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Hi friends welcome to my channel and welcome to yet another interesting video wherein I'm going to talk about how you can clear the TGTPGT exam in just the first attempt. Sounds amazing right? So in this video I'm going to talk about how you should start, what are the things that you should keep in mind when you're beginning your preparation for TGTPGT exam and finally towards the end of the video I'm going to give you some really amazing and really important bonus tips on mistakes that you should avoid making while you are preparing for the examination. So make sure you watch the video till the end. If you're new to this channel then please hit the subscribe button and press the bell icon as well so that you never miss an update. We're proud to share that we are India's largest growing YouTube channel in the field of UGC net and TGTPGT examination right now having the maximum number of subscribers. So let us begin by talking about point number one which is very crucial and it is to not take the exam lightly. The TGTPGT exam as I have discussed in my multiple videos has two basic sections grammar and literature. Both of them have equal weightage. Now one problem that I've seen with many students is that they leave out the section which they think they are weak in. Some who are weak in grammar they leave it out and slowly focus on literature. While the reverse is true for those who are weak in literature. However at this point I would like to tell you one thing. Please don't leave any topic. You need to understand that when you score well in both the sections in this exam then only you'll be able to clear it. You cannot rely on 50% of the syllabus and hope to clear the exam because the cut off itself usually goes very high. Don't fall in the midst that since this exam has limited syllabus and no negative marking hence it is a very very easy exam to clear. If you are feeling this way then there are many other aspirants who are feeling the same way and this is where the competition gets really tough because an exam that seems easy for all in the end becomes the most difficult one to clear. That is because generally in such exams the cut off goes very high and only those who had worked hard even for an easy exam would be able to clear it. Many times students tell me that some topics only come for 10 marks in the paper. So is there any need to study them in so much detail because they're just carrying 10 marks. I would like to ask you a simple question. Can you afford to lose even a single mark in TGTPGT exam? No right? This is the reason why I'm saying that every single mark matters. So your target should be to attempt all the questions with the best of your ability. It is only when you attempt 100% of the questions you will have a scope of plus minus 10% which can be due to silly mistakes but still by large you'll be able to secure 90% marks and you will be at a comfortable clearing position. It is just like that famous proverb shoot for the moons at least even if you miss you land amongst the star. Hence in this exam situation aim for 100 marks despite the difficulty level and you will be able to secure 90 marks on the final day. Now we move on to point number two which is very crucial. It is a differentiating factor between those who clear this exam and those who fail to do it. The point number two is to make smart study strategy. Telling you in all sincerity only hard work doesn't guarantee success. You need to adapt smart work. Smart work is what separates you from others. So let me explain hard work to you. Hard work is when you have a TGTPGT guidebook of about 400 pages and you mark it up cover to cover. This is hard work but is it possible? Will you have so much time to mark up the entire book? Will you be able to revise and remember the entire book? A definite no is the answer as we all know. So here what you need is a smart strategy with guides on what to read and in how much detail. You cannot solely rely on topics that they have mentioned in the syllabus because they haven't specified all the topics in the syllabus. They have not mentioned which works of the author are to be studied and in what depth. For example Wordsworth has spent down around 100-150 poems but only seven or eight of them are asked in much detail when it comes to TGTPGT exam. Whereas 15 to 20 poems can be dealt with by only studying the title and certain keywords and important facts. So it will be a waste of time for anybody who attempts to study the remaining 130 poems. First case first it is an impossible task and even if someone is able to study 130 poems Woody or she will be able to retain and recall such amount of information and let me tell you it is not just one writer we are talking about there are around 25 to 30 writers who are asked in TGTPGT exams. So always ensure that you adapt a smart study approach. The first step of a smart study approach is to thoroughly go through the syllabus. The next step that you have to take is to look at the previous year questions. You can find all the previous year TGTPGT papers on our website arpathakarwa.com available free of cost along with the answer keys. So as I was discussing the second step is to analyze the past year papers and sort every question according to topic or the writer and only after that you will be finally have a list which will be useful in analyzing the various questions that have been asked related to a particular writer or a particular work in last 10 years. Now once you have made that list you can decide to give what amount of importance to which topic writer or work and also take a call to skip certain topics from which questions haven't been asked. Now this entire thing is a 30-40 hour long process because analyzing the past year papers then segregating them according to different parameters isn't a easy task. However we have simplified this task for you with our online mock test series in which we provide you topic-wise segregated previous year questions and other practice questions so that once you have studied the topic you can directly jump to the questions and see how much you have prepared and where do you stand in terms of the topic. We have just released separate video course also for TGTPGT exam. We proud to announce that we are the only institute in India that teaches through animated video lectures. Our videos are designed using 3D animation and graphic which enhance the visual memory of the students so that they are able to retain the complicated summaries of novels, plays and poems easily and recall it effectively during the exam. In our online course we provide you with topic-wise video lessons with rich animations covering all topics in a step-by-step manner which works even when you have not done any previous preparation. We also provide you high quality PDF and revision notes that covers syllabus-wise topics comprehensively and ensure you qualify your dream exam in just one attempt. Also another very important reason to analyze the previous year papers of TGT is that many times questions are repeated in the following years with just a bit of modification in the language but by and large the questions remains the same so analyzing past year papers will directly hand you the advantage of knowing those 5 to 10 questions. So let me now summarize the smart study strategy in three simple steps. The first step is to know the syllabus. The second step is to analyze the past year papers and sort the topics from which questions are being asked and the third is to finally study those topics from either a guidebook or some YouTube videos or using any online platform like Google. Now we come on to the third important point which is revision. So I will tell you my students don't wait for course completion jump directly to revision. What does this mean? Let me explain. There are a variety of people attempting the TGT-PGT exam be it college students working professionals or housewives. All these people are tied up and have a pretty strict schedule. They do complain that they hardly get time to complete the syllabus and here I am stressing on revision. I would even go ahead and emphasize that revision is more important than completing the actual syllabus. You might find my words a little absurd but this is the fact that revision is actually very very very important. Let me give you a real life example which tells the important of revision. One of my cousin recently gave sat exam and in the exam he made two silly mistakes which were related to the simple formula of mean and median. Though he had studied so much for this exam yet he forgot this basic formula only because he forgot to revise the formula at the last moment. This lack of revision costed him four marks because of which he could not clear the exam. Many times while attempting the exam you will see many questions familiar to you. You'll be like, this was a lesson but still you won't be able to solve it since you did not revise it properly. Similarly some questions might have such close options that you'll get confused and the basic reason behind such situation is lack of revision. That's why I'm emphasizing and requesting you all to not wait for course completion and rather focus on revision on a regular basis. A simple method to ensure that you revise every day is divide your study slot of four hours into sections. Three hours you should devote to studying the material and one hour you should solely devote every day to revise what you studied yesterday. Always do remember that every day you are reading and absorbing information regarding different writers and works. However this information will not consolidate unless and until you have done multiple revisions. Another point to add here is that most of the students move away from revision or they shy away from revision because they feel uncomfortable when they are revising. They have this feeling that they know nothing as they'll not be able to remember anything when they revise for the first time. So you'll not remember anything on the first revision cycle but always remember that success happens outside the comfort zone. You're feeling uncomfortable right now as you've just started the process. However once you revise your notes for the first time you will be far more comfortable in the next revision cycle. I'm sure many of the gym freaks out there would agree with my point. The first day at the gym seems the hardest and the most uncomfortable one but after 20-25 days you feel more and more comfortable as your body starts supporting you in the routine. Similarly the first revision will feel mentally exhausting but you do not run away for it. With subsequent revision you will get comfortable and you will eventually start enjoying the process. Also keep in mind that too much new information before the exam won't help you clear the exam as you won't be able to retain and recall it. If you really want to test this study one topic today and give a test on it tomorrow you will hardly be able to recall anything without revision tomorrow. Similarly the topic you've read way before and haven't revised won't help you unless you revise. That is the reason why I'm advising you to not pick up any new topic last kid 10-15 days. Whatever you've read do multiple revisions of it so that you can at least earn the reward for the topic that you've studied hard. I always tell this analogy to my students regarding revision. Imagine a bucket with a hole in it. What will happen if you keep pouring water into it? It will never get filled right?  Hence you need to do revision so that you can close the hole and you can retain the information. Now that we are almost towards the end of the video I want to give you all some bonus tips on what mistakes you should avoid doing. But before we move ahead a small reminder if you have any other questions or doubts about UGC net paper one, paper two, MA entrance, PhD entrance, TGTPGT or any other competitive exam related to English literature then feel free to reach out to us on WhatsApp. The WhatsApp number is flashed right on the screen. You can shoot a WhatsApp message on the same number to regularly get important updates related to latest exam notification. Syllabus change and much more. And if you are searching for free study material on various topics related to UGC net or TGTPGT then feel free to ping us on WhatsApp and my team will be more than happy to assist you. So let's now quickly move on to the bonus tips. The first bonus tip is to avoid skipping any topic of the syllabus. Many times you are too afraid to study a topic and you comfortably skip it from your preparation. Many students are afraid of data interpretation, are afraid of math, so they leave this portion before the exam. Rather you should give time and invest some effort towards such a topic and trust me there is no topic which you can't understand. I always tell my students face the fear and fear will go. The second bonus tip is related to another type of mistakes that students make which is to go overboard and become over ambitious. They start studying every topic in a way more detailed way than it is required. For example if they pick up Shakespeare and his works they will do nothing but study Shakespeare for next 15 days. This approach also hampers your preparation as you are forced to skip many other important topics due to lack of time and eventually the syllabus is never complete. To tackle this situation you need to make a reverse engineering timetable. Count back the number of days left from the exam date to present. Calculate the number of hours you devote every day and then accordingly allocate time to each topic in your syllabus. Your aim should be to cover all the topics in limited time. The third bonus tip revolves around the third mistake that usually students make which is not analyzing their mock test. For example if an aspirant gives TGDPGT mock test and scores around 50 out of 100 in the mock test they usually don't pay any heed to why they lost 50 marks. However if you are able to decode the lost marks and the reasons be it silly mistakes or topics on which you have a weak command on then only you will be able to score better in the next mock. Mock after mock isn't what you should follow.  One more point I want to mention here is that many students do not recognize the kind of mistakes they are repeating on a regular basis. They don't keep track of the repetitive mistakes. Just like Ishaan and Tare's Amipur we are also having the same pattern of committing the same error. Now it's time that you become Amir Khan recognize the pattern of your mistake and work on it. So these were some tips and tricks from my side. I'm quite eager to know how you felt about this video. Did you like it? Not like it? Did you find it helpful? Please share your views in the comments below. Also if you have any questions any queries or if you want me to make a video on any other topic then also feel free to put that in the comment section below. That's it from my side from this video lecture. I'll meet you very soon in the next video lecture till the time we meet next. Happy learning. Keep loving literature and stay tuned to arpitakarwa.com


So I'm Sarah Marcellus Luganville and I'm Scott Luganville. Hi I'm Jennifer Chickering and I'm Patrick Hoffman. My name is Eliana Rios. I am Juan Rios and we serve at First Richardson. I am the associate pastor at First United Methodist Church Salina. And I'm another pastor who serves at First United Methodist Church at Salina. And I currently serve at Arapaho United Methodist Church. And my last appointment was at Castle Linda UMC. And we've been married 14 years. And we have been married for seven years. And we have been married almost eight years now with me. See? Told ya. It was kind of on accident. On the phone. All right I'll talk to you later. Love you, bye. And I was like. Thanks. Can't take that back. Okay. So yeah I said I love you first um although it was first I really really really really care about you. Yes. And then it was eventually then you know not sort of gnawing after that it was I love you. Yes so it was funny because we were on the phone really really late when I was actually February 16th. When we had landlines. We had landlines. And he was falling asleep on the phone um and I whispered it and I was like I think I'm in love with you. And I really thought it was a sleep and he was it. And I responded and I said I love you too. Sarah put an arrow. A lot to do. Yeah between me having to brush out my hair and you trying to figure out what to wear. Work to wear. We both do. But if I'm gonna put my makeup on it's me. Very sweet. And you're right about yours. It's also a deacon answer though. It's me. It's also a chewy answer. That's fair. Loving people. Yeah she she like I said she loves hard and there's just something about the way that she loves people that attracts a lot of people towards her. And uh I think that's a I think that's a it's a gift. You ready? That's not it. I'm Samson. Come on. Thomas because you're always always questioning. Like looking critically in a good way. Strong Samson no arms. You are. Come on. Yeah. You used to have a lot of hair too. I did. Long hair. Okay. Ready? Uh huh. Yeah. James. Yes. I mean all the disciples are basically interchangeable. Are they really though?  I'm pretty sure that's a little bit. That part. Yes. It might have been a little bit harder but James. You have a really good sense of justice even though you're not a deacon. I appreciate that. You know because we're all called to the same. That's right. That's right. Yeah that's right. I appreciate that. And Thomas because you doubt too much. I I try to ask good questions. Oh yes. I'm doubtful. Questions. So I knew it was I knew he was gonna write Jeremiah because of like the fire and everything and just mm-hmm. Yeah. He always says it but honestly if we're being real it's Jesus because of the hair. Just say it. At a restaurant. At a restaurant. Talk about the weekend. Yeah. Without kids. That's where we are in life. That's where we're at. We breakfast. A lot of Friday. A lot of Friday breakfast or brunch dates. Yeah. When the kids are still in school. Yeah. On our own day off. Yep. Yep. My parents actually we went down to. Orlando. Orlando for Christmas and my parents agreed to watch the kids so we could have time at the theme park without them and like our arms feel so much later that time. Yeah. Yeah. Eat food and then end it up at Bucky's. It's the way it goes. It's always like it doesn't matter our date night. Usually good system. We're fancy night and at the end of it's like hey um how about we drive out to Bucky's for coffee or something. Yeah literally. I think everything everything all the time ends up at Bucky's. Me. Because you're the one that's usually wrong. Yeah. I put more often. See I knew she was gonna say that. It's probably true. It's usually pretty good. Yeah. Going going back and forth. Yeah. Depends on what it is. Like I'm sorry for agreeing to do it. 100% I ain't even gonna lie. Oh yeah. She has admitted for it being difficult for her to say I'm sorry. It is. I don't mind. I can say I'm sorry. It is. It is. Should I guess that one? I said incorrect idioms in public. Forget someone's name. Forget someone's name. So one of my if he's turned into my favorite one of my favorite things about Scott is he's terrible at idioms like he can't get him. You can't. They're my idioms. Yeah, they're not like does a one does a one-legged duck swim around in a pond. No, in a circle. Anyways, people in Texas don't even know that one. But anyways, do they? Yeah. No. Is that just a Louisiana idiom? Yeah, I think so. But anyways, yes, I don't have good idioms. But I do. It's endearing now. What did you say? I said the day after Christmas Eve, my spouse slash associate pastor got the flu and then our daughter got sick on the car ride to church and I had to preach someone else's sermon which it was your sermon. It was your sermon. I had to preach your sermon. I think it's more funny that you fell off the golf cart at Bridgeport. Yeah, that was pretty funny too. Golf cart. Maggie Procik was driving and we were about to be hit with a water balloon. I know the hose. You had the water balloons. Oh, that's right. We had the water balloons and someone turned it was about to turn a hose on us and she took evasive maneuvers without waiting to see if I was ready and I was on the back of the cart and I slid off along with all of the water balloons that we had armed ourselves with so. On the black top. On the black top. Yes. It's quite amusing. It was very funny. It was actually. It was funny and after the fact it was painful in the moment and I of course forgiven Maggie for for this so. I don't know. She shouldn't feel guilty about it. I don't know if she's forgiven herself though. Probably not so Maggie for listening to this. All is forgiven. I don't bear any grudges. I promise. Okay. Oh my goodness. Oh my goodness. Yes. Okay. So when I was serving at uh Lake Highlands UMC at the at the new room working with Pastor Norman um he was involved in a car accident. That's not funny. That's not funny. Sorry Norman. Sorry. With his accent over the phone and he was kind of frantic. He said Juan I need you to get all the co he said I need you to get all the cones you can all the cones you can and come find me and I said okay okay so I went into the pantry and loaded the car with not the car. Not the car. It was a van. I loaded it up with cans of corn and I got there and he said where are the cones? I said you asked for the corn. He said no I asked for cones. Traffic cones. Not cans of corn. No I don't know. I think maybe this is it. I don't know but this is this is how the line goes but I don't remember. Okay I said first John got his love.  Oh that's a good one too. Well now I guess we'll go back and look. We don't have we didn't have any program from our wedding. Nothing. We got married on the beach. Beach. So close family. Just hanging out barefooted. Ralph Ford. Yeah Ralph Ford. He said something but he said some really good things. That's just some really good things. It's like the shortest best wedding ever. It was. And now here we are. We both yeah Romans. Romans something. I thought it was Romans 12. I don't know. Yeah it was a passage from Romans. Yeah. Romans something. I think I put yours on something. Maybe not Romans 12. Something in Romans. It was the one that had to do with justice and like doing good in the world and what we wanted are what we aspire to be as a couple and how we aspire to be as a clergy couple and raise our children to be you know it might be like important for us to go to scripture about that though. Yeah probably. Maybe. I don't know it was in Romans. It was. Yeah we both remember that. Yeah it definitely was not. It wasn't a traditional. Traditional. A wedding scripture for sure. What you wrote. I wrote that I don't remember. I was feeling way too many feelings. Yeah our wedding was a little crazy. It was. It was beautiful. We got married at the old red museum in downtown Dallas on the third floor and the sun was just beaming. It was very majestic. It was gorgeous. I was just feeling emotions. It it yeah but I know that it was the I don't know why like I want to say I don't know it was probably I don't remember. Martha thanks for officiating it because thank you for marrying us. I'm sure you have your sermon notes somewhere girl but thank you I love you.  Here we are. I mean yeah really eight years later so love you. Happy Valentine's Day. Happy Valentine's Day. Happy Valentine's Day.


Felly, mae'n iawn i gweithio i gweithio i'r oedden nhw. Mae'n gweithio i'r ystafell, yma o'ch gweithio i ddim yn meddylu a meddylu'n meddylu i gael ymwneud i'r torso o gael ymddiadau ymlaen, mae'n hynny'n ei gweithio i drwy ffrinsiaid yma. Ddwy'n ffrinsiaid, Ben Procter. Ddodd yn fwy. Ddw i'n sgwrdd? Ddodd yn fwy. Fy yw'n mwy. Ddwy'n fwy. Ddwy'n fwy. Ddwy'n fwy. I was born and bred I'm going to to the ground I was born and bred with the record of having travelled the least distance to come to the EMF camp. This is me.  Then you think that just as the talk approaches you think how arrogant is it that I can explain to you how the internet has changed a bit. This is my word, this is my defence, this is my perspective. I'm basically a general purpose so I'm going to have a little bit of discussion i'r bwnaeth neu ei ddechrau. Yn dweud yw'r bwnaeth i'r llun o'r bwnaeth? Yn y gallwn ni'n gofynio, ydych chi'n dweud y gallwn i'r gweithio cyhoeddus cyhoedd yn gwneud yn fwyaf. Rwy'n gweithio'r bwnaeth yn ffynig ac yn y gweithio, yw'r bwnaeth, rydych chi'n dweud. Rwy'n arddangos i chi'n gweithio. Ond ychydig iawn i'r bwnaeth i'r bwnaeth i'r bwnaeth yn y llaw. A byddwn i'n meddwl yng Nghymru. Mae hynny'n rhaid i'w ddweud, mae'n dweud o'r rhaid i'n dweudol ar ein hirio ac arall, o'r dweud o'r amddangos a'r rhaid i'w ddoedd yn hwnnw i ddim yn ymddangos, oherwydd ffordd, oedol, oedd o'r gynllunau o'r dweud o'r dweud o'r dweud o'r dweud o'r dweud o'r dweud, oherwydd a'n gofio'n mynd i'w ddweud â'r dweud, oherwydd mae'n gofio'n ac yn ddyweddoli'r ystod y cyfnod. Felly, mae'r ddweud o hynny'n three o'r ddweud yn dweud i'r hynny, oedd y gweithio'r internet oed yn rhoi bod yn ddweud mewn hynny. Mae'r ddweud o'r ddweud o'r maeth. Felly, rydyn ni'n gwybod bod rydyn ni'n gweithio'r maeth oherwydd rydyn ni'n eitio'r maeth oherwydd ymddangos, maffi wneud yn ymgyrch gyda'r cyfnodau hynny oedd yma'r gwneud yn ddigonol. Ond rwy'n meddwl, y maffi yma ar y dyfodol yma yn 2010, byddwn yn y gwir yma'r gweithio yma a'r gwneud yma'r cyfnod yma i'r cynhyrch mewn cyfnodol. Ac mae'n gynhyrch ar y cyfrifiadol yn maffio i gyfnodol. Felly we had the internet, which was a good start. We also had a system called OpenStreetMap. Hands up if you are familiar with OpenStreetMap. Almost everybody, that's great. So that's a wiki for maps which started in 2004 and its original intention was to provide a licence-free alternative to state mapping which was usually locked up and expensive, but very quickly people who got involved in that said, well this could be really useful in emergency response humanitarian work. So there had been a long drive to make use of it. And there had been OpenStreetMap deployments around humanitarian stuff before this point. What was really different here I think was this was very significantly reported in America. So for all sorts of reasons this got a lot of attention in the US. And so you have now OpenStreetMap which is kind of available and ready to be used for mapping in disaster zones. And then you have Americans who have a lot of data that could be useful for suddenly paying attention to what's going on in Haiti. So these people are search and rescue teams. After an earthquake one of the first things that happens is search and rescue teams from around the world get on planes and they just fly into the area. And at this point when they fly into Port-au-Prince it's in Haiti which is incredibly poorly mapped. The developing world is incredibly poorly mapped. So it's not necessarily that big a deal because if there's a collapsed building you can go and start digging in it. But how do you know whether you're digging in the right place, how do you coordinate with a load of other teams, all of whom are from outside of Haiti and don't know the names of the streets or so maps are a really crucial way to communicate. But like I say Haiti is very poorly mapped. But because the Port-au-Prince earthquake, I've got a clicker but it doesn't seem to be clicking, sort of caught the attention of I think a lot of Americans. There was a sudden explosion around the world of people saying let's get on to OpenStreetMap and let's start building a map on the fly so that people have some data there. So you have these crisis camps often in universities, they happen around the world. At the time I think we were really proud that there may have been a thousand people involved in this sort of mapping action which seemed like in 2010 that seemed like wow how many people now the OpenStreetMap community can mobilise that sort of number just like that. And then what you got on the ground was over the course of days, that's 10th of January, that's basically what appeared on OpenStreetMap and Google Maps was very similar and then by 12th of January you start to get that more and then by the 5th of February you get like proper hard really really high quality mapping. And there were some other things like it's not just OpenStreetMap, there's a long standing group called Map Action who actually fly into disaster zones and start to generate maps for people like having the mapping data in the internet isn't sufficient, you need to get it into the hands of people on the ground. But really from this point I think the humanitarian world woke up to the fact that there was this amazing source of data and they started to make a lot more use of it, demand a lot more, so this was Typhoon Haiyan which was one of a couple of typhoons that threatened the Philippines in short order and each of these squares is a change set so it's basically an edit that's been made to the map. These were edits that were made in the days leading up to Haiyan hitting the Philippines and by 2013 this had become kind of a normal response of the OpenStreetMap community that where a hurricane or a disaster threatened they would get online and they would start building a map so that they didn't have to do it after the fact they could do it, it would be there available from that moment. But even then that's a kind of limited value because you're still doing it in the last minute, you're remote, you don't know what the names of the streets are from a satellite, you can see that there is a street but you don't know what it's called. And so the community has now moved into this really excellent project and if you've got any interest in this area helping out with missing maps is like the best thing you could do. And essentially it started with British Red Cross, American Red Cross and Metsans en Frontier and they've identified high-risk areas that are poorly mapped and they're encouraging the community to get out there and map them early and they partner with people on the ground which is partly for practical reasons so people on the ground can go round and tell you what buildings are called, what the names of streets are but also there's a potential ethical problem with a load of people sitting in the west with satellites paid for by the west creating maps of other people's countries and so the more we can do to engage people on the ground the better. So missing maps is a great project and now OpenStreetMap really is the best mapping for much of the world. So this is a city in Tanzania, I don't know anything about Tanzania, I just thought I'd pick a city. You'll see that Google Maps actually has a reasonable amount of data about that city but there's a lot more granular data in OpenStreetMap and that's pretty common wherever you go across the world and this is roughly the same view in two different renders. So one of the beautiful things about OpenStreetMap is you get hold of the actual data so you can create your own maps for your own purposes. So the bottom is the standard map which you would just see on OpenStreetMap. The top right hand corner is a humanitarian map so it's designed for use in disaster response so you'll see that there are different buildings show up so pharmacies show up and the humanitarian map where they don't show up in the standard map. The colours are designed to use less printer ink when you print them out and also to enable you to annotate on top of them and Search and Rescue is kind of where it came from and is the most dramatic use of this but I've heard people from Metons on Frontier say OpenStreetMap has saved countless, genuinely countless lives for things like cholera control because when people come into a clinic and they have cholera you need to find out where they're from and if you haven't got a map they'll say I'm from that village over there if someone else comes in and says they're from a different village is that just a different name for the same village? Is it in the same place? Is it down street? Without a map tracing things like cholera outbreaks is incredibly difficult with a map it gets a lot easier I put this in just to show that it's not just maps so despite my enthusiasm for humanitarian OpenStreetMap team I volunteer for a different group and we essentially try and put data on top of the maps that OpenStreetMap had built This was a project we ran with the World Bank in 2015 after TC PAM had hit Vanuatu Vanuatu was a really remote set of Pacific Islands essentially and Tropical Cyclone went through several of the islands and did an awful lot of damage One of the things I did not know about international humanitarian response is the first people in and tends to be the fundraisers so there isn't a big part of international money sitting around for international aid certainly for places like Vanuatu so the first people in go in to do undertakings to assess the need for money so that they can go to global donors and ask for money to go and fix that and so one of the things that commonly is done is a rapid damage assessment so you go in and you work out which buildings are totally damaged which buildings are partially damaged and you get some idea of how many people are homeless and how much it's going to cost to rebuild that's rapid damage assessment takes six, eight weeks typically in Vanuatu it takes a lot longer because it's a long time to get there so as an experiment the World Bank paid some drone pilots to go and overfly the area and they took side-on images and they took top-down images and the top-down images we gave to OpenStreetMap and the side-on images we tagged we got volunteers on the internet to tag every building and so red tags are total damage amber tags are partial damage and blue tags are not significantly damaged that was the most tedious it was just in the terrible balance point between you had to have meticulous attention to detail but it's incredibly repetitive but it meant that we could do a rapid damage assessment in about a week and most of that was getting drone pilots on to Vanuatu and then getting the data out so that we could see it because Vanuatu is not well connected to the internet and there's been quite a lot of work to try and build machine learning into this sort of tool and I've seen some experiments in the Houston floods where I don't know if they were used by the agencies but there's certainly people were using this sort of approach but with machine learning applied to it to do rapid damage assessment so maps are a big positive that the internet has had the second really big impact I think is citizen self-organising so UNHCR do quite a lot of United Nations High Commission for Refugees they do quite a lot of work trying to understand the needs of refugees and internally displaced people one of the things they say is that amongst the most asked questions when people present at refugee camps and IDP camps is do you have Wi-Fi and is there someone to charge my mobile phone and where do I get SIM card and those are typically asked before do you have food and water so the degree to which can being connected is kind of now fundamental to human being not kind of just it's great you know I don't need to tell you we have ethernet to our tents but the degree to which connections are kind of fundamental to the way people think about the world and if you imagine the reason that you want this is you need to find out whether your family is safe you need to tell them that you are safe you need to talk to your friend that everybody that you know is on the internet and so this has had a couple of kind of significant consequences so one is that almost without noticing it communications infrastructure has become a critical part of emergency disaster recovery and a lot of it was never designed for that so the cell network is a good example like the cell network was designed originally I'm looking at someone who knows a lot about this so I'm hoping that he's nodding the cell network certainly in the west was designed to be like an add-on to the critical infrastructure which is the fixed line network well actually the cell network is a piece of critical infrastructure and you've seen that you've started to see that shift happen and certainly to switch back to UK emergency punning when I became an emergency punner in 2005 the 999 service going down was the thing that we had that was the communications risk we had in our plans now the mobile service going down the internet going down those are much more those have appeared in our risk registers in a way that we never thought of them before and then critically because human beings are incredibly connected and they have these tools and techniques that enable them to talk to their friends and family turns out they use them to self-organise so I've got a couple of examples so this is 2013 in Aberystwyth which is in midwest Wales they had a huge and not really expected flooding event and it affected not just Aberystwyth it affected some villages upstream and it really was quite dramatic and it thankfully I don't think it caused any death directly but it made an awful lot of people homeless straight away and without really the official authorities being aware the people of Aberystwyth started to decide that they were going to sort stuff out you see this a lot people offer temporary accommodation to each other they offer wifi, they offer power and what's worrying from the state responder point of view is how much faith can we have in these people like how safe are you going to the house as a friend of a friend of a friend on Facebook would you not be better going to the leisure centre and keeping on a camp bed which is the thing we have in the plan for you and that's actually no longer a relevant question because it turns out this is just what happened so the question was shifted from 2013 where Ceredigion Council were going is this right, is this safe should we need to give people sensible advice because this is the way that people respond to emergencies and I find it quite sort of life affirming almost always in emergencies, disasters human beings in large numbers go and help each other out and when they do it on the internet you can see it but they do it anyway this is perhaps a slightly more significant thing so in the Nepal earthquake there was a fantastic organisation called Kathmandu Living Labs they were part of the open street map community so they were mapping Nepal locally on the open street map because they could see that it would be useful and because they were there and doing that when the earthquake struck they suddenly kind of turned into this hub for community action and they used this tool which is used a lot even though it's horrible called Ushahidi so Ushahidi was originally developed for election monitoring or post-election violence monitoring and actually I don't think it's got a great UI but lots of people know how to use it it's free and what it enables you to do is take public reports on a map so one that we worked on in Nepal there was an orphanage full of 50 children and they're not there anymore does anyone know where they are is a thing that you can put on a map and then you can track comments and workflow against that report and then someone can close it down so say that that's been resolved Kathmandu Living Labs set up Ushahidi incidents this was towards the kind of end of that deployment so where it says that's 1015 reports of something that needs attention and then with almost all of those there was a response and triaging and this is all happening at a kind of citizen-to-citizen level the state and to a large extent the humanitarian responders who go into disaster zones weren't really engaging with that so part of what my volunteer group do is to try and help humanitarian responders understand that this is a significant thing but again I think this is because Aberystwyth is in the west and it's nice and rich and it's not totally surprising that people go on to Facebook and they try and help each other out Nepal is not rich and yet they use this kind of these free but kind of cutting edge bits of technology to self-organise kind of significant humanitarian response and then within the world of disaster response there's a whole kind of set of layers of citizens who were just getting on with it to different degrees so my group's done by Task Force is just a group of people essentially we're emergency on-call librarians like people who like searching the internet for things and putting it on maps but there's a whole kind of swath of them and they have kind of sprung up out of people like yourselves who have skills and are motivated to do something about it and rather like the Camandou Living Labs problem the people who expect to be doing something about it don't really know what to do with these weirdos who appear on the internet and stuff so the UN has set up a thing called the DHN digital humanitarian network to try and provide an interface between the weird, we call them VTCs Volunteer Technical Communities but these kind of weird amorphous citizen-led self-starting technical groups who actually have high levels of capability but don't know anything about humanitarian response and the people who are on the ground trying to kind of install clean water and all that stuff and so if you're inspired to do any of this stuff find yourself a DHN group and join it and we've seen this citizen self-organising happening this year in the Kerala floods so lots and lots of people now what's interesting vaguely to me is globally the way this is done is moved off platforms like Facebook and Twitter and other more public platforms on to things like WhatsApp so the Kerala floods huge amounts of citizen self-organising but not really done on the public web all done on interlocking WhatsApp groups and that's interesting it's not because people have made a decision that they want to use WhatsApp above these are the platforms it's just they're on WhatsApp their friends are on WhatsApp that's what you do I think I'm running out of time so I need to explain very briefly even though I'm running out of time you know how it is you have a set of slides that you've used a few times this is the slide that I always use to talk about convergent volunteers so this is the 2014 floods in Somerset but it's a picture of the Prime Minister of the time visiting and I just couldn't put a picture of David Cameron up I just couldn't do it so I had to replace him with a penguin so what we have in the UK and around the world is this idea of convergent volunteers so not just people getting online people organising online and then going to places and this is such an issue it's of such significance that there's now UK government guidance to all the local public sector bodies about how you should think about convergent volunteers so the Somerset floods thousands possibly tens of thousands of people turned up in Somerset which is great but it's not clear that they were necessarily very helpful but that's not necessarily that might be because they were not directed to helpful things to do who's watching my time? I've got that, alright so and then the third bit is which I've kind of alluded to is formal organisations of people who expect to be doing this stuff find there's a lot of friction as the internet changes the way that they think stuff so dramatic one that UK citizens may remember is 2011 2011 we had riots in cities in England there were lots of causes for the riots but one of the things that was very significant was people used messaging platforms and social media platforms to organise, coordinate, to work out where the police were so they could go into other places and the police did not expect that at all they were not geared up for that even though it wasn't the first time it happened they still hadn't noticed and you're now like the police thing has attitude to online social networking has completely transformed in the UK since then so neighbourhood policing is really emphasises getting out into virtual communities because they don't want to be in the stage where citizens are organising to riot and the police have no idea of what's going on and a significant phenomenon that I guess has always been there when the emergency is but the internet puts it on some sort of drug that accelerates things a lot speed is rumours so people it's a weird phenomenon but in the emergency people kind of seed the internet with rumours, false rumours and not usually not with any don't seem to have any sort of political agenda just a thing that people do and often these rumours don't go anywhere but sometimes the rumour will capture a sense of where people are and then it gets spread very widely and it seems to cause a lot of unsettling and this is again another example of the riots so when the riots spread to the centre of Birmingham someone tweeted a picture of this which is if you know the centre of Birmingham it's a huge metal bull outside the bull ring and it had been taken off by the rioters and this was incredibly widely shared and caused I think people to be very worried because it just sort of encapsulated this idea that the police had lost control of the streets and yet A, how would they get the head off a bronze statue and B, it was you could see from, if you knew anything about Birmingham you could see from the shops behind that this was an old photo that had been photoshopped and one of the interesting things is that the community in Birmingham, the online community in Birmingham scotched that rumour very quickly but the rumour kept coming back on an eight hour cycle because people who were not online when the rumour was originally scotched logged on, saw the image, went oh my god and that that is a thing that certainly in the UK we don't really we still agencies don't know what to do about that do they leave it because the community will sort it out should they say it's not true five minutes okay that's great, that's totally on plan there isn't there isn't half my presentation yet to go and just on the edge there I'm really just sharing my pain so I used to work for Hereford's Council as a comms officer a few years ago someone returned from Sierra Leone felt a bit ill went into a GP walking clinic in the centre of Hereford and said I've just come back from the Bola area and I'm feeling ill which you shouldn't have done so that person shouldn't have done that they should have phoned up and said I'm feeling a bit ill but then the walking clinic didn't do what they should have done which is say go home and phone us they evacuated the walking clinic and put up a sign saying and left this potential patient in there and put up a sign saying suspected to Bola case so it became quite a significant rumour and the frustration for me was the public health people who knew what they were talking about were absolutely clear right from the start that there was very little chance that this was really Ebola but they wouldn't say it because they have to go through a set of protocols which is fine unless you live in Hereford when there's a sign outside the GP surgery going Ebola has come to the and so this friction of the people who are supposed to look after you in the months is interacting with what's really happening in the months is a kind of ongoing problem this I will tell you very quickly so one other thing we haven't really come to terms with is bad actors in these networks so this was in 2011 you may or may not remember that there was a NATO bombing campaign in Libya my volunteer group worked for the UN privately to map what was going on and provide that information to the UN so that they could plan a humanitarian response afterwards it became clear very quickly that people sympathetic to the Gaddafi regime had infiltrated our network because we never gave any thought to operational security and in fact we still don't really know how to handle operational security and they were trying to manipulate the information that was on there and that was back in 2011 and that was before we knew about what Russia were up to and they we don't know how to deal with kind of bad actors trying to influence our normal discourse we really don't know how to deal with it in an emergency or a disaster it's an it's an example there so how the internet has changed emergencies maps are better and maps save lives maps are the thing it's made communications infrastructure critical it's enabled citizens to do things they never could before but we're experiencing this friction with established organizations and their normal way of working and what could you do about it if this has inspired you if you ever ever do anything with geodata do it with OSM the more people work with OSM the better OSM gets for the world and a lot of the missing map stuff relies on a thing that was developed in the UK for a completely different purpose called the walking papers and so if we develop things here and have unforeseen benefits around the world if you have tech skills and you want to help out join a DHN partner organization and if you can work out how to fix Twitter and Facebook that would be great that's all I have, thank you very much thank you Ben, that was an absolutely amazing talk we have time for a few questions just stick your hand up if you do have questions just so I can get a sense of how many we've got okay great thank you very much for that very interesting stuff there's been a couple of applications built for Android and iOS to kind of supplement Google Maps for things like traffic and speed cameras and police all that fun stuff have you thought about maybe making applications sort of like this for emergencies because then it would bring it down to sort of very low level that anybody could start using it and kind of feed into the system just by taking out your smartphone to use is there something like that out there have you thought about this? I think that sounds like a great idea what has worked so far is where people build applications for their own purposes but then open source them so like Ushahidi is a critical tool for citizens self-organizing but it wasn't built for that purpose and so the map of mercy of OpenStreetMap group is building exactly what you described data into OpenStreetMap in Birmingham and I think we should focus on building applications that have a use now and let people who need them get hold of them when they need them rather than trying to guess what application might be useful in the future if that makes sense so I guess what about emergencies like disasters so I guess my experience is in a disaster people reach for the tools that they are familiar with and some tools that other people are familiar with people do try and build disaster specific applications but they often don't gain traction because in a disaster you want the thing that you know how to use not the thing that was designed for this purpose so I think we should build cool stuff but not build it for emergencies build it for use available to people in the mountains so not so much of a question but just a call out to missing maps that they hold mapathons regularly go to missingmaps.org and there will be a mapathon in your area there's lots of them I organised Reading missing maps and I'm involved with London missing maps as well so maybe missing maps could have a village at the next EMF any more questions there's one over here hello it's just interesting hearing about Aberystwyth since we were me and my friend were staying there at the time but my question is you mentioned these large organisations which have like bureaucracy or process in place which means they can't comment on a like a bowler thing and then the small people to people like peer networks is there anything between them and the two kind of extremes or like a bridge of you know maybe knowledgeable people that could comment on the a bowler thing because they're not as constrained by process yeah and in fact the police have cotton on to that since the riots so so in in Herefordshire, in south Hereford we had a couple of years ago a set of police in close proximity which the police said were not related it was just a chance thing but the police now are smart enough to know that a statement from the superintendent won't go anywhere but the neighbourhood policing team putting something out on twitter will get a lot of trust because everybody knows them already in that environment and so the it isn't that so that's the message for I think for formal organisations is you need to join the network like the world is not as you think it is you need to join the network and then we need public health professionals in the network that people know and trust that's fantastic a huge round of applause for Ben


Hello everyone. Next is Michael. He's going to talk about Susie and I'm going to let him start. I'm not going to take any time. We're kind of running a bit behind. So, everyone welcome Michael. Hello. Does the microphone work? Yes. Very good. This works as well. From roots to artificial intelligence algorithms. This is of course about Susie. And yesterday I introduced why we are doing this project and today I will get into details and explain how it works in a very detailed way. So, some time ago, 1986, already people thought that computer in the future are something where you can talk to like Scotty in this Star Trek movie. And this is a bit coming true now. As we had seen yesterday in my presentation, also Google starts to respond to complete sentences with complete answers directly without providing a link or they have links but they also have the answer like here also. And my idea about search engines in the future is that what should they do in the future? And maybe an answer is that they simply answer to all kinds of questions. So, what's inside the web is not that important anymore. People are simply searching for answers and search engines of the future will just return these answers. We created the log log project where we collected billions of tweets and we started to ask questions against this database like who tweeted most about FOSS Asia yesterday. So, this is also kind of natural language question against the large database about social media. And this is also something which should be answered in a natural language way. And all the big companies, Google, Amazon, Apple, Microsoft are now inventing these machines which are doing exactly that. These are the answers on the question what is the search engine of the future. It's something we can simply talk to and it will give you any kind of answer. So, what we are doing with the Zuzi project is that we are creating a field open source personal assistant. They call it sometimes smart speaker but this is a very similar thing. So, this is the open source version of it. It's considered to be artificial intelligence object. So, if we want to do something like this then we need to explain or need to understand what artificial intelligence actually means. So, people have opinions like with devices like that you can be smart. They think work for you and maybe do unexpected things but we want to know it in detail. So, artificial intelligence has a definition and it's that systems which think like humans or that think rationally are artificial intelligence systems.  There is also the distinction between weak artificial intelligence and strong artificial intelligence. There's a big mixture of things. So, people think things are intelligent if they just act like humans but what is actually built are very simple tools. So, they can do something which a human can do in a very specific field like recognizing objects or playing chess and so on. They are not general intelligent. And this is the distinction. The strong AI says it's like a human can think and act like a human and in the past it was also mixed up. It was a mixture of the meaning that real intelligence only comes if you have a mind. So, it's not that big discussion anymore about this. And weak AI means you have a specific tool. So, this is the toolbox of the things you can have in artificial intelligence. Heuristics and constrained search is something you know from your navigation system. Heuristic search is something which is done to find the best connection between two points. And this is a very normal thing. It's artificial intelligence from the algorithm but it's a normal thing. Learning with reinforcement is something which is now done with neural networks and it's a very new field because it had been done already 30 and 40 years ago but it wasn't very good. And because of the computation power and new computation models they are now very strong. Then there's reasoning with knowledge and logic and uncertain knowledge with game playing. And reasoning with knowledge and logic is where you have automatic proof systems which create something like expert systems. They have a knowledge base and they have deduction rules. And you can apply these things if you have a specific knowledge and you don't have uncertain things. And certain knowledge is where you do game playing. And 20 years ago this field of reasoning, this was the strongest field in artificial intelligence from my perspective. And this is a very interesting thing where we can also have a model for an expert system which creates a personal assistant. So other things you expect from artificial intelligence system is that it can do natural language processing with text-to-speech and speech-to-text. Then being able to compute with a large number of data objects like we did in the lock-lock project where we have billions of tweets, reasoning chains, that's what expert systems do, machine learning like sentiment analyzers for texts. Then you need something where you compute. That's what we do in the Susie server and where I get into detail. Then you need something to handle accounts. So many people can access the same server and it's computed for each of them individually. And you need this ecosystem of different clients which access a server. And of course you need user-defined skills so people can contribute and create skills themselves. So it's a complicated thing and it's something which we created already. We have created this ecosystem of different applications, clients, and the ability to create skills in an easy way. So the beginning of this idea was not to create artificial intelligence but what I did with the Yasi peer-to-peer search engine project was creating a search engine. And with the lock-lock social media harvesting engine it's also a search engine. At a certain point we thought that we must bring these things together so we have an aggregation level and have then a search for all these things together. But after we found out that we can ask questions against this database like who tweeted most about Force Asia and other questions against the database, we thought let's get more elements inside like conversation rules so that we can formulate what kind of question can be asked and what kind of result should be computed, should the result be just a phrase or should it be a picture or a map and so on. And then other sources came inside like results from Alpha and from open data sources and so on. So this is the idea how SUSE was created. It was not like let's create a chatbot because chatbots are cool. It was the necessity to have an aggregation engine for different kinds of sources of search engines and that's a specific strong element in SUSE to be able to integrate data elements from outside. And once you create new information out of this you can feed it back into something like a reflection memory and then it's something which should be represented in a common way. So all these data sources should be represented in a specific way that's similar to each other and it should track a state so you know that one information came from a course. And this data structure is called the SUSE thought. So this is like SUSE thinks it goes from thought to thought. So how can you do this? We have this backend server. It's available at api.susieai and if you do not a search you put something in a phrase into this field then you get a JSON backend. That's what every client sees if it's computing a result like a spoken access or written access to the client. So it always gets this JSON back and that's what you see here that's a SUSE thought. It's a computation step to answer a question. And the question here is how is the weather in Singapore and it returns an answer object containing an action element and the action element says it's an answer and it has an expression. So actions could be also not answers it could be other things like switching on the lights or playing music and so on. So the result of a query is a set of actions which are executed after each other. So these are the elements you can compose if you create your own skill. So this is the backend thing and it's really easy to test new skills and see what has exactly happened. Then there's the data object and the data object collects everything which you have accessed from external sources but it also represents the internal variable space. So if you set temporary variables they are represented here and you can do a debugging and see what's happening there. To compute the result from a skill you need a computation model. It's not a chatbot where you can say this is the input and then please give me that output. These chatbots usually are very simple. You just put something in and you have a national language processing, you have a pattern. That pattern is represented as an intent and the intent means you have to put something outside. The idea is that Susie is able to act like an expert system. It can think about things. It can have, think about an option and then during that thinking finds out that this option is not a good option and that it should have an alternative. This kind of computation is shown by Prolog, the Prolog language. There's an example for this language and this is the inspiration. We have this condition part and the predicate part and if every predicate inside the condition holds then that predicate is true. This program that's a quick sort in Prolog. In Susie the condition is the rule process. So what is the rule process? All the things which must hold true to produce an answer and the predicate is something that's the answer itself. We turn this thing around. Everything which is an intent in a bot is what here is a condition in the rule. It's not a predicate, it's so easy to understand. You need to know some predicate, first order logic predicate knowledge. So here's an example. The Susie skill language has a very simple form. We can forget all these complex things and just write some simple phrases like this one, shall I start? This is the simple pattern and if a variable called boot is set to excited then the answer is you will be happy. These are the conditions. You have two conditions. One is that the pattern holds and the second condition is that the variable set and the answer predicate is this one. So this very simple kind of language can be used to create an extra system which creates the answer. So it's maybe completely different from what you have seen from other kind of chatbots or personal assistants. It's not that difficult in the end. So the whole ecosystem what's running in the server is that this deduction can only can take place if a specific skill is found to be computed and because we are computing with patterns, some patterns can fire at the same time and so we need a ranking. Some skills must be computed first and then other as a second option. In Prolog, the order of computation is not defined. It's open and here we have a ranking of skills which is necessary for communication. So we have a learning component. We have a data memory where we can recall what was in the thought before. We can feed this back to the next query and we have these data sources which are presented and so we can access resources from the data, from the web and we have a skill resource and we have also a special skill resource which are called dreams. This is the testbed for new skills. And plug-ins is that maybe in the future this is not implemented. All other things are implemented that Susie is able to create its own skills. So you could have a teach-in method. So Susie learns skills. This was the first representation of the rules inside of Susie. It's a JSON structure. This is what internally runs. We have a lot of patterns which cause that we start a process. This process can access data from external source. This is like a SQL statement and then we have an action which is returned and the variables which had been computed inside the process is then replaced in here. And to make this kind of access to an outside we need a console service which is described here. This is the external resource. So it's not that complex in the end because the rules are very simple which you describe and this is compiled into this internal format. Because of time I will jump to the skill description. This is a picture I took outside from the building because it says it takes 10,000 hours to master a skill. But this is wrong. This would be very long. I think it's 10 seconds. What I show you you will understand it instantly. So here is the example. The idea is that the skill data set can only grow if it is as simple as writing a wiki article. If it's more complex people won't do it. But it's that simple. So this is the most simple skill. It's actually a text file. A simple text file where the input is the first line if it matches then the second line is the output. Many of the impressing features of Alexa for example I think they are all scripted in this way. There's no intelligent thing around it. Having a lot of these phrases makes a funny thing. That's an important thing that if you create a tool like that it's funny as well. So it should be easy to put in all these things which could be funny. Next example is that you can have alternatives in the answer so it's a random answer one of these. Next example is that you have several inputs which cost the same output. So you can say Bonjour or ciao and output is hello. Then a simple pattern. This is a placement for anything. So if you have anything inside then you get the output. And if you put something inside here this is the same as here. The previous example but this is stored in a variable which is called one. So you can just output something called one. This is at this time not more than you know from Eliza a very classic example but this is just the simple things. So having more patterns means you have more variables then you can store one variable into a permanent memory. So this is memorized permanently and can access it afterwards. It's not only part of an expression which is output but it's also stored into this beer brand variable. Then you can give this out again and you can have hidden assignments. These are visual assignments where something you can see in the expression is stored into a variable. But here you have a hidden assignment where the word excited is not shown but just stored in the mood variable and then you can put this out again. Now this mood variable is something where it can have conditions on. So you can have rules which fire on specific conditions and so this is a condition where it only matters that something is set into this variable and here it's required that it's set to a specific value. And here's an example where you can have a call back to itself. So function color is not a, this is not a special word. It's just like a phrase. And you can access this phrase again in this example where function color is called inside of a result. So Susie is calling itself at this moment. It's taking its answer from another answer which is computed inside. This is the reflection element. So phrases can be like meter phrases which are inside somewhere else. And you can of course put in some JavaScript. So if you start a line with this bank then you can compute until URL in JavaScript. This can be more complex by using a variable. And that's the final example which takes the result from an outside API. And that was the beginning of the idea to have a scripted meter data search engine which is taking data from a JSON component and then a specific element in that JSON is accessed. And to say which kind of element is accessed is given in the JSON path and that's the object's statuses. So now there are the things which are not implemented. Thinking with backtracking, expert system with first order logic. Skill reflection, skill read skills. So you don't call a skill but you read a skill and skills which create skills. And Susie talks to itself. So this can be done by going into the interface, go to Susie AI, click on the burger, make an account, click on skill. Then you see all the skills. Click on the skill. Click on edit. And there it is. That's a skill which takes information what happened on and it takes it from this API and the JSON path is data events. And very easy thing to test is you can go to dream Susie AI and it has, this is an etherpad and you can make an etherpad an instant input for a skill. So you can put in anything there. I don't have time left I think. Okay. So come to my table at the basement. I will show this to you. So thank you.