Hello, I'm Love Ikuku Oyedoku. I'm your host. This is Greta Lagos' vision. Lagos prides itself as a state of excellence. It has continued to record rapid infrastructure development by Governor Babaji Desu Oulu, our visionary leader, with the zeal to translate his Lagos dream into an unsupposed legacy. The governor promised that his administration would not relent in the provision of infrastructure for coordinated and sustainable development, giving priority to continuation and completion of strategic projects in line with the state's transport master plan. This is the Greta Lagos' vision. Welcome. This episode features Lagos rail lines to begin commercial operations in 2023. Governor Babaji Desu Oulu resets commitment towards rebuilding Igbo Shirei High Court to an enviable standard. Another set of 100 units of housing projects commissioned in Ikate, leaky area of Lagos state. Answers, Governor Oulu Broca's reconciliation with youths promises increased state's investment in human capital development. And the first edition of the 2021 National Women Conference organized by Committee of Wives of Lagos State Officials Council held during the week, seemed awake. These are many more. When we return, please stay with us. Lagos State Governor Babaji Desu Oulu says, his administration has demonstrated commitment to the blue and red rail lines in the last two years. He said he's sure to deliver them before the end of his tenure in 2023. The governor stated this in Lagos while speaking with journalists after inspecting the level of work done by contractors handling the projects. Lagos State Governor Babaji Desu Oulu and other government functionaries inspecting the rail projects, the blue and red lines. The construction of the project began over 10 years ago by the former administration of Babatunde Vashula. The governor explained that a blue line was assigned to run from Okokomiko on the Lagos Badagri Expressway through an elevated line crossing the Igomu Lagoon to Marina on Lagos Island. We're going to push back the rail up until we do, but we didn't get to do today. So crossing all of that, we now cross over onto the blue line. So on the blue line, we stopped at the beginning of Marina, which is where you have the sea crossing. So there's an interesting development that is going on there. Because of the sea war that we have at Ibuteru, we had to redo another sea war. And we saw all of the sheet path that had been done so that we can preserve and conserve the water bed in that area. And we're happy that all of that is also going according to schedule. When the inspection was over, the governor assured that commercial operations will be flagged up in the first quarter of 2023. We're still on track with last quarter 2022 by the grace of God. You know, last quarter, we hope that the train will move last quarter or first quarter 2023 if you get to see a rail and your train moving on this. On this two rail. The governor also highlighted the features of the Ikeja and Marina sessions, which are the meeting points of the red and blue rail line projects. At Ikeja, we saw the station and we also saw the construction of the overpass. The overpass is to ensure that vehicular movements can move over and above the train that we're going underneath. And we saw that work as commenced extensively. There are few issues, which is why you saw the small parts where you have a generator which was built in approval with a motor, and that will be removed in the next one week. The Lagos State government has repeatedly postponed the completion date of the blue line. But Governor Sao Wulu has assured Legosians once again that the project will be commissioned before he leaves office. Lagos State Governor Babaji De Sao Wulu has restated his commitment towards rebuilding the Igbo Shirei High Court to an enviable standard. The governor stated this during the launch of the fundamental principle of law practice and procedure in honour of Justice Jumoke Pedro in Lagos. Seated here are men and women of the legal profession who have come to lend your support to one of your own, Justice Jumoke Pedro. The moment was there of no nostalgia feelings bringing back the memories of the past, the monumental destruction that followed the ensouled protests both public and private institutions burnt down. Police stations, B-R-T bus stations and buses also burnt. Courthouses not spared. Bring the state to near Riyun. What he did and how he made me for two minutes take you back one year ago. Exactly one year ago, a disaster hit Lagos. An icon of our time. What we all grew up watching as a faster and as an emphasis in Lagos was plundered down. Lagos saw an aftermath of the ensouled and were thoroughly, thoroughly devastated. But this is Lagos. Optimistically, Governor Saoono recounted efforts being put in place by his government at ensuring the provision of suitable courtrooms for judges in the state. Rekindling the hope of the men of the bar. That's the Bushy reports to commit that not only are we going to rebuild it, we'll be putting a structure down at 49 years of age. It may interest you to note that the Lagos' chief executive also reassured these legal luminaries that his administration will continue to guarantee the independence of the judiciary at all times. As part of the commitment to rebuilding affordable houses for Lagosians, the Lagos state governor, Baba Judiso Wulu, has yet commissioned another set of 100 units of housing projects in the Ikate leaky area of the state. The governor also named a block of the project after a grade level 15 staff of the Lagos State Development Property Corporation, LSDPC, late engineer Wakilu Hamsats. The Bayview estate Ikate elegushi leaky brings a number of housing estates commissioned so far by Governor Saoono Luto 11. The project consists of 100 units of 68 terraces of four bedrooms with a maids room and 32 flats of three bedrooms with a maids room. We were able to very auditiously push forward this project and we said we wanted to reflect a development that will speak, you know, middle-upper markets, you know, that will meet the yearnings of the young, upward-remobile, you know, citizens that are in this etiosa elegushi corridor and that's why we've put here three bedroom flats and four bedroom terraces, each one of them coming with a maids quarter. So it's not for them to go outside and go and look for where they are made or their support staff will be. It's all been put into the facility of this development here and it has also come looking at the entire family ecosystem and so you have a swimming pool, you have a gym, you have a small hall, you have everything that can indeed, you know, meet the needs of the families of today and that's why I'm so excited that we took that view way back to meet the needs of today and the needs of future people that will be staying in this facility in this estate. According to Sawulu, another set of housing estate will be commissioned before the end of the year and first quarter of next year. We've done 11 housing estates in less than three years, over two and a half years that we came into government, right, and we still have a lot more that we're pushing, that we're pushing. We should, before the end of next month, be handing over the Beshe housing estate. That's a massive, massive, massive project that I'm very, very happy to have also been identified with LSEPC and Minister of Housing are pushing that. It's a total of almost 500 units, 480, and at that commissioning we'll also be laying the foundation for phase two of that Ibeshe housing estate. So we'll be commissioning, but we'll also be starting the phase two almost immediately. We'll also have the Shangutedo, we're going to be commissioning the phase one of Shangutedo. Shangutedo is over 1,000 flats, but the phase one of it is over 744 flats. We want to ensure before the end of the year that we also hand over, you know, phase one of Shangutedo, which is about 744 units. We'll also have houses that we're trying to complete at Udonosa in Aboa. That also we're pushing all the contractors to ensure that we complete. And of course, the Undubusi Cano housing estate in Bagada. That also we just have a little bit of snags here and there to finish and we're hoping that before the end of this year of early next year, early next year, first quarter next year, we also should be able to hand over, we also should be able to hand over Undubusi Cano housing estate in Bagada. Commission for Housing Muruf Akinde Rufotai said the Somuluz administration is committed to resolving the housing deficit in the state. This noted was aimed at boosting the state's economy and increase its internally generated revenue. It is worthy of note that Bayview estate is an avoidable luxury project, which is a joint venture scheme handled by LSDPC and Missile Limited. It comprises of 68 terraces and 32 flats in this eyebrow area. This, the inclusion of this generation of houses scheme in our portfolio is part of our social inclusion housing policy in ensuring that all classes of inhabitants are catered for by this administration. It's also part of our goal of developing a 21st century economy that housing development should encompass the apartment. While appreciating Somulu for the support, the managing director of LSDPC, Dakrile Ha Yusuf, assured that no effort will be spent at ensuring that no housing scheme is left uncompleted. Under the Somulu administration in the last one year, we have completed and delivered the estate. Among them are the Kotlan Villa estate and Platinum Road, Leki. The project was initiated four years ago while Somulu was the MD, CEO of the organization. Governor Babajide Somulu has promised to increase Lagos state's investment in human capital development and equip the youth which requisites 21st century skills. The governor stated these are the youth symposium organized by the Ministry of Youth and Social Development, themed Rebuilding for Greatness, Peaceful Conflict Resolution. In the wake of the NSAS Memorial, youth across Lagos state defied the national holiday and came together to participate in our peace conference aimed at creating a common platform to pursue resolution to conflicts. Governor Somulu listens with proud attention as a youth-led conversation on how they could effectively channel their grievances to the authorities. Actually there is somebody who is selfless, somebody who understands that leadership is a privilege and I will tell you that a selfless person is somebody who says to the heart of the people to realize their pain and it is when a leader sees the pain of the people that is when he will have the ability to address and give solution to their problems. It's that I am saying thank you. Thank you for giving me a voice, for giving me the privilege to be able to represent the youth in Lagos state. I'm so grateful sir. You've done a lot and Lagos state will keep going higher. We are rebuilding Lagos state. Yes, NSAS happened last year but it won't happen again because now we are hoping to light. We now know what we want for our state because we know that if Lagos state is not suitable for us, we are at the receiving end. So we must all put our hands together. We must all work with Lagos state government to ensure that we build a greater Lagos. When we heard about this program we had an emergency meeting at the level of the youth council and we came up with resolutions and they kind of propose us that we believe that if well implemented the Lagos state government is going to be on a good page of the youth forever and ever. The governor said the moment for true reconciliation has begun. Today it's a day of reconciliation. Today is about the youth. Today is about a day in which we want to take ownership of our future. Today is about not really forgetting what the past is but indeed coming together and saying to ourselves we want to have a future together. Savolu who agreed with the youth said there was a need for intergenerational dialogue to address issues that may lead to conflict proactively. While assuring of his administration's readiness to champion courses that would be beneficial to the young people, the governor promised to increase the state's investment in human capital developments. And so I take your point very seriously that human capital in health, in education, is the way to go. Commissioner for Youths and Social Development Sheru Daudu, who was represented by the permanent secretary, Dr. Uluwagwemiga Aino said rebuilding Lagos for greatness involves constructing a formidable identity to unify people of common interest for a common goal. After much of a negative conflict is never beneficial to the individual, to the society or community or the nation at large and even globally. I want every youth to know here that they can demonstrate certain efforts towards nation building and that is why we felt it, the governor of Mr. Baba Gidesong Uluwagwemiga felt it wise that it's better we sit down without this intention of blaming ourselves for what has happened to us. What we suffered within a year ago runs to millions of, or trillions of, Naira and also colossal loss of property and lives. And as a resilient society for which Lagos it is known for, we also further demonstrating here that we can lead and we can demonstrate that Lagos is truly a resilient society and that is why we have deemed it fit that those that this affects are the ones that will be the four bearers to discuss these issues and see how such will never happen again. How they will also be active participants in nation building. The consensus here is that accepts the basic demands of the youth are substantially implemented. Nigeria may never regain their trust. And the 21st edition of the 2021 National Women's Conference organized by committee of wives of Lagos state officials also held during the week, themed a week. Under state governor Rotimi Accredulou, while declaring open the conference called for more active participation of women in politics, saying men have failed to find solutions to numerous problems bedeviling the country. It is the 21st edition of the hybrid 2021 conference of the committee of wives of Lagos state officials called so. Having as a theme awake, a clarion called to join the first century women to become fully a lot of our responsibilities as a pillar, enamble and catalyst within the family. Under state governor Rotimi Accredulou declaring the conference open, beckons and women to rise up and occupy their rightful place in politics. We have had women in this country who have contributed a lot to the development of this country. We can keep on, we can name them. Remember those famous women during the Abaraians. We knew what they did. We must remember and cannot forget Margaret Epo. We cannot forget the queen herself, Fundlayos Ransom Puti.  We cannot forget Ladi Kuali and we should not lose sight of Adia Sarabha and lately Kudirat Adiola. So women have performed a week in this country and we must continue to have preceded them. So I see that when the need of these women is clear to me that there is no disabled society that can confine women to the back seats. It's not possible any longer. You can't confine women to the back seats and expect that you may progress. If this country must progress, we must move with our women. Our women must lead us to progress. Lagos State Gov. Papa Jidesawunlu emphasized the importance of women in society, especially in a home. He urged women of all ages to be bored, assertive and fearless in the quest for a truly just, equitable and inclusive society. But awake, it's not only apt, it's only appropriate, it's for you to be a lot more resilient, to be aware of your environment, to have a new approach to doing things, to ensure that you have an integral and a sustainable mindset and everything that you find your hands to do. As individuals, as organizations, as corporate entities, I think it's important for us to know that all of you, working collaboratively as partners with government, we can achieve a lot together, working in unity. And so, as your leader in government, it's important for us to listen and to know that the talks and the directions that are coming out from this year's conference today, tomorrow and next tomorrow will set a path that will believe, will help shape the tomorrow's leading from today and begin to shape the leadership role that Lagos and Calso have in our government and in the conversations of the greater Lagos. Chairman of Calso and wife of Lagos State Gov. Dr. Ibi Jidesawunlu earlier in her opening speech posited that recent security challenges facing Nigeria is a wake-up call for women to prepare themselves for the future. She charged women to stand and contribute positively to society. This conference is a platform for women not just in Lagos, but from all over the country and beyond our shores, to come together to share experiences and insights on modern day issues affecting women, men, children, youths, the home front and the society in general. This annual conference is one of the major initiatives of Calso to make a significant positive difference in society, especially in terms of greater convergence and the avenue for women to unlearn, learn and relearn in order to align with modern realities and also prepare them ahead of challenges of life. You will agree with me that with the recent aspects of kidnapping, terrorism, mandatory and other forms of violence, a convergence of this sort aimed at the future preparedness of our women is most desired. Highlights of the opening day was the presentation of the 2021 Instigration Our Women award to some members. Award was also presented to Nigerian female footballer Assisat Ushuala as the 2021 inspirational youth. That's all we have in this episode of the Greater Lagos Vision on Plus TV Africa. I'm Lovie Kuku Oyedoku. Bye for now.


What you are hearing is the sound of progress. Over 103,000 tons of debris has already been removed from homes burned in the October wildfires. To put that in perspective, 103,000 tons is the equivalent of the weight of a modern day naval aircraft carrier. In neighborhoods like Coffee Park, for example, streets are virtually blocked by the numbers of trucks and excavators hauling debris out of the area. The household hazardous removal, well ahead of schedule, over 7,000 sites now complete that's upwards of 95% of all lots. Already we've shown you progress and cleanup in Lake, Mendocino, Napa and Sonoma counties. Properties that have already been cleared now have a checklist in front of them. The goal? Check all of these boxes so that the lot can be turned back over to the homeowner. One of those boxes to check, soil sampling. We mix them all up once we pull them off each line, put them in our sample jars and then send them off to the lab. The harsh reality is the lush green hills of Napa and Sonoma counties are now a patchwork of scars from the October wildfires. Signs of destruction will be visible for years to come. But now it's a race against Mother Nature to prepare as many of these hillsides as possible to reduce potential debris flows. Some of the most visible here near the borders of Napa and Sonoma counties. These burn scars a visible reminder as to just how destructive these wildfires were. For all of us at Cal OES, I'm Brian May.


Like in many other fields, artificial intelligence and machine learning have a very important role to play in the field of media and communication as well. So in today's presentation, we'll be looking at how various newsrooms across the world have adopted some of these AI applications, what are the pitfalls of these applications, what are the changing roles of journalists and what actually is artificial intelligence and machine learning. So in the next few slides, we'll first talk about what is machine learning. So unlike science fiction, machine learning is not about machines having a brain made out of metal. It is not an artificial brain that machines are being provided. It's about training those machines to performing a single specific task according to a specified measure that the user has defined. So basically, we are training the machine into certain algorithm to predict and perform certain tasks and we'll explain what these tasks are and how that training goes off. So before we begin discussing about the machine learning applications, this is a very recent survey about what journalists feel are the most enabling technologies for journalism. And no surprises, almost 7 out of 10 journalists feel that artificial intelligence is going to play a very important role in future journalism. And of course, other technologies as 5G and there are new devices also. But artificial intelligence for a number of years have been the most important technology that journalists have been discussing. So let's talk about how AI has been used across the world in many of these newsrooms. So the Peruvian news outlet Oho Publico, for example, has a tool which can spot potential patterns of corruption in government procurement contracts. So whenever they have these contract documents, they pass it through their algorithm and they try and look for any pattern of corruption there. The BBC of course has been testing that artificial intelligence powered chatbot to answer questions about coronavirus using their own reporting resources and summaries from official sources. So this again is a very useful resource where all the answers are provided based on some very authentic evidence. The South China Morning Post is also using artificial intelligence to identify lookalike audiences so that when they want to target new subscribers, those new subscribers will be very similar to the subscribers they already have. So that's where artificial intelligence also has a very important role to perform. And of course, the Reuters news agency has used this speech-to-text technology to add time-coded transcripts to their archives of videos. So that makes the videos much more searchable and much more easier to find the key moments or anything that the researcher or the communicator wants to find out from the huge video resource beginning from 1896. So as we said in the beginning, artificial intelligence makes it possible for machines to learn from experience. So we provide data sets to machines and the more data points we provide to the machines, the better they become at predicting and performing certain tasks. So it makes machines to learn from experience and we'll find out how that experience is reinforced and all. But generally, two of the things they rely on is deep learning and natural language processing. And we'll see how natural language processing and natural language generation has a very important role to play in everyday journalism. So using some of these techniques of deep learning and natural language processing, computers can be trained to accomplish specific tasks. So we provide them with a large amount of data and they can look for patterns in that data in a matter of few seconds. So we train these machines for certain tasks and that's a very important thing. So machine learning is a branch of artificial intelligence that learns from experience as we said and this learning can take many forms. It can range learning from example, learning by analogy and at times it can be autonomous learning. But the important thing is that we are training the machine with millions of data points if possible. And when the machine is fed with newer data, it can look for the patterns it has been trained to recognize. So we first of all make the machine aware of what these patterns are and then the machine will be able to look for those patterns when we give them a fresh data set. So at its very basis, this is what machine learning is. So it's about learning some properties of a data set and applying them to new data and for that the common practice in machine learning is to split the machine learning into two sets. So for example if we provide them with 100,000 data points and we split that into two different sets, 50,000 each. The first is the training set on which we make the machine learn those data properties. So for example, we could be feeding them with thousands and thousands of images and telling them that what those images are. For example, we could be feeding them with images of different vehicles and train the machine to recognize bicycles for example. And after we have trained the machine onto those training sets, we then provide a testing set on which we ask the machine to recognize those bicycles for example. And based on the machine performance, we can streamline or we can add further data or fine tune it to recognize bicycles for example when we feed them with thousands and thousands of photographs at a later point of time. So machine learning in this sense is telling the machine to recognize these patterns or these pictures and then whenever we provide them with a new kind of a picture, the machine will be able to find that out and predict that okay this is what this image has or it can just in a matter of seconds it can tell us that okay there is a bicycle in this photograph. So there are three different processes of machine learning the first is the supervised learning where along with the training input we also tell them what these classifications are. So we tell the machine that okay this is positive and this is negative and this is neutral. So this is a supervised learning where we are telling the machine that these are the categories or these are the categories that we are training you to. So if I give them a particular word and tell them that this is positive later on it will be expected to recognize similar words as positive or similar words as neutral if we train them as neutral words. So this is known as supervised learning where we provide the machines with the categories and later on the machine can find out those categories from a larger data set. The other kind of machine learning process is the unsupervised learning. So unlike unsupervised learning we provide no labels to the learning algorithm. We let the machine find out the patterns and then you know we might give those patterns or those categories certain names but the machine itself finds out those patterns and we do not give categories or we do not train the machine into the categories that we have identified before. So we let the machine identify those hidden patterns or it can look for those categories by itself. The other point is the reinforcement where the computer program interacts with the dynamic environment. So it must perform a certain goal. So it could be like driving a vehicle or it could be playing a game against an opponent or it could be playing a chess game for example. And as it learns or as it interacts with that dynamic environment the environment which keeps changing the program is provided feedback in terms of rewards and punishment. So if it does a right thing it is rewarded if it does a wrong thing it is given a negative feedback. And when based on these feedbacks the machine reinforces or it knows that what needs to be done so this is what is reinforcement learning. So machine learning is generally of these three types the supervised learning the unsupervised learning and the reinforcement. So for the impact of artificial intelligence on newsrooms I have drawn on this book by Francisco Marconi this is a very useful book which talks about artificial intelligence and future of journalism. So generally the traditional journalism model is a linear model where the news gathering the production and the distribution process it takes in a linear fashion. But when we use algorithms then you know it could be a circular pattern or it's a lot more dynamic. So there are different ways in which artificial intelligence works in these three different processes. So we will see that in the news gathering processes we can use algorithms to mine data from the social media for example and also mine data using AI sensors. In the production part there are different ways in which we can write stories or construct stories from data using these machine learning applications. And even the distribution of content can be helped in a big way by using these AI applications. So in the next few slides we are going to talk about these processes of news production news gathering and distribution and how AI can help us in that or does help in that. So one of the first instances of automated news was from Los Angeles Times in March 17, 2014 where there was a 4.7 magnitude earthquake in Los Angeles. And within three minutes of the earthquake subsiding the first news accounts appeared on the website of Los Angeles Times. So based on data that was fed into these AI programs the program could construct a news story out of that. So that is one area where certain kind of news stories can be constructed with the help of AI applications. So the machine learning process which helps us or the AI process which helps us with writing news stories is a subset of the natural language processing. So as we know natural language processing is an application used to help computers understand the human's natural language. So one of the objectives of NLP is for computers to read, decipher, understand and make sense of the human language. And we'll see that it's not only just understanding and deciphering human language but also constructing words out of data with their knowledge of how humans interact or how humans communicate. So the traditional uses of NLP are things that we all are aware of or we might have seen in our everyday usage. So we have these language translation applications as in Google Translate. We have these processes like Microsoft Word or even Grammarly which checks the grammatical accuracy of text and that's where AI applications are used. Even in IVR applications interactive voice responses are the ones which we use to call call centers. So it's based on AI applications and based on these speech-to-text recognition. It recognizes our tone and our voice and our diction and tries to help us with that. And a lot of these personal assistant applications like Siri, Alexa, Cortana, they use natural language processing in a big way. So these are the applications that we already see in our everyday life. In the newsroom, the NLP can help us to scan huge documents. So when we have lots and lots of papers or pictures or documents and we want to find out certain kinds of words or we want to find out whether there is a pattern or whether there is some wrongdoing somewhere. So AI-driven artificial intelligence can create summaries by ranking the relevance of phrases and whether they connect with each other or whether they appear with each other and so many other analyses that can be drawn from there. So a lot of critical information can be gathered from these big documents just by using artificial intelligence applications. And one of the subset of NLP is the natural language generation. And it's the process of producing meaningful phrases and sentences in the form of natural languages. So it basically the input could be just structured data maybe in form of tables or in the earthquake example as we just saw. So we just provide them with data and they can bring out with tailor-made content in a matter of seconds. Thousands of pages in a matter of seconds and that would be somewhat like a human-like communication. And we'll see that readers are not even aware of the fact that they might be reading some content produced by an AI program. So it's so much precise. So this natural language generation has reached that level of precision where the language is very similar to what humans would write with a number of other advantages. So energy as we saw the natural language generation is just a subset of the larger natural language processing and there's also this concept of natural language understanding. So these processes are used in the newsrooms to generate stories out of data and we'll see some of these applications in the next few slides. So one of these commercial energy applications is this area and this is from their website. It says that it's a form of artificial intelligence that transforms structured data into natural language. So through this knowledge automation language generation, it can provide tailor-made content and the tailor-made means that it can be from the perspective of both teams. For example, if there is a sporting event and there are two teams there and there are supporters of these two teams who obviously don't agree on many things. So we might have content tailor-made for these two different kinds of supporters. And also it can change in terms of any other template that we might want to provide them and it can be done on a massive scale and in a matter of seconds. So it's just the matter of creating a template and providing the structured data and letting the algorithm work out. It's the magic of creating stories or creating text that makes sense and text that is tailor-made for the audience and for the time of day and something that can be updated also. So one of the things is narrative that is also an AI application. So it uses natural language generation and it can write more than 10 matches on a single day in just a matter of seconds. So the journalist's task of repetitive writing is taken care of. So the journalist doesn't have to focus on the main stories because they are generated just from the data that are provided to the AI application and it frees up the journalist to focus on analysis. So it's not that journalists are becoming redundant but it's the fact that the journalistic work is freed up from these repetitive tasks into more analytical tasks or into more soft stories or human interest kind of tasks. This is again from a narrative web page and this is where they talk about this was created in 2015 and they've been generating automatic content from any field. It could be from the field of economy, from the field of health, from the field of science, from the field of sport. So we just need to know the template that has to be created and we just have to provide the right kind of data to the AI application and it can create up those kind of stories in a matter of seconds as I said. Also AI can help us with very many different kinds of storytelling so it's not just one kind of storytelling but the same data can be used to provide these 12 different kinds of stories at the same time. So you could be getting photo galleries or you could be having timelines or you could be having short videos or you could be having VR or AR stories out of that or newsletters or even chatbots as we saw some time back. It could be a long form story, it could be listicles or it could be visualized data or data visualizations, it could be an audio experience and there could be explorable stories and even alerts and notifications. So the same data can be used in multiple ways without much of an effort. So the simple information can be provided to the consumers at a very swift rate into very many different formats and even tailor made according to their own requirements according to what they would want to read or what they would want to see. So this is a very important thing about AI applications that this can tailor made content or create content according to the readers, varying personalities and according to the location, the time of the day and so many other conditions there. BBC is already working on turning text into visual stories as suitable for mobile phones with pullcores and animations. So again the same thing providing data and harnessing technology for providing a format of a story which the end news consumer finds very relevant. And you can also provide summary of those news items and maybe even audio versions of their stories using those synthetic voices. So there are many other users of artificial intelligence as well so using new sensors for example rather than relying on government figures about how many people turned up in a meeting for example it can provide you with a more precise head count at a particular meeting. It can scan through photographs and provide you with the kind of people you are looking for or it can even provide us with causal links and correlations within data. But as I keep emphasizing the humans will always be needed. They will not be redundant because the task of human journalists will be much more different than it is in a non-AI environment. And as I said this is a very important finding by Christopher Clairwell in 2014. This was published in a journalism practice and it was found that the news audience could not distinguish between automated journalism and human journalism. And that is what drives some of these AI applications because they know that the consumers would not be able to distinguish whether it has been written by a human being or whether it has been created out of an artificial intelligence program. And as I said before it's just another tool in the journalist's armory and unlike in many places where people have been thinking even in the past when computers came a lot of people thought that journalists should be out of work or if we travel back a few centuries it was thought that even printing machines would make people lazier. But we've seen that it's just a change of culture it's a change of how we use that technology into our everyday work. So jobs that involve creativity and the jobs that involve ideation or even empathy they will not be automated. For them we will always require a human creative mind there. So artificial intelligence just accelerates the process of collecting and contextualizing data. So it provides the right context to the data and it can very swiftly collect that data as well. So now we are going to talk about how AI can help in the process of news gathering. Even in the news gathering process AI applications are extremely useful. So there is this news tracer at Reuters and it finds events that are breaking on Twitter in a matter of seconds. So it is scanning all the Twitter timelines and whenever there is an event breaking on Twitter it can trace that event and it even assigns them a newsworthiness score and also gives them a confidence score about how likely it is that those events are true. So instead of journalists scouting for information manually it is this application which helps journalists save those precious seconds in reporting the event very quickly. So it is about scanning the social media environment to find out newsworthy events giving them a newsworthiness score and also a confidence score but it has been found out that this news tracer is very good at finding out only certain kinds of events quicker than the mainstream news organizations. So there are a lot of these applications. This is from Graphics and it can take as it says it helps us develop, test and validate the hypothesis in matter of minutes. So we will be talking about many such applications. The other is the Data Miner which helps newsrooms mine data from various sources. So whenever there is a breaking news and Data Miner as they say on their website is used by 650 newsrooms around the world 24-7 to provide earliest tips on breaking news and breaking events. Then there is Factiva which does a very similar kind of thing. And there is this ICIJ which has its custom built search engine to pour over millions of documents and to classify them and find out patterns in them and to look for stories in them. So as we see that this machine learning algorithms are revolutionizing the news gathering process as well both in terms of speed and in terms of the huge volume they can handle to predict and provide insights into stories. So it is not just the news gathering process but also the distribution process and this is one study done by native and they found out that a lot of these distribution processes that that bus feed uses. So it is not only just the social media account and not just their own website but there are lots and lots of distribution channels that they can find out through these artificial intelligence applications and these applications help a news organization find out where the possible news consumers could be. Media cloud again is a very important open source platform for studying the media ecosystem. So it can allow researchers to track how the stories and ideas spread through the media. It helps us understand how when a story is out in the news environment how it finally spreads through the various media and how people are interacting with those things as well. So as we can understand there is a lot more technological help for journalists not only in finding out where the stories are or writing the stories but also the impact of the stories also. There is another application which is known as True Anthem based in San Francisco, California where they use artificial intelligence to identify the right content for the social audiences and post it to them at the right time. So identifying who are our potential consumers. As I said in the distribution part also artificial intelligence has a very important role to play in identifying who your potential consumers could be. There is this application News Whip which again tracks the impact of millions of stories and it empowers the news and communications professionals. So it tells us about the impact of the news story within a matter of seconds and predict whether it will have an impact for a certain kind of audience also. So as we talk about the positives of artificial intelligence very important to understand the question of ethics there and the question of responsibility because if we treat artificial intelligence as just a black box where certain kinds of information goes in and then we get out certain information out of that then there will be a problem. So this question of transparency and the explainability of algorithms explaining people how a certain algorithm was built up and what kind of training data was used there and what are the methodological issues involved there what are the questions of algorithmic errors or bias. So all these things have to be disclosed to the end user or to the larger academic and the communication fraternity. So there are many things or many kinds of jobs that will come up with the new applications and one of them is that of automation editors. So as we've discussed about these natural language generation it's important to create certain kinds of templates. So these automation editors would write these templates and even think about the branches or the possible variation in terms of audience and in terms of location in terms of time and all that. So that template has to be humanly decided by these automation editors. They would create these templates and then use the AI applications to create content but this template has to be a dynamic process and it has to be done by a human and after those stories are generated if there is any additional information required or if there is any additional explanation required that also has to be done by the automation editor. So although the AI applications speed up the machine learning speed up the news creation process there are a lot of things that journalists will still have to do. Also there will be a new class of data journalists whose job would be to run sophisticated analysis on available data using all the traditional means of data science and to collaborate with reporters who have domain expertise in a specific area of coverage to make sense of that kind of data. So these kind of data journalists and local reporter teams will become even more common in days to come. As we said these ethical questions are extremely important and Kathy O'Neill brilliantly summarized it by suggesting that algorithms are opinions embedded in code. So as we saw at the beginning that when we are talking of algorithms we are talking of training machine learning programs using human coders to identify certain patterns or even tell them that what those patterns mean. So there is always an element of opinion involved in these algorithmic processes. So it's important for us to bring these things to the forefront as journalists and as communicators and even as people who are using these AI applications about these algorithmic decisions, about what does the algorithm do. So not taking algorithms just as a black box but explaining all these questions about category. What does it do? What was its goal? What was it trying to maximize its time on? What data was the algorithm based on? And is this made clear to people who have been using it and people whose data have been used? Is there an oversight by humans to make decisions and tweak the algorithm? If the algorithm is not doing well, so whether there is a human element there as well and as we explained earlier whether it's explainable and whether it is interpretable and whether how errors are taken care of under all such things. One of the problems with artificial intelligence is this problem of deep fake where these images or audio files are altered with the help of AI applications to dupe an audience into thinking that they're real. So we could be having someone else speaking something else and it is not even observable and people can't even make out what reality is. So these problems of deep fake are real and we have these open source systems like Deep Face Lab where you can use face swapping for example to make someone else say something which they didn't say in the first place. So there are lots of these examples. Channel 4 for example created a queen lookalike recently to deliver an alternative Christmas message wearing a coronavirus-shaped bruise and making jokes about the members of our own family. And Synthesis even released a deep fake Santa that delivered personalized greetings. So this AI in communication is not only just for applications but also in the theoretical field there will be a lot more changes because most of our communication theories are about humans as subjects humans as subjects of communication. But when we have AI devices where machine subjects who are doing the communication or people are communicating with machines rather than through machines so that's where a lot of these communication theories will also have to be re-looked. Thank you very much for your patience and thank you for joining in.


If you guys need my time, I can't reach them here. If I turn to the side, I can reach them. So this side kick is used for a long distance. Especially if you have time, the guy is coming out from the way he seems coming away. And I can reach him. But if he's really close, then I don't... Then this is better because he's already close.


Most of this information comes from the tax guide for small business for individuals who use Schedule C, Publication 334 Tax Year 2022, you can find on the IRS website, irs.gov, irs.gov. Looking at the income tax formula, we're focused on line one income. Remember, in the first half of the income tax formula is an essence and income statement, but just to outline other forms and schedules flowing into these line items, one of those being the Schedule C, it having business income minus business expenses, the net business income then flowing in from the Schedule C to line one income of our income tax formula. First page of the form 1040 noting that the Schedule C generally flows into the Schedule 1, which generally flows into page one 1040 line number 8. The Schedule C is the profit or loss from business having an income statement format income minus expenses were focused here on the expense side of things and in particular the de minimis safe harbor for tangible property. So generally you must capitalize costs to acquire or produce real or tangible personal property used in your trade or business such as building equipment or furniture. However, if you elect to use the de minimis safe harbor for tangible property, you may deduct de minimis amounts paid to acquire or produce certain tangible property if these amounts are deducted by you for financial accounting purposes or in keeping your books and records. In other words, let's think about this just from a bookkeeping standpoint. You might have an expense account for supplies or an expense account for repairs and maintenance and you might run across some items where the question comes into your mind as to whether you can just expense these items when you purchase them or do you have to put them on the books as an asset in which case you would generally have to be allocating the cost over the useful life. Now from an accounting standpoint that's an accrual kind of question meaning did you consume the expense in the current time frame? If you did then it would be just an expense meaning if you bought these supplies and you used the supplies in the current time frame you would think that would be an expense same with like a repairs and maintenance type of situation but if you're purchasing something that's going to be consumed for multiple periods into the future you would think then from an accounting standpoint you would put it on the books as an asset and then depreciate it basically over its useful life. However, we can think of things that we're going to do that with that are still pretty small in terms of dollar amount so you might think yeah I bought like five years supplies of paper clips or something like that it's still pretty small in terms of dollar amount so is it really worth our time to do the more complex thing of putting it on the books as an asset and then allocating the cost over its useful life even though technically I would be using it over a long period of time so many purchases that are that are low in dollar amount even if you plan on using them for a long period of time you might be saying hey look it's not worth my time to put it on the books and capitalize it because it's in essence immaterial it's a small amount compared to my total income it's not going to have a big impact on my financial decision making and in this case on the taxes so you have a similar kind of concept here now you might be thinking hey look I'm on a cash-based method and you're talking about this accrual stuff it doesn't matter to me at all because I'm cash-based but even if you're on a cash-based system we know the tax code is going to force you to deviate from the cash-based system for large pieces of equipment and you're still going to have to put them on the books as an asset so if you buy like a forklift or something you can't just expense forklift expense typically you have to put it on the books as an asset and then use the depreciation methods to depreciate it now the thing that's kind of weird about the tax code right now is that you end up in the same spot oftentimes because if you just expense like a big piece of equipment like a like you know a forklift or a piece of office equipment that's a big piece of equipment then you would get the expense in the current time period if you're forced to capitalize it then you're going to put it on the books as an asset that you would normally depreciate over its useful life like five or seven years but they currently have the 179 deductions and and the special depreciation which may still allow you to in essence take the expense upfront so you might say well what's the point you end up in the same spot either way possibly and that might be true but the concept here is that is that do you have to put something on the books as just an expense or do you have to put it on the books as a depreciable item in the future it's likely that the tax code might change like the 179 and special depreciations because those are typically distortions that are used to stimulate the economy however it's unpopular to remove those items so you'll think they might not do it but we're in a stage where the economy is kind of overheating so you would think if it if things were running right they would actually reduce those you know at this point in time but it's not popular to do politically so it's kind of an interesting situation


When we compute a rate of change, we should also compute the units. And if we're looking for a quantity, we can use dimensional analysis to help us decide what we want to find. For example, suppose the height of an object is given by some function, and this is in meters t seconds after an experiment begins, and we want to find out how rapidly was the object moving after 6 seconds. And so we find h of 6. Now, since h of t is measured in meters, then h of 6 will also be measured in meters. Now, before we box in this answer and turn in our work, let's remember something useful. Read your answer out loud with the question. And so here the question, how rapidly was the object moving after 6 seconds? The answer, 138 meters? And it's important to recognize that this answer of 138 meters doesn't really answer the question, how rapidly. So even if this number is correct, it's not an answer to our question. Well, this is calculus, and we don't have too many other things we can do. So what if we find the derivative at 6? Now, here's where differential notation is useful. This h prime of t, well, that's dh dt. And remember, the change in a quantity has the same units as the quantity. So dh, well, that represents a change in h, but h is measured in meters. So dh is also measured in meters. dt represents a change in t, our time, and since our time is measured in seconds, dt is also measured in seconds. And so while it might not be clear what the units of h prime of t are, the units of dh dt will be meters over seconds. And so let's say we go to the trouble and find h prime of 6. We find it's equal to... numerically, it's 4, and we know the units are meters per second. And so h prime of 6 is 4 meters per second. And again, we can gain some useful insight if we read our answer out loud with the question, how rapidly is the object moving after 6 seconds, 4 meters per second? And the important thing here is that 4 meters per second does sound like it could be an answer to our question. Now in the previous problem, it happened to be that our derivative was the velocity of the object. But keep in mind that this is only because our function gave us distance. Do not make the mistake of assuming that first derivative is velocity, second derivative is acceleration. That is almost never true. Outside of cases where the problem is constructed to make it true, it's always better to compute the units and figure things out for yourself. So here, v of t is a velocity in meters per second. t seconds after the experiment begins. Let's find the units of v prime of t and decide what v prime of t represents. Again, our differential notation is useful. v prime of t is dv dt. And so our units... dv is a change in velocity. So its unit will be the same as velocity, meters per second. dt is a change in time, so its unit will be seconds. And if we clean up the algebra, the units of our derivative will be meters per second squared. So v prime of t is an acceleration. So for example, suppose the distance an object travels is given by some function in meters. t seconds after an experiment begins. What's the acceleration of the object after three seconds? So we could find s of three, which will give us an answer in meters, but this doesn't answer the question. Acceleration is not answered in meters. We could find s prime of three. So again, we find s prime of t. That's really ds dt. And so our units will be... And so s prime of three will give us an answer in meters per second, and this is not an acceleration, so this still doesn't answer the question. However, s prime of t will be a velocity. Now we'll call it v of t, and we can actually find that derivative. And so now we have a function for our velocity. And notice that v prime of t has units... Well again, it's dv dt. v is measured in meters per second, and so v prime will have units of meters per second squared, which will be an acceleration. So let's find v prime of t, and so v prime of three is two meters per second squared.


Appalachian Wireless proudly brings you unlimited data. Unlimited data is only $80 a month for a single line. Four lines as low as $200. Better service? Bigger savings? That's today's Appalachian Wireless. An East Kentucky network company. Get a speed slow to 25 gigabytes per line to 512 kilobits for phones and tablets. And 15 gigabytes for motors. See store for more details. Business and community leaders from across eastern Kentucky gathered today in Pikeville to brainstorm ideas for a regional branding initiative. Officials with Pride recently announced the receipt of an ARC technical assistance grant and they are using it to see how best to market the region. We want to bring people here to the region and keep them here in the region as a whole. So that's the branding initiative. We're not really looking for a logo out of this. We're just interested in telling our story, bragging on what we have here in southern and eastern Kentucky. Pride retained Steve Chandler as a consultant for the project and for the past two days two different teams have toured the region, hosting six town hall meetings to discuss how to bring people to eastern Kentucky. And we're not here trying to remake the wheel either. We're just trying to put a platform out to bring more folks together across the region. I think the conversations are already there. We're just trying to expand them some. In addition to local business leaders attending today's meeting, several tourism officials also traveled to Pikeville and Pike County Tourism and CVB Executive Director Tony Tackett says he's pleased to see a true regional effort to promote the area. Today you'll see a tourism director traveling from Ashland, Kentucky to be in Pikeville today for this meeting. You'll see people traveling from Hazard. You'll see people traveling from our capital in Frankfurt just to make sure that we are tying the shoestrings for a better tomorrow for these visitors. Following Pikeville's meeting this morning, the final two town hall meetings were held at Natural Bridge State Park and in Hazard. In Pikeville, I'm Shannon Deskins, EKB News.