doing it for 40 years? It's simple.


Today, I have the pleasure of speaking with Darcy Ladd. How are you today? Good things. How are you? And we're going to do something very fun. I'm going to talk to a vanadium expert, and I would like you to start by telling me what is vanadium? Well, it's actually simpler than it sounds, because people aren't familiar with vanadium at all. But it's very simple. It goes into steel, and it makes steel stronger and stronger and better. A very small component of vanadium added to a ton of steel significantly increases its tensile strength. And of course, we're always marketing vanadium as a technology metal. So can you tell us what technology metals that vanadium is utilized in, in addition to steel, which of course is a huge growth market? Right. Steel is the biggest market, but there is a lot of interest and a lot of attention has been paid to this vanadium redox battery and the lithium ion vanadium battery. It's still a very small nascent market in terms of vanadium demand. It's less than 1% currently, but it is something that could be very exciting in future. The biggest problem with renewable energy is storage of the energy produced. So when the wind is not generating energy and when the sun is not shining, what do you do with the energy that you stored during those periods and when you need them the most? And so I think you will see renewable batteries like the vanadium redox battery take off, and it's just a matter of time, but at this point it's still a small area for vanadium. Because vanadium prices went down for a little while this last year, but right now they seem to be rising again. Can you tell us about the price of vanadium? Yeah, sure. Well, it's actually a very interesting situation that we found ourselves in, particularly at Largo Resources. We've sort of found ourselves in an unprecedented low in the vanadium price. Typically you have a pretty solid floor, and you can see this visually on a long term price chart for vanadium. It's $5.00. This is a very solid floor for the price. And we've seen it go below that in the past six months, which is very unusual. So after this unprecedented lull in the price of vanadium, we have seen the market do what it typically does in a situation like this, and it has begun a correction path. Typically when the price goes below $5.00, you see supply coming off stream because the average price for most producers is at or above the $5.00 mark. So we have seen it begin to correct up, and we have seen as well we've seen supply coming offline. Three suppliers in South Africa, as well as in Austria and who have all reported that they've had to cut production or they are going bankrupt in reaction to the low prices. So we're certainly seeing the market do what you expect it to do, and we're extremely hopeful that we'll see kind of a more normalized price range going forward and potentially a strong uplift in the near term. Well, that's very exciting because aren't you one of the most cost effective producers in the world? Yes, we will be for sure. By the end of this year, we expect that we will be the lowest cost producer globally, and that includes what is by-product or co-product production of vanadium as well. So we're in a very good position to weather downturns in the commodity price should they persist or should they occur in future. And so we're really in an excellent position for growth going forward. In the interest of compliance, I need to let our audience know that I am a shareholder of Largo because I am so interested in vanadium. So can you tell us a little bit more about the actual supply of Largo's vanadium? So currently at our phase one capacity, we'll be about 7% of global demand. And that's really, you have to keep in mind that the market has been actually growing at about 6% per annum for the past several years. It did slow down a little bit last year, but it's still a very strong growth rate. So if you think about it in that respect, you almost need to mine the size of ours coming on every two years or more. So we feel we fit very comfortably into the current market as it is and we already have expansion plans to go forward to fulfill continued demand. So what do you anticipate for the future for vanadium? What other technology uses are you currently exploring or can you share any of that with us? Well, I think the future of vanadium is extremely exciting. In addition to growth in demand for steel applications, you're seeing it going into a wider range of products. Probably about 10 years ago it went into missiles, turbines, golf clubs, very esoteric applications and now you're seeing it going into a breadth of products including automobiles, aviation, railway lines, railway cars, et cetera, power pylons. So that I think will continue to be exciting in steel. But you're also seeing growth in the titanium, vanadium, aluminum alloy market which is really a strong growth area for vanadium and that's particularly going into a lot of new aerospace applications. So I think that's another area where we'll see strong growth going forward. Well Darcy, thank you so much for joining us today. Thank you.


And I'll start with the mission, which is quite easy to view and reinforced, but before I start it, by the door. We are the steward of your first definition, and emphasis on the steward means that we don't define the definition in a market. We would maintain it for the community. So, if the community wants to change it, like so many people are yelling, but are angry, all the time, you can change it. And we are a public charity company, which is something that I am very enforced, especially because so many other corporations, organizations, have still a nonprofit that can work and behave like a trade association. We are by definition about our fight laws and the fight that we are included in the United States as a 501c3. And we are working to make the difference among the people in the general, not all the members of the community. This is the distinction that is worth highlighting. Because, again, people yell at me, they are saying, you put the money from Google, put the money from Microsoft. Therefore, you represent Microsoft and Google, which is not true. Technically, in an market, I speak about it in an ultimate way. And historically, I have been on the other side of the world. And I have been protesting against the right of corporations before I joined the U.S. association. And our mission is, our mission is to be the leader of all the different governments around the whole system, and the principles of the different governments and sources. And we will help the U.S. system to try to build individual practices, and the practices and ideas in open source for the implementation, and for the benefit of the, because we believe that that is not going to be the benefit of the society as a whole. And the other part of the logic is that we want to build bridges. So, we want to create a class of different B-discretes, we want to be on the big end of research, and society, all the same thing, so we don't really have any mission. I think it's a community goal that everyone wants to make. And then despite being established in the U.S. state, we do have a global bridge. So what we do in America is, we maintain your consortium in Asia, and with the new licenses, we're going to use the principles, using the better hand than the U.S. consortium in Asia. And then we're going to use this for 25 years, or five years, for a long time. So this is a project we've been doing for a very long time, which is, we're going to talk about it a little bit more. We're going to move the hands, and then we're going to use it like a series of steps, and then do it after a long enough, and then as they get in the night, and there are two areas where the refugees are monitoring and working with all the members established to review it and help out them about policies that they don't refer to the ecosystem, and actually promote and facilitate collaboration of community and agricultural borders. And we will help review the standards in making our system. that we are members of a standard setting of communications like at CISO, like in the sense of making sure that when the standards are set and adopted, they don't include innovations that would prevent the communication of the standard that people don't want to support. And it's a really crucial piece of the activity that is not only visible, because when all of the communications are happening, as I said, we're losing a lot of secret. But I want to make sure that we allow for that activity to happen and the damage done to us is great. Quick reminder, your research definition, I used to call it a poor worded way of the 43 systems of the CISO Foundation. Fundamentally, they're the same. But the checklist of your research definition is a little bit more practical. And what we use, the community uses it to give you licenses of how they come in. And it's really just a checklist. One couple of interesting points. Highlight here is the two points of non-discrimination in person or in human endeavor. These have been coming often under stress and under the thought in the recent world. Because the decision why you are trying to make up is because human first definition has enabled the same aggressive flow of an internet to protect that allows for recommendations that we would do. So I'll talk to you again, for example. In a very, very human way. In a very, very human way. In a very simple way. You can do the loading application from a light line or from an internet. And you just do the license for something with a code. And then that code corresponds to a license in which it will be applied to your social media. And then it will have to be there. So you can do the online application. You know that the code that you're downloading grants you those 10 commands. It grants you those 10 commands. Without it, without any of those 10, you must have your legal department and they must check the license first and see if you're allowed to send them off. It's very crucial because in the past few years, more and more groups, corporations, independent people, individuals have been telling us that the open source, the word open source is not directly tied to the open source definition. Because, well, you have no trademark. Well, we may not have the trademark, but the thing is that once you start polluting the definition and you start polluting the meaning of the word that, for example, this conference carries and understand very easily that open source is software that has been licensed with a license that has been approved by the open source initiative. Then you're creating doubt. You're creating friction inside the environment. And you're creating troubles down the line. And these ambiguity, these troubles that these groups have been putting are dangerous. And we need to take really good care of defending the common understanding of what open source means. And the reason for this is because the validation that open source means what has been approved by the open source initiative comes not just, comes from a very wide understanding, even policymakers. So these are top level government organizations that understand and assign to the open source initiative, to the list of licenses that we approved, assign the value of the organization that I represent. The Italian government, the UK government, even the European Union, without saying explicitly because they can't. But once they presented, they developed a new license to use for all the software developed and released by European Commission, European Union institutions, the European Union public license, they wanted us to approve it. And they celebrated when we approved it. So delegating to us that importance and the trust for the authority. So how we are maintaining the definition and how are we responding to these common threats, but also how you're maintaining this authority by doing what we're doing in a very humble way. So we want to maintain and keep on enforcing the definition to maintain this honesty and advertising, meaning we have noticed a lot of, when we notice corporations or groups that are using the licenses, creating new licenses, and then in their GitHub repository, Git repositories or on their publicity material, their advertising material, they call it open source. Then we nicely go back to them and say, please, be nice. Open source is not what you mean. This by this, call it something else, but be true. And luckily, we're also starting to see courts noticing this and assigning the reinforcing the meaning of the word open source as using a license that has been approved by the open source initiative. So we're going around and monitoring this being very, very active. And the other way that we're doing this is by working with having this project called clearly defined. Clearly defined is the repository of metadata that increases the information that is available into individual packages inside the largest package managers, like NPM and PyPy who's come to mind, where a lot of these package managers don't have a strong enforcement of licenses information inside the packages. So individual developers can pretty much swap any way or form. Nobody checks whether the licenses are correctly applied inside the repositories and they get distributed. What clearly defined us is to provide an additional layer of information that's crowdsourced information, vetted and validated by the maintainers of the metadata repository so that your CI CD, your S-bomb material software, your scanners, your license scanners can rely on this information more clearly. And we are reinforcing this project as four years old is in production at Microsoft, Bloomberg, Windows, Siemens, and SAP also are big users of it. And we are hiring a community manager for this. So if anybody is interested in working with us, let me know, reach out. And the other activity that we're doing to reinforce our understanding of the licensing information is to look at new technologies, how those new technologies are affecting the 10 principles of the open source definition. AI is one of the new technologies that is deeply changing how concepts of data and software and source code are intertwined and mixed in a way that the software that we had in mind when we wrote the open source definition doesn't have. So we launched this event, which is in three parts. It's ongoing. It's still not over. The first part is a series. It's a podcast series. And I highly recommend to listen to five episodes and with interviews with experts to kind of that will set the stage for the second part, which is happening next month, panel conversations, four panel discussions with three to four experts each of the panels. And we will dive a little bit deeper into the aspects of the legal status of a model. Since it's not covered by copyright, most likely, what is it under? How do you understand whether you can share it or modify it? And how to modify it, which will be also addressed from the business perspective, from the perspective of researchers in academia, and finally from the civil society as the ones who will be judged by the AI, whether we are deserving alone or not, then what are the rights that we should be exercising? And this comes from my experience from when open source started to become a thing.  Like if you wanted to apply for a credit card on one hand or for an ID card and you needed to go to a website and the website was only available for people using Microsoft Windows with Internet Explorer and ActiveX plugins. So the combination of that proprietary software to interact with citizens, we had an answer. We said, look, you have to be able to interact with citizens with open source software. Now, if we say to the policymakers, if someone is denied alone, you have to give them, you have to give the citizens what? And that's why we're doing deep dive AI. On the policy front, we've been working in Europe for multiple years now, but we're also expanding our reach. We announced that we hired this week a U.S. policy director, Deb Bryant. She's a very well-known leader of open source projects. And she will be working a lot with local institutions in the United States, local agencies and also federal agencies to teach them about how the value of compliance, the value of open source collaboration and how to do open source. Because if there is one thing that I noticed in the 25 years of existence of the open source initiative is that we have many other ways in software, there is a top of the spear, top of the pyramid set of people who really deeply understand what's happening and why and how to deploy, how to collaborate and how to use licenses. There is at the bottom of the pyramid lots of people who have just barely heard of this. They come out of college, they have played with Apache software, they have played with Linux software, but they have not really understood exactly what the whole means and nobody taught them. So we have some catching up to do and we're gonna be doing this with thanks to contributions and donations and goodwill of Deb Bryant and Simon Pipps in Europe. So I was hired one year ago and I'm the first executive director of the open source initiative. This means that a lot of the processes inside the organizations have to be created. A lot of the programs have to be reinforced and these are the three big buckets for me in 2022. And I'm glad to say that, so improving our outreach and advocacy team was one of the main things that it's in my to-do list, reinforcing the projects and fixing the operations inside. And it's at the same time as building everything else. It's like fixing the plane as you're flying. So I'm happy about a lot of the things that we've done. So we managed to launch a new blog and I encourage you to look at it because it's called Voices of Open Source because the intention in here is to work with the community and make it available as a platform for the community. So affiliate members, affiliate organizations which are part of our network of friends would say they have access to this and in fact, we've been publishing interviews and publishing stories about affiliates, but it's also available for partners and sponsors and individual contributors within the framework and the limitations of being a charity organization. So we can not advertise your products but definitely we can talk about stories of how you deployed, how you train your new staff, for example, new engineers, how you teach them how to use open source or how your customers are enjoying the fact that you are working with open source software. And the one thing that I'm really happy about is we removed Google Analytics from our systems and went for a European company called Plausible. A new website is also under development and you may say, what's taking you so long? Well, I tell them myself, limitations but we have a good team working on this and these are the focus areas. So on the advocacy and outreach that I spoke a little bit about, mentioning the AI work and on the licenses front, I mentioned clearly defined but there is another project that is brewing and I will announce it by the end of the year. We want to streamline and simplify how the core activity of OSI has been done. So licenses right now, they are published as static web pages and a lot of tools out there are relying on scraping, web scraping to understand whether a license has been approved or not, which is really, really, really so in 1991 we should move on. And so we have a plan of actions to transform this into, we're doing two things actually. One is to put the list of licenses behind an API so that tools like SPDX or software heritage can automatically check and deliver the information about the license, the approval of the license or not. But the other thing that we're doing is to validating that database to make sure that we haven't missed anything because you may imagine with lots of volunteers over the years maintaining that list, there might be like one or two that have been missed. So we're gonna have to hire some contractors with some legal knowledge to understand, to go through the minutes of the week and build a database. It's gonna be a little bit painful and boring, but we'll do it. And the other thing that we wanna do is to change how and create like a reliable archive of those decisions because the discussions and the knowledge about that, the discussion when a license was reviewed are now in a very opaque, I must say, and loosely connected archive of mailman. All the Piper mail archives holding the information about why a license was approved or why it was denied approval. And we need to build that kind of information back into the license text itself. So that's a little bit more complicated to achieve, but it's also something that we have sketched out and we will start the conversation with the community very, I'm hoping as soon as we're done with the AI project. And then going into the future, we wanna change how we review licenses. Like right now they are happening, like I said on mailman mailing list, it's not exactly the right way to do it or at least it was the right way at the time when we had, we knew no better, we didn't know better or we didn't have any sophisticated tools to do it, but we do have it now. We don't have ways to annotate text and keep that for forever as archive. And okay, so and these are the other, that's the other area that we're working on on to the expansion of our policy programs because we see the activity in related to security and the fact that open source software is everywhere. Finally, policymakers in Europe and United States are waking up to the dependency. They need to understand what's happening and why and we need to avoid for them to, for us to be chasing them at the last minute to avoid them from, for example, banning the export of all software from one way to another. And we will be stopping collaboration that has been creating this wealth of software. And we'll do more, I have a lot of other ideas about how we need, we want to engage with the members, with the community in general. Right now you may have noticed on the website there isn't, there isn't, there are many ways to interact within members and staff, for example, or just to collaborate lots of the conversations happen outside on Twitter or on different Slack channels, different IRC channels or mathematics channels. And we just need to have a better way to interact with each other. So it's, it's also on my radar and my to-do list. And on the training and education side, we do have a partnership with, we helped run the ISA, it's a university in United States to create a training program for project manager, program managers to understand open source. That program, training program has wonderful reviews, but not as many subscriptions. So we need, we're working with Brandeis to refine the way we reach out to potential trainees or people who are corporations rather that want to offer that as a training package. So if you have, if you work at an organization and you would like to see your company offer more training to product manager, project managers about how to do collaboration in open source, it's a great program and I'm welcoming your contacts. So I can put you in touch with the university. And I would stop here and I would take questions from you.  Are you convinced that this is a good idea or are we missing something? Do we? So the question is, we partnered with, you're mentioning the one that we did last year. I don't remember now, is it the second? No, not with someone. Oh, the partnership now is with our God. Cut this, oh my God. It was a survey, but it was done with a company and we helped them refine the questions and distribute the results. Yes, that's a good question. In fact, we are in the process of reviewing the questionnaire now. And so what's your suggestion? What would you like to see? The raw data? Yeah, yeah, yeah, right, right, right. Yeah, of course, there is an interpretation going behind the presentation of the result. That's a good comment. Yeah, I'll take it to the team and we'll definitely discuss that, yeah. Thanks. Think about it, you know, it's daily. Finally, I call to like, this is the one thing. Some of the names just have to be tracked over time. So the interest is very much in, exactly what do you think you'll be delivering in the process you're going to find? Because I thought it was literally interesting, you're asking what the rest of you are. So you just have a roadmap, what's actually going to be delivered there? It's just a bit of an idea of what's happening. So clearly the find now has, it's already in production. So it has APIs and it's got all the information from the consumption perspective. So you can look it up now. I think it has partnerships with a bunch of OSSA, Phosology, I don't know what other code scanners you can plug it in. I don't know if that's your... Canonical names for some purpose? Canonical names for the licenses? That's a good question. Yeah, for canonical names of the artifacts. So you can recognize in a package, science something is actually this one corresponding. I'm not sure. Honestly, I'm not into the weeds of the users of clearly defined, but that's something that we can definitely, I can bring it back to the team and discuss it because in the end, this is all driven by adoption. Right now, I think it's satisfying the needs for, I know that they want to fix all the time something like Microsoft inside Bloomberg, but more participation and more comments. Definitely, it's worth bringing it up. Thank you. Yes? Yeah, right. So okay, so it's, I understand correctly, your comment still, it's referring to clearly defined and being caring the information about the license and the seal of approval from those. Yeah, okay. Definitely, definitely something that it's nice to have. So the community of clearly defined meets on Discord a lot. They use it very, very heavily, but they also have a presence on GitHub. So lots of conversations can happen there, but I will definitely relate that to Carol Smith and the others leader. Yeah. Anybody doing AI here? No? Yeah. Yeah, I do have some ideas. I spoke about AI yesterday, but I can give you the gist. I think what's happening is that there is a huge, there is a huge push and pull forces. One from research and academia, they've been working on these problems and they have been playing with small data sets. They have been playing with small models. They have been doing so many interesting things. And what's happening is that all of a sudden there is a huge amount of data available coming from corporations or coming from groups that are capable or able to assemble these huge data sets. Huge data sets bring larger models. Larger models bring better results or faster results and they're very exciting. This means that the, these AI models start to become really good, really appealing. Oh my God, let's put it in production. So they go into production and they started to damaging things at the very fast pace. So we need to, what we're trying to understand with the AI, oh, sorry, at the same time, the people responsible for these large models and these large data sets, they're scared, they're afraid. So my interpretation, by reading the room from the outside, my interpretation is that the fear of these models getting out of control is pushing them to write licenses, so releasing the code, but then writing a license that says, you cannot use it to do harm. I'm being very blunt, but it's a little bit more sophisticated than that. But they understand that the AI can do damage, so they're limiting the uses of AI, then their AI. And so with these new licenses coming up, we're gonna have more and more of those because the temptation to deploy more AI, to deliver more AI, there will be more temptation to write contracts and write norms, write law cases. And we as the Open Source Initiative, we need to, we wanna help them. We wanna help them understand the space because before you have a huge field of licenses and that you cannot really use because they don't enable collaboration, they don't enable sharing of information, they don't enable sharing of weights or all the pieces, the source code, whatever that is for AI, if they don't have that freedom, those freedoms defined and clarified, the field may slow down instead of making fast progress. So it's a way for us to reaching out and we're gonna have in the panels, to reaching out to other communities and convene a conversation with us so that we can help them. See, traditionally we haven't covered data, that was the realm of the open data movement, open knowledge movement, open access movement. And in fact, that's one of the challenges of AI, it's that it brings together software, knowledge, data and we need to think about all of that holistically. And everything can respect what's in the data. Yeah, yeah, yeah. And the gap is very visible to me on the images front. It's at the same level. I put my picture on Flickr a long time ago. Now my picture on Flickr a long time ago is being used to identify me on the street if I'm going for shopping or on a protest or something. Did I give the right to Clearview to use my picture and sell it to the NSA as a model? I have not, not explicitly, but at the same time, the EU has pretty much given a blank cover defining the right to data mining. It's only available for nonprofits, for research purposes, but the data set can be built upon anything that is available on the internet, unless someone says no. So all the past, it's available for data mining in Europe. Yeah, yeah, except, yeah, it's a new, it's a new right. It's like when the EU established the right to databases. Yeah, so I only have one minute left. It's, I can, I would continue the conversation with much pleasure outside also. Over lunch or something, yeah. Cause I think that the, we are at the, when software was created, I mean, in the 80s, when the open source definition came out or the free software definition came out, software was a brand new primitive, a brand new artifact, it did not exist before. And the community of researchers in, funny enough, the AI lab at MIT, they created the social norms first. They saw the danger of the privatization of knowledge that was coming out of the labs and getting into the private enterprises. And they created the GNU Manifesto, Richard Solomon wrote it first, then he wrote code, and then he wrote the license five years after. So I think we are at the same stage now where AI is escaping and the labs and getting into the, in production and banks and governments and stuff. And now we need to establish those norms. Like what's acceptable behavior? Why is that acceptable? What's the purpose of having, enabling sharing and stuff? With that, I got a red light. Thank you very much for coming. I got stickers here if you want.


You're watching News Made Easy, I'm Anandesh Chakravarty and today I'm going to take about Kerala's runaway COVID infections. It's of great glee to right-wingers because they can use it to attack the left-front government in Kerala and say that, look, this is your Kerala model, you completely messed it up, India was on its way to do well and look what you've done. There's a kind of communal angle as well but I'm not going to give it respectability by taking it up at all but it is true, the official data shows that Kerala is doing badly at this moment because yesterday there were about 40,000 odd cases, new COVID cases in India and more than 50% came from Kerala alone but as we know coronavirus is a thing in which when you get COVID you can be asymptomatic you might not even know you've got it and you develop antibodies, you'll never know that you were once a COVID patient so initial estimates said that about 80% of people who get COVID are asymptomatic and have no symptoms but later that number was changed and it was said that a large number who appear to be asymptomatic then develop some symptoms one way to find out what is the total number of infections in a community not just the officially tested cases because that's always going to be lower is to do what is called a sero survey, is to randomly treat test people and find out whether they've developed antibodies and they might have got COVID, they might not have got it, they might not know that they got it but if they have antibodies that means two things, one they either got the infection or two they got vaccinated and developed antibodies, right? I say Amman Indian Council for Medical Research which is the central government's body has done four such sero surveys and the last one, the fourth one took place between 15th of June to 7th of July and for purposes of this show I'm going to take the midpoint 26th June to compare data what is that sero survey show us, that sero survey shows us that the number of cases in people who have antibodies in India is almost two thirds two out of three people in India have antibodies which means they were either infected by the coronavirus they got COVID or they had vaccinations now as I said the 26th June is the relevant date that I'm going to take and I'm going to take the actual official cases on that day for four states including Kerala and I'm going to compare it with three other big states, number one is Maharashtra which has the maximum number of cases Maharashtra on the 26th of June had over 60 lakh COVID official cases Kerala came second with about 29 lakh cases remember Kerala's population is much much smaller than Maharashtra so 29 lakh cases compared to 60 lakh in Maharashtra that's a huge number and I'm going to take two Hindi belt big states Uttar Pradesh and Madhya Pradesh in Uttar Pradesh on that date there were just 17 lakh cases huge population but just 17 lakh cases and in Madhya Pradesh it was not even 8 lakhs just 7.9 odd lakh cases that's on the 26th of June so by 26th of June 5% of Maharashtra's population had officially through confirmed tests been infected with COVID they got the COVID infection in Kerala that number was 8% huge in Uttar Pradesh it was just 0.7% just 0.7% of people had officially confirmed got COVID infections and in Madhya Pradesh a close number as well about 1% 0.9% less than 1% in fact but what is ICMR's data tell us and now I'm going to take ICMR's data and I'm going to tell you about Kerala last right because on the face of it officially it looks like Kerala was the worst it was the worst when it came to trying to stop COVID because 8% of its population had already by 26th of June got the virus ICMR's sero survey data tells us that around that time in Maharashtra 58% of people had developed COVID antibodies remember I'm reminding you again and again this means that either got vaccinated and developed COVID antibodies which takes about 2 to 3 weeks after your vaccination and or they had been infected 58% in Uttar Pradesh which only had 0.7% official infections compared to its population the sero survey found that 71% of its population had antibodies to the coronavirus antibodies to COVID right so either they were infected or they had developed antibodies because they were vaccinated in Madhya Pradesh where less than 1% officially had got COVID 79% had antibodies which is the highest number for all the big states and now finally I come to Kerala it had the lowest sero prevalence of big states just 44% of people of the population estimated to have either got antibodies because of vaccinations or because they were infected now how do we find out how many people got antibodies developed antibodies because they were vaccinated impossible to tell because you know even after vaccination it takes time and it varies from people people so what I'm going to do is I'm going to do what I'll call a guesstimate I'm going to say that okay 26th of June was not that far back it was just a little over a month ago so I'm going to take yesterday's cumulative vaccination figures for each state I'm going to say what proportion of the population has at least got at least one dose of the vaccine in each of these four states and I'm going to say that 50% of them were vaccinated and had developed antibodies by the 26th of June right the midpoint that I took so if I take that then I have to say that in Maharashtra approximately 18% of the population had developed antibodies due to vaccinations by 26th of June these are broad figures this is a range and this is a guesstimate so it's not going to be as accurate as ICMR's seroprevalence studies but even that after all is a survey right so out of the 58% with seroprevalence or as in with COVID antibodies I'll say about 18% in Maharashtra got it because of vaccination in UP about 11% got it because of vaccination so out of 71% 11% got it because of vaccination in Madhya Pradesh about 21% got it because of vaccination out of the 79% who had antibodies in Kerala because it has a very high rate of vaccination as of now in Kerala about 29% 29% of those who showed seroprevalence around the time when ICMR survey was taking place would have got it because of vaccination there'll be a bit of double counting these are broad figures but remember that this will be equally true for all the states so I'm adjusting for that now remember that as I said that the only way for us to get a sense of the actual infection is to remove the number of people who might have got it because of vaccination and that's what I'm trying to do so what are we left with in Maharashtra about 40% of people who were caught in ICMR study to have developed antibodies 58% was total number and removing 18% so 40% were infected in UP 60% of the population was infected and didn't develop antibodies because of vaccination 60% were infected in Madhya Pradesh as I said about 58% in Kerala it is just 15% so Kerala's actual exposure the population of Kerala who actually got infected even though only half of them ended up being caught in tests only 15% were actually infected around that time around June 26 which explains why there was such a huge population left for the virus to play with yes many of them had developed antibodies because of the vaccine but the virus still had a large number about 55% of the population to infect which it did not have in UP and Madhya Pradesh and in Maharashtra it had a fewer numbers which is why we again saw a bit of a spike in Maharashtra as well so Maharashtra and Kerala the two big states now let's look at what the ratio is so if we look at it and what do I mean by ratio I'm saying the ratio of official cases versus my adjusted seroprevalence adjusted for those who would have got it for vaccination because that is a point being made against ICMR study in Maharashtra I said 5% official cases 5% of the population officially detected to have got infected 40% is my adjusted number based on ICMR and I'm adjusting for vaccinations which means that about 8 times is the actual infection rate look at UP 0.7% officially infected and 60% is my adjusted number it could be 55 it could be 65 to 60% so the ratio here is a whopping 84 times 84 times the number of people who were infected in UP compared to the official numbers and in Madhya Pradesh it is 63 times it could be I mean I'm just giving you a broad picture but look at the ratio it's massive 84 could be 50 that doesn't matter but 50 times is also a very huge number right it could be 90 that is even worse in Kerala what is the case as I said 15% around that time 15% would have been officially infected would have been infected by the coronavirus that means if I compare it to the official cases it's just 2 times so Kerala successfully identified 1 in every 2 cases make that 3 cases make that 4 cases it is still much much better than any of the states we are looking at much better than any of the states whether it's Maharashtra, Uttar Pradesh, Madhya Pradesh in being able to capture the actual infections and treat them and deal with them let's look at the death rate you can say ok maybe there were so many cases but who cares people didn't die in other states well they didn't die because they weren't counted right we know the under counting that has taken place which has been repeatedly reported in various places we have a new piece that has come out which shows that in the key hotspots of UP the under counting is massive excess deaths were massive what does excess death mean? excess death means that let's say that this is the death rate trend that every year we expect so many people to die given the trend over the past few years how many additional people died in a covid year in a pandemic year we have the Hindu did a study and they came up with several big states the excess deaths in several big states and compared it to the official covid number this did the study from April 2020 to May 2021 and after that we know a lot of people have died in other states so that number has changed significantly but still we get a sense as to excess deaths which is the number of extra deaths from the trend which has taken place during the covid year compared to the official covid death because remember in a covid year if there have been excess death then most of them would be because of the pandemic yes some people might have died because all medical resources are being pushed towards concentrated on treating covid and dealing with covid so maybe people with chronic diseases, terminal diseases died because of that they would have died in coming years but they died this year because they couldn't get medical attention and some excess deaths took place so in Kerala the number of excess deaths was 4178 in the period studied by Hindu in Madhya Pradesh the excess deaths were 192,000 that's the number of excess deaths now compare that to the official covid death data for that same period the same period that the Hindu has studied Kerala declared that 9,954 people had died of covid in this period which is more than the excess deaths which means that Kerala the number of deaths in Kerala which would have normally taken place actually reduced in the covid year because of lockdown because people were wearing masks and respiratory diseases which would have normally killed them killed fewer people, road accidents didn't take place and maybe there was a slight fall in registration in the beginning and that could lead to the reason why we have fewer excess deaths than the total number of coronavirus cases one would have expected that the excess deaths would be higher than the official coronavirus cases covid death cases right but in this case it is lower what's the case story in Madhya Pradesh in Madhya Pradesh officially only 8,068 people died of covid when its excess death was 192,000 I am leaving it to you to decide whether that 8,000 number seems credible to you 192,000 excess deaths and only 8,000 people died of covid what did the others die of maybe they died of something I don't know loneliness or whatever but the point is that one has to adjust for these data and see and remember Kerala has a very good death registration rate much better than other states India has a good registration date because the ministry's data for 2019 says it's almost gone to 90% but Madhya Pradesh would have lower Uttar Pradesh would have lower and Kerala of course higher so maybe this data would catch up as we move forward but the point remains that essentially Kerala has dealt with not only covid stopping covid from spreading as we can see from the seroprevalence rate as well as reducing the number of deaths so even if Kerala sees more infections in the coming weeks if it manages to control it it is not going to take any serious proportions that we saw in some other states where there was no oxygen where there were no hospital beds people were dying on the streets outside hospitals not being able to get any treatment Kerala hasn't seen that because and that's not surprising because the Niti Ayog's own health index ranking makes Kerala number one Kerala is number one in terms of health in India among states and UP is the worst performing and Madhya Pradesh is also somewhere down there among the worst performing states so that is why Kerala's official numbers are robust they're transparent and Kerala has successfully caught coronavirus cases and stopped it from spreading and now that is also the reason why it's spreading faster because others have reached their herd immunity stage probably where is Kerala hasn't but as long as Kerala's health system continues to be able to deal with it then that problem won't exist that is what we have to watch out for that's the show today keep watching Newsclade and do subscribe to us