Kanfiasta 2022 organized under the team where talents meet. Kanfiasta was introduced by the faculties of commerce and management department in the year 2016 with an aim to promote the true spirit of competition and to test the artistic mental abilities of the students. Kanfiasta is also aligned with the vision of that so college which is to create an impact, positive impact in the world as this phase looks to help students develop and bring to for their skills and boosts confidence within themselves in various ways enabling them to follow the right trajectory in their coming years. It is also a platform to let students create memories together, memories that will live run free forever. This year we have entered the seventh edition of Kanfiasta and this is also the very first offline edition since the pandemic in 2019. So we are truly excited and very honored to have the participation of 13 schools and colleges this year. They are Unity College, C.H. College, S.D. Jane, Women's College, Pranab Nanda, Women's College, St. Joseph's College, Jakama, Daily Public School, City College of Arts and Commerce, Public College of Commerce, Ram Jana Ki Hayasek Andrews School, Padkai Christian College, St. Joseph's University, Chumuk Dima, Livingstone Foundation International and yes of course that's the college. We are also extremely grateful to our sponsors for the support and generosity that has enabled us to you know make this Kanfiasta even better and this year we have at least of many sponsors. They are Naglin Coffee, Hetika Cafe, Cafe Jeju Island, Cat Sweating Collection, Island Low, Illumi Skin and Aesthetic, Iphone Hub, Nagland, Nagahad, Naroki, Heelstar Dimaapur, Helpline Tours and Travel, Quality Work Furniture, SP Mobile Shop, Coco Berry, Madras Cafe, Sports Hub, Baskin Robbins, Jenny's Habalement, New U, Fusion Dimaapur, Hornbill TV, Annapurna, Flavors Restaurant, Twice New, Battle Light, Maverick Dream, Sapient Wild, Synergy Systems and our alumni and various individuals. So let us all give a round of applause for the schools and colleges and our sponsors. Thank you once again. Now before we start off anything here is another announcement and also a reminder to all the schools and colleges participating that there will be points given for your discipline and we will also have a winner for the best discipline team. Therefore I request each one of you to maintain your discipline and be the winner at the end of the session. Let us all look to God in prayer. Eternal God our Heavenly Father we want to thank you and praise you for this beautiful day. We thank you for the life. Now we will have the welcome address by a principal Dr. Hawesah Elkin. I give her the time. Good morning everyone. Our respected chairperson, our honorable special guests for this morning, Professor Dr. D. Nannadurai, the Vice Chancellor of St. Joseph University, our faculty, staff, students and all of our participating institutes and staff who are visiting Ditzel College for the first time or here to witness the confiesta from the previous sessions too. I warmly welcome all of you to the Ditzel College campus and to the Ditzel College community. We welcome you with great joy because Confiesta 2022 has been a long-awaited program. I know the students and staff have been preparing hard for this day and the excitement that has been building up has been so strong the past few days so we're very excited and we're very happy to be having as many as about 13 institutes, colleges as well as schools attending the Confiesta this year. We're also happy to be having the winners of our Confiesta 2021, our Reading Champions, our St. Joseph College Jacoma. Thank you for coming again and we also have the runners-up, the Delhi Public School. They were the runners-up of Confiesta 2021 and we're so glad that you could be participating this year as well. We look forward to seeing who the overall champions will be for Confiesta 2022. We have a lot of exciting events and programs lined up for you all and so as we take this time to participate and engage and learn from one another, I'd like to extend this warm welcome and invite you all to our Titzel College campus once again. For those of you who may be not strangers to the campus, you know your way around already. For those of you who are new, feel free to reach out to our volunteers, to any student over here and let this be your campus for today. Titzel College has been envisioned as a place for big dreamers, deep thinkers and effective and impactful doers. It's a place where we believe in students coming together challenging yourselves to become better versions of yourselves through the various competitions that you will be participating in today. It is our hope that you will be able to explore your talents, discover new ones, and be able to express your most original true natural self through the events that have been planned for you all today. We look for students that are driven and focused, enthusiastic and excited about life and this is what Confiesta is all about to bring that student community together to compete in a healthy spirit, in a positive spirit and to be able to learn from one another. It is not just about winning but it is about learning from the different events and programs that are being planned. So I hope that when you go back today you will exit this campus taking this positive energy, this drive, and this focus to keep on succeeding, competing and learning. Whether it is whether you win or lose, we believe that we're all meant to be here today to experience and to grow as humans. So thank you for participating on that note. I would just like to wish everyone all the very best and I hope that you find what you are looking for as you participate in this Confiesta 2022. Thank you very much. Director and principal of Tessow College and faculty members, students and participants from other institutions, a very good morning to you all. I'm really happy to stand before you in this occasion and I feel it honored to be here and I thank the management, the principal as well as the director for giving me this opportunity to address the gathering. My dear students, just I will talk to you for 10 minutes. I don't want to take more time. Why I'm telling the previously means many speakers they are going on talking then the audience will be getting frustrated when this man will complete his speech like that. So just I will take 10 minutes to address you. So I really feel getting energized just by seeing the young minds of this institution and other institutions during our time. We were not having such type of talents, such type of occasions. I'm talking about the time of 80s because that time the number of institutions are very minimum in a districts one or two. But nowadays it is not like that. You are having a lot of opportunity. You are having so many institutions and you are having so many opportunities to expose your talents. I think this is one of the occasions to expose your talents. So in this context I would like to convey important message to you all. So nowadays the talents or the quality of a student is being decided by the great system or the class what he is getting. It is not like that. You don't bother about what is the mark you are getting. But of course the minimum requirement is the past mark. Don't go below that. But you don't always aim at the A grade. If you are not getting the A grade don't bother about that. If you are getting C grade or D grade be happy with that one. But the very important thing is you identify your talents because each personality, each human being is having their own talents. Don't compare yourself with others. I don't know either any parents are there here or not. Or at least the faculty members, you also don't compare one person with the other student. Each student is having his own weakness. They are having their own talent. So the student should first identify his talents. And similarly the faculty members also should make the students to identify the talent. And then that talent should be enriched.  Then only you set up your bright future. Many of the parents they are willing to make their word as a doctor or engineer. But the son or daughter may want to become a musician or something else. So there is a conflict. So that is the main drawback of this society. Because the life of the students is decided by somebody else. The parents or the people in the society or relatives.  Then definitely you will come up in our life. Because God has given talent to all. But the talent are in a different nature. The second thing I want to emphasize is it is very important to improve your practical knowledge. Nowadays when you are going, students are going out of the institution, they are having a degree in their hand. Be a political science or be economic, something like that. This is the certificate for the purpose being issued is that you completed a graduates in a specialization that's all. It is just a paper. But what knowledge you have gathered during your studying is very important. What knowledge you have acquired, what experience you got during your study period. That should be very useful for getting an employment or making your future a good thing. Many of us our purpose of getting a degree is to get a good job. And after getting a good job, getting a good wife or husband and having a decent life. This is our main aim. This is our normal human being, our students, they are aim or objective. But you think beyond that one. So whenever you are studying, you always concentrate in research. Nowadays our national education policy and the UGC and HRD, all the organizations, they are very much interested in promoting the research. Because research is very important. Research in the sense, don't think about that is a very high thing. Even in the plus two level, even in the UG level, you can do a small research and you can find something. Then you will be automatically motivated by yourself. I have found this one. Then you can present that one in some gathering or some occasion. Then you will be getting motivated. Then you can go deep into the research. Then finally you can achieve something different. Don't think that the research means it is a PhD or something else. The research can be started from the school time itself. You know about the Bill Gates? He is the founder of the Microsoft. He started his research from his plus two level itself. He did lots, but he is a dropout student in the college. Do you know that? He is a dropout student in the college. But he has identified his potential. He concentrated in that one. He started his research during the school time itself. Slowly he developed. At the age of 21, with a small team, he has created the Microsoft. Now you know what is the potential or what is the turnover of the Microsoft company.  It can be started from a very small thing. You always concentrate on the research. It is very, very useful for you. And you always think that don't think that after the graduation we go to go some employment like they don't. Confine your thinking like that. You think entrepreneurship, because this is I think it is a management and commerce. No. You don't think about employment. Think about creating employment. If you create employment then you will be employer. Then you can give employment to many people. In that way you go to think. So my dear students, I think you enjoy this talent search where the talents meets. Expose your talents and getting an award or getting a first prize or second prize is not at all a problem. If you get a first prize, you enjoy it. Suppose you are not getting, then you learn why I'm not getting. You learn from that your failure. The next time you perform well. Normally the human beings are very much accustomed to manage their successiveness. Once they are getting success then they will celebrate. But they are very poor in handling the failures. But we should strong enough to handle our own failures because failures are the real teachers. If you fail anything else, then only you can learn why I am failing in that one. What is the reason? Then you can learn more. The next time you can perform better and you can again you can have a success. So you always keep the failures as the stepping stones of your success.  I think I don't know where I read that one. See, keep your mind a very strong one. If you keep your mind weak, the situation will be difficult for you. If you keep your mind a balanced one, then the situation is challenging for you. But if you keep your mind a strong one, then the situation becomes an opportunity for you. Then you understand. That is why many people, they are keeping their mind very strong during the COVID time. Then the situation is an opportunity for them, very particularly for the software engineers. Because you know the software that is that software engineering field is a very important field. It is having many employees. During that COVID period, they suffer lots, but they kept their mind very strong. Then they take that critical period as an opportunity by developing the online software, attending the online examination. Then again, it becomes a booming industry. So if you keep your mind very strong, whatever may be the situation, it will create opportunity for you. So my dear student, just like keeping your body beautiful or strength and one, keep your mind also very strong. It will help you to make your life a very bright full one. Thank you very much. Thank you so much, Sarah, for speaking to us in such a nurturing manner and also for you know speaking to us and believing in us that we will someday grow into somebody to be remembered in the future. We are truly grateful. Before we go ahead with the competitions and events, I also would like to give a quick announcement that we have our media partners from Hornbill TV and Nalklen pause this event. So may we all give a round of applause for our media partners.


Well, this is my first. It's been a critical event for me to get here. I've been wanting to come on other occasions and there've been ways of stopping for whatever reason. But this is, I've regarded this as a critical event when I was working in Australia. I mark this event as the number one event for regulators. I think the Pacific has particularly unique challenges. The situation in Vanuatu is that we have a competitor. But the competitor interestingly has really eaten into the previous incumbents territory very quickly. So to balance and get effective competition there is a real challenge. A technological challenge for us is that everything is via the satellite at the moment. If the weather is not good, the reception is not good. If the weather is not good, there's no television predominantly. And so, yes, everything. And then there's the speed and the latency. So we have a submarine cable coming. The government has made that decision. And the cable will arrive late this year or very early next year. And that will of course give us huge capacity. I think firstly I would like to make them aware of the challenges of the Pacific. There's no one-size-fits-all solution. And often that's what people think. If it works in one country, it works in another. And in fact, there would be a different solution for each Pacific country. And then there's the dialogue and the know-how, the ways to achieve, the secrets unlocked. That's what I think we need. And particularly for my manager that's travelling with me as well.


Dear learners, I welcome you all to my class on theory of production. So in this class basically we will discuss about production function, the functional relationship between input and output, production function in the short wrap as well as in the long run. Then we will discuss what is iso-con, then properties or characteristics of iso-con. Let me define what is production. Production is the process in which economic resources or inputs are combined to create economic goods and services or output. As for example, in the production of a table, several inputs are required such as labor, raw materials, tools and equipment acceptor. So these inputs are combined in a particular manner as defined by the technology to produce the given output. Now whenever we are talking about production function, it basically describe the relation between physical quantities of inputs and physical quantity of output. What if given a state of technology, the production function shows the maximum amount of output attainable with a given level of input. So it does shows the functional relationship between inputs and output. If x1, x2, dot, dot, dot, xn are the quantities of input and q is the maximum attainable output, then the production function can be written as q is a function of the input used such as x1, x2, dot, dot, dot, xn. Now the general mathematical form of a production function is q is a function of labor, capital, raw materials, land input, return to scale parameter and efficiency parameter. Now in case of production function, all variables in the production function are flow variables and are measured per unit of time. Since raw materials bears a constant relation to output at all levels of production, hence if output is measured in terms of value added, that is the value of the raw materials can be deducted from the value of the output and the variable r can be excluded from the production function. Likewise, land input as is constant for an economy as a whole and hence we may not enter the aggregate production function. Thus if we exclude these two variables, ultimately the production function in a traditional economic theory assumes the form as q is a function of labor, capital, return to scale parameter and efficiency parameter. And symbolically what we can call it as, what we can term is that q is a function of lk small n n a. Now the return to scale parameter that is n refers to the long run analysis of the laws of production and the efficiency parameter refers to the entrepreneurial or organizational aspect of production. Graphically, how we can represent a production function? Graphically, a production function is presented on a curve on a basically two dimensional graph. Senses in the relevant variables are basically shown either by moment along the curve that depicts the production function or by shift of this curve. Now, whenever you are explaining production function, it can be explained in case of short run or it can be explained in case of long run. So, there are basic differences between short run, production function and long run production function. So, we will start with production function in the short run which is also known as the law of variable proportion. In economic theory, as I have already told you, you know, a distinction is made between the short run and long run. The short run is a time period when it is not possible to increase the supply of certain factors, especially the fixed factors. So, accordingly, senses in output camp come about only through changes in the supply of variable factor. The behavior of the production function in the short run is governed by the law of diminishing return and is also known as law of variable proportion or return to a factor. The supply of fixed factor, you know, remaining constant in the short run, you know, as a result, you know, the production function taking the formula Q is a function of labor and capital. Now, what if when, as in the short run, some of the factors are constant, the total product, the shape of the total product is an increasing function of labor input. That is, as labor increases, the total output also increases. Now, total output, basically what happens, total output initially increases at an increasing rate. This is because for a given amount of capital, as labor input increases, the productivity of both the factor increase, and this leads to total product increasing at an increasing rate initially. But for a given amount of capital input, as labor input increases further, what it results, it results in a fall in the productivity of the inputs. And as a result, total product increases at a decreasing rate. Now, in case of long run, the long run is a period where it is possible to increase the supply of all the factors as and when required. Thus, all factors of production become variable in the long run. So, you know, in our production, you know, in case, in our production function in the long run, both labor and capital are variable inputs. And accordingly, increasing output can become about throw and increase in all the factors in case of long run. Next, we will discuss about isoquant. Now, what is isoquant? You know, to represent the long run production function, you know, graphically in the, we used to the technique of isoquant. Now, how can we define isoquant? The isoquant is a curve which shows different combination of capital and labor producing the same level of output. So, obviously, you know, to show different level of output, we draw defined isoquant, and that is represented by isoquant map. So, if you see the figures, the figure 1 shows, you know, a isoquant representing defined combination of capital and labor. And the figure 2 shows, you know, isoquant map, it contains defined isoquant, you know, representing different levels of output. Now, we will discuss about what are the basic properties of isoquant. The first property of isoquant is that, you know, isoquants are downward sloping from left to right. So, why is it so? Because as one input increases, the other must be reduced so as to get the same level of output. And that is why, you know, isoquants are always downward sloping from left to the right. The second important property of isoquant is that isoquants are convex to the origin. The convexity of the isoquant arises on account of diminishing marginal rate of technical substitution. Now, what is, you know, what is marginal rate of technical substitution? The marginal rate of technical substitution is the rate at which one input is substituted for the other, keeping the output, you know, keeping the output same. Now, what you can, you know, you can also see, you know, the other possibilities. So, what happened if, you know, the marginal rate of technical substitution increases? Now, if marginal rate of technical substitution increases, the isoquant will become concave to the origin. And if, you know, marginal rate of technical substitution, you know, will remain constant to what will happen, the isoquant will take the shape of a downward sloping straight line. So, the convexity of the isoquant is basically determined by the nature of the marginal rate of technical substitution. So, as I have already told, you know, since there is a diminishing marginal rate of technical substitution, and as a result, the isoquants are always convex to the origin. The third important property of isoquant is that no two isoquants can intersect each other. So, why? Because if two isoquants intersect each other, it would mean that, you know, in that particular point where these two isoquant intersect each other, same amount of labour and capital is producing, you know, same amount of labour and capital will produce, you know, two different level of output. So, which is basically contradictory. So, as a result, you know, we can easily say that, you know, no two isoquant can intersect each other. Next, another important property of isoquant is that, you know, higher level of output are represented by higher level of isoquant. So, the, you know, isoquant, which is, you know, represents a higher level of output is always placed at the higher level as compared to a isoquant, which represents a lower level of output. So, this is, you know, the fourth property of isoquant. So, these are the things we have, you know, discussed in this class. Basically, initially, we try to define what is production. Then we try to explain, you know, what is the relations between input and output in case of production function. Then we try to explain the nature of the relationship both in the short run as well as in the long run. Then we explain what are the basic properties of isoquant. So, thank you for, you know, attending this class or, you know, see this class where we basically explains the initial part of the production function. Thank you.


President Mohammed Buhari has once again issued fresh directives to security agencies to rescue all those in captivity across the country and advance the acquisition of intelligence. The National Security Advisor, Babagana Munguno, told state house correspondents after the National Security Council meeting that the president is not happy with the prevailing security situation. According to him, the last straw was the recent attack on the Abujakadano train leading to the killing of some passengers and kidnapping of schools.


They really don't wait a second, not even one day, and it's on to the next big event. You know, these politicians, world leaders, clowns on TV, would be nothing without the millions of cronies fulfilling their wishes. Never let a good crisis go to waste, Winston Churchill. You know, it's funny how all of these countries work together, including Russia and Ukraine, to shut down the entire world because of, you know what, now wait, hold on, they're at war with each other? Wonder what they were talking about at the G20 summit? It's almost like they're planning events to manipulate the masses into doing certain things. I wonder which politicians cashed out of the stock market last week or bought shares in certain energy companies? Guys, it's called the New World Order. Not the new Russian order, not the new United States order, not the new China order. Whatever reason these leaders are creating a war, it will become very clear in the next few weeks. The bankers will ensure we stay in debt. The pharmaceutical companies will ensure we stay sick. The weapons manufacturers will ensure we keep going to war. The media will ensure we are prevented from knowing the truth. The government will ensure all of this is done legally. Whether this is all real or fake doesn't matter. Once you understand that these world leaders are just a bunch of puppets doing what they're told, working together, you should disregard what they're saying and figure out what their next step is. What's the goal? The media around the situation is incredibly controlled. It's always been controlled. All of the blue check marks on Twitter spewing the same garbage makes me want to vomit. You ever notice how the media and the world leaders are never encouraging you? They're never being positive? They're always trying to scare you, keep you in fear. Put you down. Whatever videos you see, whether it's troops moving or military attacks, they want you to see them.  Regardless of what the video is, I don't know if it's staged, real, used in a misleading application. Back at the peak of you know what, when hospitals were allegedly overwhelmed, I visited them in New York City. They were completely empty and the video of me doing that was wiped off of YouTube for showing the truth. Out of the millions of people sitting in their homes, scared, watching TV, I was one of the only people who went outside to see what was going on and all those people are just believing and doing what they're told on the TV, on social media. If you understand natural law, you will know that it is not possible. One cannot lose their life in war unless they are willing to do so. That's why the elite sociopaths in charge are plastering the media as opposed to actually just doing what they want. You have to submit. You have to allow their new world order to happen. They can't just do it. That's why we have this whole charade that's been going on for years and years and years. We know these psychopaths are willing to go as far as it takes to convince people of what their truth is, whether the deaths are real or fake, it does not matter. The majority of the public will be convinced of this and then whatever actions follow will line up with their end goal. I've said it before, but the most important thing about everything else is that you need to understand. People can lie to you. The stuff coming out of their mouth, it's not necessarily the truth. They have lied to you about almost everything in the past and they will continue to lie. My personal experience in the carnivore diet community with being plagiarized and then a whole group of people gaslighting me saying I wasn't being plagiarized woke me up to how evil these scumbags are and how they work together. And I mean it goes above and beyond that, you know, the standard American diet, vegetable seed oils, diabetes, every single thing the American public has been told and poisoned in the food and water, like you're trusting the same people with the media. One of my lovely female viewers informed me about the chevron gas deal, which was supposed to allow Ukraine to become independent on energy from Russia. And she also said that Ukraine produces a lot of wheat grain food. So by Russia invading the Ukraine, then the NWO Globalist Lunatics can have their supply chain crisis they want. Destroy the energy, destroy the food. They're slowly increasing prices on both of those, squeezing more and more money out of the masses. As they continue to have these events plaster them in the media over the next few years, the grip is getting tighter and tighter. The masses continue to believe the media while their plan unfolds right in front of their eyes. And you can't forget about the cyber attacks. Is Kahned going to turn off your power because of some big bad guy in Russia clicking a button on a computer? After charging a double last month, are meat plants going to send workers home? That's what happened with the JBS a few months ago. All of these big corporations take orders from the 1% in charge. And it's simply to gain more power and more control over the masses. Keep people in fear, manipulate the resources in their favor, move closer and closer to their new World Order Globalist BS. And you'll see in the comments, oh, my third cousin's friend is in Ukraine and he told me it's bad, like, yeah, no shit, like, please, that is completely, that's not the point of this video. The point is really to stop watching the news and try to enjoy your life and be happy because if no one listened to these fuckheads, nothing bad would happen. So thank you guys for joining me today. If you could please drop a like on the video, leave a comment down below. Subscribe so that YouTube can unsubscribe you next week and be sure to check that notification bell so they don't notify you of my videos. Therefore, you guys can go to frank-to-file.com to support me through all of my businesses. Thanks again, guys, and I'll see you tomorrow.


Thumbs up, subscribe, all that good stuff. Now it's gonna do a little Q and A, I'll answer all your questions, the best of my abilities and we'll go from there. All right, everybody, let's see. Go from there. It's already listed on Binance. And Rob will never try to contact you though. That's true. Sometimes you gotta break your own rules, right? Rigged, congrats, winners.  That's right, Benny does that stuff. Congrats, congrats.   Because you're here early in the crypto markets.  Danny says, but not only are you two viewers of Twitter, I understand, but the thing is, and maybe you guys can help me with this one, if you won Danny, how would I get this to you? Because like you could email me, but the funny thing is, is that scammers love to impersonate Danny Trifon, and they'll create a Gmail account called Danny Trifon 0097C6, email me and said, hey, I won. Give me my, give me my tangent. Here's my address and go from there. There's no way for me to verify here unless you want to give me your address, which is not happening. I don't think anybody wants to do that. So Danny, that's why I do it the way that I do it. Unless somebody has a better way to do it, I'll do it that way, but I like Twitter Picker. So go from there. I'm just saying to your research, Mark. I don't have as clean shape there, okay. When you get, the beard works out pretty well, but when you're in Puerto Rico and it's always muggy and hot, sometimes best not to have a big beard. Okay. Mitko says, will it be a deeper pullback? Maybe. I hope so. I'll be honest with you. I'm looking at these prices that I'm dollar-cost averaging every single day. I'm like, man, this was a lot cheaper back in March and April. So yeah. Dave says, thinking about a second cold wall most people here like it. I'll check for us really. I, a lot of people like Tracer too. That's an option. Some people like Keystone. I like the beard itself, but whatever. But to me personally, Tangem Ledger and Ellipal. And I lean more towards Tangem and I don't try to connect anything anymore. It's just too risky, too much on there. What's the point, right? Rob, did you sell amp in recent pumps now? I didn't really sell any of the amp. Rob, is TA no better than astrology? No, I mean, it has its place and people's do really well with it. It's just all about probabilities really. That's what the TA people tell me. It's all about probabilities. If I can, if I get 60% right or 65% right that's better than 40% and with TA that helps me out. So sure, I just don't use it.   But that's just time. And then the MBRVZ score, well, multiple PyCycle tops using different moving averages. I mean, to me, that makes sense. And that's it. Crypto Ricardos is TA's human psychology. Humans are very predictable, sure. Very true, you can see a lot of things. I wonder if TA saw, and of course retrospectively, TA will say, yes, we did see the, we saw a bonk coming and we invested heavily. Have you heard about Arbitrum solver stalling? I'm gonna read you the inscriptions, ETHCAS, who's everything with inscriptions and ordinals and things like that. It seems to have a big problem. At least for fees and things like that. Polygon had the issue, MIR had the issue, although they didn't slow the actual platform down. It was just the fees went up. When it really screws things up is with Bitcoin. And when you have inscriptions and ordinals, which some people hate, some people love, some people learn different, the fees go way, way up. Thanks, Tanny. It's nice to you. Always more shake out. Yeah, took me some bonk. So that's the end of the game. That's the way to do it. Just to get your, who said it? Somebody said, I got a moon bag. I think that was Paul. Cardano with Paul said that, it was pretty good. I sell somebody, so I got my moon bag. Do your research? Sure. You know, the thing about that, do your research thing, let's be honest. Like, how many people do their research on Voyager and Celsius? A lot of people did. You know, Mark Cuban was one of their sponsors. He introduced the Verlick at the basketball center in Dallas and said, this is our official sponsor of the Dallas Mavericks, Voyager. We want you all to sign up for Voyager. You don't think that they did their due diligence? Just a Voyager made a bone-headed play and screwed everything up. That's why I like, when everybody says, but Rob, you don't understand because you got to dime hands everything forever. These are just businesses. All of them are just businesses. Bitcoin's a little bit different. Bitcoin is different, let's be honest. But some of these, I'm not dime hands anything. I fell victim to that a long time ago. I thought if something was free then you were the product, Rob, you'd tell me that. Of course it is, right? It's free, you're the product. So that's the same way everywhere. So I do giveaways with Tangem. I really actually reach out to Tangem and I go, hey, man, it's Christmas. Let's give something away. Great. So what do you want to give? I'd like to give 20 wallets away. They go, well, how about three? I'm like, well, how about five? So we went in the middle there, I guess. Which I kind of lost that one. So I give away five Tangem wallets. You hear about it. And then at some point you go, hey, maybe I need a Tangem wallet. And then you go into the description and there's an affiliate link which is clearly labeled affiliate link for Tangem. And you'll use that Tangem link and you get 10% off.  I'm going right to tangem.com, which is your God-given right. So yes, that's exactly right. That's how it works. Try to be transparent. Jose says, y'all sold too early. And Jose could be right actually. And everybody asking me about their project. Let me just say this. Whatever project that you're in, you're probably gonna do really well. That's usually what happens in bull markets. I don't care what you're into. You could blindfold yourself and throw it a dartboard. You could probably do really well. Just some are gonna do a lot better than others. Right? Thanks, Panda. Hey, Tesla. Pat says, never sell before you're sure it's done going up. The very beginning of the bull market is the exact wrong time to sell. That's one way to look at it. Do we really need to go to a penny though? Nah.  If it already, it isn't already out there. They don't like her. Yes, and $1, a dollar bonk would be a hundred trillion market cap. That seems reasonable. Yeah, Steve was like, oh my, I don't know what I'm doing. Again, everybody's different. That's not a bad play either. Just hold on. Thanks, Linda. I appreciate you. Fortunes are made by buying low and selling too soon. I think it was Baron Rothschild that said, I made all my money from never buying the bottom and never selling the top or selling too soon. Exactly. Ada's daddy, Tangent giveaway happened yet? Yes. And here's who won, which was Spencer Zorro, Dabmore Bitcoin, Ada Penguin, Elvicho. So those are the winners. Congratulations winners. Do you think Bob's gonna dull? I don't think it's gonna hit a hundred trillion. I could be wrong though. Stranger things have happened. That would be, yeah. So Tangent of all you say, I like to partake of your free giveaway. So I, it's already been, it's already done. Hey, I will say this, if, like I sent, I sent Tangent wallets to my kids this for this Christmas and I'm gonna give them, I'm gonna give them crypto. So if you're like thinking to yourself like, Hey, what's a pretty good gift? There you go. All you gotta do is just asking for, you know, whatever wallet you want or whatever address. And what's great about Tangent again, it's everything that you that shouldn't be in there is there. People will say, well, what about CASPA? CASPA is there. What about near, near is there? And what about, of course, the big ones, Bitcoin, Avalanche and Ethereum and every year I see 20 tokens you can possibly think of. And yeah, Bonk is in there and Pith or Pithe, however you say it. Cardano is in there. SNEC is not in there, which SNEC is another one of my meme coin plays, which I bought a boatload before, doing pretty good. But that's not in there yet. I made a request to them personally to add that in. So we'll see what happens, but yeah, most of it's in there already and they've moved very fast. They just added in Vechain yesterday. Don't fall for Ram's tension, give way to all the scams and the rules. Yeah, that's it. SNEC. Pop a case. Whoops, sorry. So many good ledger question. Is it at risk to connect to remove staking from Lido? As I understand it, this situation was already rectified yesterday and they said to give it 24 hours of propagate or whatever to update. And for every other DAP that's out there, they've already been notified and they're supposed to fix the code or rewrites or whatever they have to do, obviously not a developer. But they said they'd wait 24 hours. Maybe you want to wait 48 hours, just to be sure. How do you buy a boatload of digital coins on my digital boat? Obviously, how do I get my ICP into my LODX? I don't know. Yeah, you know what? That's a good question. I wonder something. Let me just take a look here. So, I'm looking at, get out of there. ICP is not available. Might have to ask them too. ICP's on a tandem. But, Finance, Tether, Avalanche, Doge, Tron, Toncoin, Shiba, OKB, Leo, Cosmos, Kronos, Immutable, Near, Filecoin, VeChain, Injective, Optimism, ThorChain, Render, Graph, Arborch. Everything else is there. That's right. How do you become a bonk millionaire? Start with a billion. That's an old joke from, how do you become a millionaire angel investor? You start with a billion dollars. Ah, thanks Rex. Just bought three tandem on your Danco because I never win, but you got 10%. Yeah, 10% is pretty good, right? Spanish citizen says it's been patched. Real quick, how does everybody feel about ledger? I'd like to know everybody's thoughts in the comments section. Are you gonna trust them? You still gonna use them? Or you wanna switch? I still have good amount of Bitcoin online, Bitcoin, Ethereum, and Solana. But I've also got Bitcoin, Ethereum, and Solana on tandem too. I diversify again. But yeah, I think we're good here. Brian says, moving sleight of tangent. Yeah. Once you start though, and once you start to use, once you start to move things around from like, if you wanna use a dex, and you want to, like the dex I use Orca and Jupiter. When you use that dex you're using Solana, it's just so seamless and fast. It's like once you scan the card, it's there. Then once you make the transaction, it's there. And then once you wanna put it back on tangent, it's there. And it takes like no time at all. It's very nice. I just don't like the button pressing and the confirmation, everything else with ledger. But again, I'm not connecting to the dex. I'm actually sending my crypto and my cold storage wallet to my wallets, which would be in this case, the Phantom wallet, or NAMI, if I'm using the Cardano dexes. And then I do my transactions and I ship them right back. One says, what percentage of your portfolio is Bitcoin? As far as value goes, it was 75, but alt coins are making quite a gain. So I think it's below 70 now, but it's quite a bit. And I keep dollar cost averaging Bitcoin, but a lot of these alt's that I got into are overextending, bonk being one of them. So yeah, snack being the second one, yeah. From a G perspective, you're wrong for promoting a non HD wallet and wallet that gives the same transaction address isn't good. So we're talking about it here is like the Bitcoin addresses, they don't change it every single time. You can, but here's the thing, I'm not using these Bitcoin addresses consistently and moving things around. Then the cold storage and that's it. There's plenty of wallets out there. I believe ledger is one of those. So just use that if you don't like it. Yeah, and Ben's haircut, I won all in with tangent. I love it. Give them my ledger nano. Yeah. Asus, did you grab a Solana phone? You know what's funny? I was talking about it and I was like, I'm gonna get a Solana phone just to see what it is. And I looked at them like six hundred bucks, I'm not paying that. I didn't get one. Would have been nice too, but I didn't. Would have been sweet, but I mean, how many times have we said that? Boy, it would have been great if I would have bought, you know, playable in the very beginning when Jesus was talking about it or myria or immutable, but that's just how it goes. I stay sold to ledger. Yep, that's a good one. Do you think world assets like will be big this cycle? There's some decent trial and error. Could be big. I know people hate JP Morgan, but they reached out to Avalanche and to help them do their centralized permissioned blockchain called Onyx to help them move real world assets around, which is kind of funny. They have to talk to a company that's using decentralized, but for real world assets, sure. I believe Larry thinks of the exact same thing. Real world assets will be the next frontier and probably be a big mover. The question is what chains are gonna be? Is it gonna be Onyx on JP Morgan? Is there gonna be Avalanche? Or it's gonna be Ethereum? Oh, it's gonna be Ethereum. Danny says, are tangent wallets subject to swim swapping? No, they're not. So these, this is the wallet. It's weird, isn't it? It's just a card. And if you think about it, like we all have these cards, right? We all know how to do these things. We all know how to use apps. Even the people that don't earn a crypto, they know how to use debit cards and credit cards.  It's the same thing here. If you wanna pay for something or send something, you just do this. So there is nothing in here. The only thing that's in here are your private keys. And if this doesn't make sense, I can understand why it wouldn't. I did a deep dive video and I explained everything in that one about why I prefer the private key in one of these three cards. Why I don't use the harmonic phrases anymore on this particular device. And what would happen if your card got stolen and or your phone got stolen and how you would recover that or if you would get ripped off? Watch the deep dive video. It's the links in the description. Yeah, I just bought a tangent but we'll also go tangent also. Are you using ledger? Yeah, just use both. I do the same, I use them both. Some person, I think it was crew CTO Larson said that you should have one wallet as like a designated hot wallet, which makes sense. And one for just straight cold storage. You never touch it. It just goes there and it's like in a black hole, which would be, you know, maybe that's a ledger usage. You can do all your slowness shoes. Jesus said I bought three of those DGEN phones. So that means Jesus is living it up. Jesus is also really good at selling at the right time. Definitely check his channel out. I could have bought socks at a hundred bucks, socks. Ah, I bought the phone yesterday. Any chance the Voyager video's gonna bone to their way with their, with the market bumping? Probably not.   Sir, please review Gary token. I just bought it last month. Maybe, you know what? Whatever you bought, probably gonna do great, matter of fact. Oh, it's a great question. Probably the thing about people buying properties with crypto and tokenized properties. So if you're buying it with crypto, it depends. Depends on if you're using it as like collateral or you're buying it outright. You're buying it outright. It's not a bad deal, right? If you find a real estate agent is like, yeah, we take Bitcoin, like this house right here. Originally they said that we're gonna take Bitcoin and they said, no, just cash only.   Which they really didn't. I've been, since the army days, I've had USAA. So I've been with them for like decades. So they don't really ask me too much. But as far as like tokenized properties, the question I have about tokenized properties is who actually owns the property and who actually owns the deed? And has the deed been tokenized itself? And let's just say that whoever has access to that, like how do you get access to that? Because you have to have the deed of the property and has to go to all the people. And I don't know, there's a lot of things to think about for that one. I will say this, if I know there's been a couple of different companies that have sprung up that are offering the ability to do loans, we would take your crypto, that is a no-no. That is a catastrophe waiting to happen. I'm gonna tell you why. Because when you get a loan using your crypto for like a mortgage or a house, usually this is what happens. It's doing a bull run when things are going up, right? So you put in your two Bitcoin, right?   Sure, they get two Bitcoin. And then of course everything's good until everything's are going fine. And of course, things are to depreciate. They're like, hey, Bitcoin just dropped 50%. We need more Bitcoin. Oh, here you go. Bitcoin has dropped 60%, give us some more Bitcoin. They're gonna just drop. And before you know, you're like, I don't have any more crypto to put in there. And now of course they don't care because they get to liquidate you. You get the problem is that you get taxed on that. On that situation, you know, people say you don't get taxed on loans. You don't until you liquidate the asset that is the underlying the collateralized aspect. And then of course they make the money because they charge as a commission. So it's no skin off their back, but anyhow. I don't know on that one. That would be a good one. That'd be a good one to ask a lawyer, honestly. Mm, good question. Did I hear that Ivan, that World Bank, Slime, Syndrome Bank, St. Petersburg is in Bitcoin, their balance sheets? Yes, that goes into, some people said it goes in effect already, but I've also read that it goes into effect on December 15th, 2024, which will be in a year. You see there December 15th or January 1st, 2025, one of those two, which is good. That way 2%, they don't stop. They can keep accumulating Bitcoin, hopefully. I think Scott says they just picked up a Keystone Pro. Nice. Why isn't YouTube taking down the Fig Charles Hoskins now? I've seen it for two days now. There's a funny thing about that. So the video you're talking about, this Fig Charles Hoskins and Ed, watch this. Let me share my tab. This is what you might have seen today, at some point. This is a scam. Here's how you can enter the giveaway. Find the QR code on your screen and scan it. It will direct you to our official website where you will see further instructions. This giveaway is our way of giving back to the community that has stood by us, believed in our vision and held Ada through thick and thin. We are here because of you and we want to ensure that you share in our success. Yeah, yeah, yeah. So I know people are saying, that looks so fake. Who would fall for that? Okay, here's the thing. Most of us are gonna fall for that, right?  Maybe your eyesight's not so good. Maybe your hearing's not so good. You look at that, and of course, those are the ones that are the most vulnerable, right? If they take a look at that and go, maybe this is the way things are done. Now, I hear these airdrops. Now I see an airdrop right here. Good thing though, is they're like, now just scan this code. Hopefully the older generation doesn't scan too much. But I think because of the coronavirus, we're all very adept at scanning things, like menus, remember that? So I think people are gonna fall for that left and right. And the funny thing is, let me pull this back up, is I asked this question directly, and I said, hey, YouTube, the scam's are only getting more sophisticated, and this is pretty scary. And Team YouTube said this, sorry to hear this, while we can't try to remove bad ads from our platform, we also have the community members to flag them. Be fine ones, you think it's appropriate, you can report it here. So I'm like, well, that's great, but don't think it actually got done. So that's YouTube for you. I'm always amazed, like, if you can make AI kind of look like Charles right now, imagine in six months what it's gonna be like, it's gonna look perfect, right? So if you can do that with AI, can you just incorporate AI into your ad review process? I would think that YouTube could do that, Google could get that done. I'm not just saying, maybe I'm crazy. Look at this, BL says, I fly it two days ago. Yeah, Chris says this, I'll leave it this, grandma pays her light bill with the Apple gift cards. I mean, some people fall for it, and that's true. Anyhow, look, everybody, that's it for today. It's Friday, it's a beautiful day here in Puerto Rico, as usual, but that's it for this session. So if you liked today's video, give it a thumbs up, because you're subscribing, everything we talk about is time-sensitive. Thanks so much for stopping by, do appreciate it. And remember, things are gonna get pretty crazy coming up in the next year, so get your information from somewhere, because it's gonna go pretty fast. All right, everybody, thank you, and I'll see you guys on the next one. Have a good one.


Thank you. Thank you. Thank you all for coming here. It's nice to have some people in the room at least So yeah, I'm here to talk to you about the concept of developer portals and Tell you how not just this community, but every free and open source Software community can benefit from having one now the problem is that I could talk about this for days But we only have a very short time here So I'm gonna have to fly through it on a very basic level But if you would like to discuss details with me, you can always just contact me on Twitter Or I'm in KDPromo channels every day. I try to be online most of the time. So yeah, you can Find me there. So so this whole talk was actually inspired by developers by you by people I work with at this company versus labs where I work as a technical writer by my friends who are developers By developers I talk to online in different contexts. So in in these talks with the developers I realized that they often feel like they're taking for granted Especially by managers They're quite a few managers who treat their developers as cold monkeys and are not really aware of their needs and issues And it's true that you developers are very smart and self-reliant But sometimes you also need help and this type of help that you need is very different from the help that our end-users need and As a community that wants to grow and that wants to attract new developers It's it's very important for us to accommodate that. So luckily In recent years even some big software companies have started realizing this, you know That developers actually matter and that they need help so you can see initiatives like developer relations or their role for short So that's basically a technical community management It kind of boils down to building a community around a software product and Trying to give those developers use that product as many resources as they need so that they can be productive and successful So it's a basically a two-way relationship between the developers who give feedback To the company and the company who tries to make their product better based on that feedback So developer experience is analogous to user experience because as we know developers Are also users they just use software in a different way So the things that matter to developers are different than those matter to to the end users So in different studies of developer behavior and expectations the results show that Documentation influences developer experience a lot more than many of you may think For example poor navigation Insufficient or completely lacking information no working code samples Those are all things that make a bad developer experience and this is where developer portal step in as a potential solution So what is a developer portal? It's a self-service hub that contains all the resources that developers might need to understand and work with a product You can also extend this concept to include end user documentation such as user guides You know your regular user manuals and then you can just call it a documentation portal But the basic idea is the same. It's the landing page It's a complete information architecture that's designed to support your documentation and then by extension your product and your whole community So when you're building a developer portal, you're gathering all this shared knowledge in one place and This is this is important because it becomes a place where developers start to build their own things based on your technology It's also important because it's a place where businesses and our corporations start to see how they can make use of your technology and if we want to be successful and work with You know big businesses We should start building a developer portal because it has a major influence on people who interact with your With your products. It's very important to get it right. So how do we get it right? these will be some essentials that Every developer portal should should have so it's search we have a search function basically you're telling developers Here's how you can find whatever you need You need working code examples obviously so that they can start working with your Software with your technology immediately. So you're telling them here's how you can start building your own thing You also need full references if have API's always have a full API reference on your developer portal So that's like telling them here's everything we have and You need some kind of human contact information Whether it's a link to a mailing list or Telegram group or whatever just to show them here's how you can find help if you get stuck It's also extremely important to have different types of documentation to accommodate Developers on different parts of the developer journey. So for example, there's a saying that a getting started doc Should get you from negative 10 to 100 where negative 10 is a person who doesn't know anything about your code or your product but if you have only those guides and you don't have anything for people who are for example at 8 or 80 out of 100 so they know a lot of things but there's some key missing parts if you don't have Resources to support them. You're losing quite a bit of a chunk of your potential developer community so Obviously when you try to build something like this, you want to know what's in it for you So what do you get from it? So some things that this could help with our on-boarding? For example, we talk a lot about on-boarding in this community and it's obviously very important So this could make it easier we could have you know instead of digging through code and sending people thousands of links you just send them one link to this developer portal where they can find everything and When documentation is scattered around it causes confusion for people who are new obviously So you can always tell them to just Google it But when you say something like this to a person who is new to a community, it doesn't really leave a nice impression. So You know better to avoid it. It also reduces Time to hello world, which is an actual metric that is used to measure efficiency of documentation So how fast can a person start building their own hello world application immediately after reading your docs? When people read the docs they usually do it because they have some kind of a problem or they're frustrated They are trying to solve it quickly So they don't really have time to read through very long detailed Explanations so, you know, we have to accommodate for this They also scan instead of reading so the layout of your portal should accommodate scanning first, right? So, um, what else the existence of a developer portal is actually a major trust signal in itself and The more information you add to it The stronger your trust signals are so what this means it means that you're sending a message to Potential new developers that this project, you know, it's growing code is being maintained.  It's not a dead project or anything like this You also target very different audiences when you have such such a variety of content and it helps also to To optimize for search engines for example when you have all the documentation in one place It's easier to optimize this one page in three different pages in three different places So you can also target developers from other communities or as we said from businesses Who want to integrate with your with your technology? It also increases visibility among members of other Communities and it's it's an opportunity to showcase your software projects in a different way than you would usually do So you can say we usually promote software to users as you know This is dolphin our file manager. You can share files here, but on the developer portal. You can give more prominence to some developer related features You can tell them how to build integrations with different for example file sharing services or stuff like that So you can also use this portal as a whole to improve the image of your community as one That's very easy to work with because you have all these resources in one place and they're they're easy to find because in promo We see people online all the time They're asking how do we start contributing to Katie where do we start? So if we have a good answer to this it will be a lot easier to convince those people to actually join us so Let's look at a few examples of developer portals that actually exist in other freedom of source Software communities. So this is fedora. So as you can see they have actually some really nice Calls to action immediately on this page. They give you links to tools and Resource that will help you help you start Developing basically immediately. So they're they're aiming to reduce this time to hello word that we mentioned You know has a very simple one But again also has all the essential information on it. It has some useful links It has the link to the full API reference which we said was very important and they also have an interesting thing Right at the top. It's not very visible, but they let you switch contacts quickly So you can switch between developer and user documentation on the same page Which can be a helpful actually and then this is a snap craft I'm not sure if you can see that snap craft.io for building snaps, right? They have this really really cool thing that developers I've heard appreciate a lot Which is co-examples in a bunch of different programming languages So this can be extremely helpful and if it applies to your technology or to your project It's really good to have this. So what do we have in KDE? So how does it look like when someone joins and These documentation well our problem from the way I see it is that it's all scattered everywhere It's very decentralized. It's not a huge problem, but it's still something that we could maybe optimize and do better And a developer portal could be a way to solve this. It's not the only solution, but it's it's a good start This is how people feel when you tell them things like this when you give them a bunch of links and then they don't know where start So how do we fix this? Well, we could have an Approach that combines a centralized and decentralized Approaches to develop a portal. So if our documentation is already decentralized We don't have to move it all to one place immediately. We can just build one landing page that will connect them all So in this way, we'll kind of mask the complexity that we have and We will still have this one central place that we can use for search and for highlighting Different types of documentation. So yes, we have this docs.kd.org Which has some problems for example search. Can you find a search on this page? It's very small It's very like up in the corner and it should be front and center and also when you have to explain the navigation On the page that means the navigation is not really that great, is it? So yeah, this is something that we could improve and I already know that there are projects working on this I think Carl Sean who maybe not here not sure. Yeah, you're dead. So he has plans for improving this. So that's great We have this also which is kind of better than the previous one This is wiki.kd.org. So it has like some Semblance of what a developer portal could be but it has this weird mission statement thing at the top Which is like weird flex, but okay It's yeah, so we could we definitely could work on this to make it better So it's yeah, it's not great. It's not terrible. There's always room for improvement So how to fix any documentation you have any documentation? This is how you can fix it which should basically repeat what I said at the beginning So you need a better search you need better navigation always need code examples when you're writing for developers The first thing they want is always code examples and yeah, definitely make it look modern when I say that I mean don't leave pages outdated the same way they looked You know in the beginning of the 2000s because that kind of sends a bad trust signal it doesn't It makes the site look untrustworthy basically because it's not immediately obvious to the person who is Visiting it for the first time that it's actually being developed developed and maintained so try to work on that So yeah, I think I'm almost out of time So if you think that the KD community needs A developer portal here are some things that you could do or you could start doing so we could build a centralized index or a catalog or however you want to call it of all KD documentation And we could have a search that will use whatever Back end we want to use in in in the background to to actually search through everything or we could start small You could take your own project whichever one that is and you know motivate people to actually start improving the docs based on some of the Things we mentioned before so more code samples different types of documentation Different types of guides right once forgetting starter once for doing more if you don't have a detailed API reference do include it Definitely keep working on documentation I think now is kind of the right time to do it in this community because There's already been so much work done on it as you've probably heard in previous talks today during the goals discussion Good thing about documentation is that it fits into every goal because you know better documentation is always a good thing to have So whichever goal you're working on or trying to contribute to documentation will always fit into it So try to do that. It's also cool to think about options Such as documentation sprints or hackathons where people get together and instead of coding as you do They would actually work just on documentation or you could maybe have something like an indexing police I couldn't think of a better name for this, but it would be a group of contributors who don't even have to be They don't have to need have some special technical knowledge They just need to be able to observe links that are broken or things that are not indexed properly And they would just report a list of things that are not linked or things that are missing from documentation They would report this to you and then you can start working on it in more detail and if you want to see some really good examples of Developer portals if you go to the portals of the world or the org That's a site that every year. Well, I think since last year they nominate and award Different developer portals in different categories. You could get a lot of inspiration from there And yeah, definitely keep working on docs and if you want to talk more about this Reach out to me. Thank you for listening. I don't know if we have time for questions probably not Yeah, maybe Ray is the next speaker so you can set up and maybe if there's a question You can answer this while Ray connects his computer. Yeah There are some questions. Okay Hi, Vana. Thanks for a great suggestion Justice suggestion.  Maybe start a fabricator task or something so people could join in and Haven't started anything yet. This was just an idea, but if you think it's worth of Starting an initiative. I think we could do it. I think it's definitely the worth it. So yeah, go for it so one of the four basic principles of agile development is quote the value working code over documentation in Other words the best code documents itself. So what's your take on that? Oh, I heard that I've heard that a lot and in my workplace a lot of people like You advocate entirely different approach I'm not sell you like which of those approaches I like based but like how how does it square? Is it like entirely orthogonal to this like working working code over documentation or can those two principles somehow complement each other? Well, I think you need some kind of documentation for people who are starting at least So you need to know how to start to work with something and then you can only start understanding the code I think do you expect? Newcomers to start reading the code immediately and not the dogs. I'm not sure if I get your quiz. I Don't think I don't think the the thing you mentioned is completely completely at odds Aha true. Yeah, that's true. That's true. But then again, there's a lot who don't so I guess it depends on the industry or your approach I personally think that you always need some kind of documentation at least something basic And then it all depends on what you're aiming for you don't really need a developer portal if you don't want to attract developers It's like as simple as that But if we do want to grow as a community and there's already so much invested in this I think this could be a way forward, but it doesn't have to be right


Thank you, Pierre. Thanks a lot. And thanks also a lot to Benelah, who did a really great talk right before me. So, yeah, I'd like to put forward the concepts of psychoinformatics, as opposed to neuroinformatics. And what I'd like, and I'd like to show that machine learning on brain imaging, I think, can really bring something to the field, and has brought in the past. So what I would really like to do here is to propose a research program and to illustrate it by things we've done in the past. Really, the start of this research program is that we're really, these days, accumulating functional brain data that is extremely rich and that is getting more and more standardized and reusable, and thanks a lot, basically, to the effort of mostly people who are here. And really, the question is, how are we going to use this to ground theories of the mind, and what I call the theory of the mind, is basically laws for perceptions, decision action, emotion, basically, for the cognitive functions. And if we think about how, currently, we typically study mental processes, the way we will work is that we're going to craft an experimental condition that recruits a given mental process, and we're going to do some form of elementary psychological manipulation, and then, most likely, we're going to contrast those. And so what this is telling us is that we typically study mental processes via oppositions, and I find that this is a very strong reductionism. I find that this is a limiting factor, and one of the challenges is that to interpret the results, basically, we're bound to a paradigm, an experimental paradigm, but sometimes a conceptual paradigm. So, this is a real challenge, it is not an easy problem, and what we're proposing is that generalization is really a guiding principle that can be used to build broader theories. And the kind of generalization we're looking at is can we go from one given experimental paradigm, so, for instance, you're showing a stimuli to subjects, to another one, for instance, the subject is thinking about stimuli. And why this is important is that the experimental details are different, so you can believe that your results are broader than the experimental details. So the challenge that we're going to be facing is how do we bridge paradigms, and this is actually a very difficult challenge. So we're going to be using brain imaging to do this, mostly functional brain imaging, and basically we're going to be using it to learn brain mind associations. And I've been doing this for a little while, and one thing I've learned over maybe ten years is that the imaging part was the easy part. At least I believe that modeling the signal, which is basically what I've been doing for ten years, is the easy part, and the hard part is modeling the brain, the behavior and the cognition. So Russ Poldreck and myself have just finished writing an opinion paper that claims that predictive models can broaden theories by generalizing brain mind associations to arbitrary new-task and stimuli. And so hopefully this is going to be out soon. I want to explore and give examples of concretely the challenges that we face by doing this and how we can address them, and I'll show several examples. And I'll be basically walking in Pamela's footprints, so I'll start with encoding models, and I'll show you that they can go beyond a position. And this is mostly based on a paper that we published last year with Michael Eichenberg. So we were interested in vision, and the challenge in vision is how do we break down the ecological situation, which is complex natural images. So we need to break down those complex natural images into elementary psychological processes. And historically this is being done. Vision is an area of cognition where we know many things, and maybe the projectmatic experiment is the one of Huber and Wiesel, where they showed that basically the V1 neurons were receptive to GABA or filters, were receptive to edges. And to do this, they crafted specific stimuli and they showed them to cats. And later on, people continued working in this direction, crafting more complex stimuli and showing different receptive fields. And so the current picture of the visual system is the one of a cascade of regions that are specific to specific aspects of the stimuli.  So maybe we have a foot detector and maybe we have a left big toe detector, okay? So that's all good. I can craft an experiment that will do this and I'll craft stimuli that have a left big foot and I'll oppose them to stimuli with faces. I'll acquire fMRI data, I'll acquire lots of fMRI data, I'll do a contrast and if I have enough stimuli, I'll get something that's significant and I'll publish about my left big toe region and probably won't go through in a good paper. Why? Well, because people won't believe that I've used good stimuli, they're not well-balanced, and people will not believe basically that I have a proper theory, cognitive theory that analyze my experiment. And so what I'm showing you here is that boiling down cognition to a new position is extremely fragile. And if I take a stupider position, then I'll get a result that will be significant, maybe interpretable, in the sense that I will have found a region that is different in faces and left big toes, but not interesting. And I claim this is because we're reducing too much cognition during those experiments. And the nice thing is that encoding models allow us to go further because they can first be used to build complex representations of the stimuli, not simple one, and once we have this complex representation of the stimuli, the only way we can do statistical analysis is basically predicting the brain response, and that's for technical reasons because those very high-dimensional objects basically call for high-dimensional statistics, and high-dimensional statistics and machine learning are pretty much the same thing. So if we want to go back to the visual stimuli, how do we decompose visual stimuli? Well, we can follow the footsteps of Alhousen's and Field that basically tell us that the reason that low-level visual cortex is tuned to image statistics is because – is tuned to – sorry – to Gabor filters is basically because those are the simplest representations of natural image statistics. Basically, any kind of simple analysis that you do on natural images will show you that they're what are represented with Gabor's. So what drives high-level representations? So we can use the modern, powerful statistical tools to address natural images, which are basically convolutional neural nets. And so what we can do then is to take convolutional neural nets and to build an encoding model from this. Now, the way this works is that we take convolutional neural nets that have been trained on natural images. So basically we take readily-trained convolutional neural nets, and then we take a data set where subjects have seen natural images. We represent those natural images with the convolutional neural nets because the continents have several intermediate representations. From those intermediate representations, we build an encoding model that is basically trying to predict brain imaging, all right? So we were not the first to do this.  And so what we showed is – and what we and others actually showed is that these features of natural images, so the intermediate representations, explain the stimuli much better than handcrafted features. And what we showed that we found was really interesting is that they not only explain brain imaging, but they also map the visual system. So what you're seeing here is which intermediate – which layer of the convolutional neural net maps best to brain activity. What you're seeing is that we can see a gradient basically of low level to high level, and we're really actually mapping the areas of the visual cortex, but in a way that's actually fairly weak in terms of hypothesis. We haven't decomposed or stimuli to oppositions. So once we have this, we can actually – what we have here is basically something that can predict brain activity. So we can use it to simulate classical experiments. So what we've done here is that we've done a synthetic retinotopy. We've taken our model of brain activity, we've predicted the brain activity for wedges, and then we did a standard analysis on this. So what you're seeing here is basically a response to eccentricity, but artificial. So it's an artificial retinotopy. So it's showing us that our model has captured things that artificial stimuli also capture. And so we also did the same thing using phase versus place oppositions, and what you can see here is that – so we used – to generate these maps, we used the phase versus place stimuli of the historical XP experiment, and what you can see is that they have actually different low-level statistics than the one there are in the Gallant studies. And so what we're showing you is that the high-level properties are carrying over, even though the low-level properties are different. So what I really like about this work is that it really shows that we can go beyond opposition, that without oppositions we can recover the full hierarchy of visual modules, but more importantly that it generalizes across different patterns. So the results that we have show that we've worked on data sets that were natural images, but we can reproduce classical results that are done with extremely non-natural stimuli. So this I personally find exciting. Now the question is can we go one step further? Can we generalize to arbitrary paradigms across tasks? And this can be useful to characterize the function of brain structures. So really the question here is how much observed activity is a consequence of the specificities of the paradigms? And the school of thought, I would say, is the idea that you can use large-scale decoding for principle reverse inference. So basically we would like to conclude on the function of given brain structures and using decoding across paradigms is useful for this. But this is challenging because what we find is that the paradigms that may study similar mental processes may have a lot of things and difference. For instance we could be giving a visual stimuli versus an auditory stimuli. And here I should have put the auditory stimuli in French. So is this a confound or not? So there are two kinds of heterogeneities. One of them is technical, so scanner, stimulus, modality. But one of them is a fundamental problem in psychology which is the pragmatic isolation. And this is a problem that has been well-known and that has been put forward, for instance by Newell in 1973 where he claimed that you cannot play 20 questions with nature and wind. So there's really this challenge of generalizing across paradigms. And so what we did, so basically the question we're asking is if you give me an image of brain activity, what can I conclude about the ongoing mental processes? And so the way we tackle this is that we describe the tasks by their cognitive components. So we did this in a predictive setting. And in this case this is what's known as a multi-label prediction. So it's not a multi-class prediction in the sense that you're not trying to assign each experiment to one class, you're trying to characterize one experiment by a bunch of different labels. So we're using a cognitive ontology to label experiments. And we're using cock-bow. And then we're trying to generalize across study. So basically we're trying to describe the tasks that we've never seen from the brain activity of books. So where we're trying to get at is we're trying to find regions that are specific to certain facets of cognition. But specific is a word that has many different meanings. So I'd rather use that predict facets of cognition. So we've done this on a fairly large database that was actually assembled many years ago by Yannick Schwartz. It has many studies and many different subjects and many different experimental conditions. But what I find really interesting is that it has data that comes from different labs and different cognitive science labs. And having worked with different cognitive science labs, I know that there are different opinions on what is the right way to conduct a cognitive neuroimaging experiment. And I find this really interesting to see if we can generalize things across those different ways of working. And so the answer is yes we can. We get a reasonable prediction accuracy across a variety of different concepts. Some of them are harder to predict than others. Though I wouldn't jump on the conclusion because with only 30 studies, we don't get a lot of redundancy. What we found is that it's really important to use some form of ontology to shape those labels to predict and this gives us a better prediction. Then I said that we wanted regions and there we have to address a challenge that Pamela mentioned, which is the fact that when you have a non-identity covariance, you can actually pick up regions that are not marginally related to what you're trying to predict, but conditionally related to what you're trying to predict via the noise. So the way we tackle this is basically we do some form of conjunction between a standard analysis, so a forward inference, and the decoder. I won't go into the details, but basically we're trying to have something that is both conditionally and marginally related to the aspects of the stimuli we're interested in. And so if we do this, we're really narrowing down on the important regions. This is for the concept of a place in the brain. And so here I'm comparing different approaches. I'm comparing crafting contrasts and what you find is that crafting contrast is actually really hard when you're working across experiments because the stimuli are not well balanced. It's extremely hard to balance the stimuli. So here we're looking at the visual cortex, and we find that basically we tend to overload the mid-level visual areas because it's extremely hard for us to cancel out stimuli there. And the way people work, by the way, is that in a given experiment they work until their stimuli are balanced. But across experiments or cross paradigms, it's very hard to do. So I'm showing the Neurosynth reverse inference, and it actually does much better, but it still has trouble separating those mid-level regions. And I believe that the reason this is the case is because the Neurosynth uses a naive-based, the Neurosynth reverse inference uses a naive-based decoder. And a naive-based decoder is basically a univariate decoder. It's just a sum of univariate decoders. So it's not marginalizing on the activity of other voxels. And so what we're doing is we're using a multivariate decoder. It's basically some form of complicated linear decoder. And when we're doing this, we're conditioning on the activity of other voxels. So by doing this, this is actually removing basically the joint information. And this is helping us to narrow down on the most important regions. So we basically are covering the cortex with this breaking down the cortex into different relevant regions. And so basically we're getting a map of what I call the map of reverse interference. So I've shown you that generalizing across tasks with decoder was a powerful tool. To do this, we've had to move away from the classic oppositions that basically classification uses and use the multi-label setting. One thing that we've found and that's something that we've found quite often is that prediction using discriminative models is more robust to heterogeneity. Here we have paradigm heterogeneity and basically standard statistics pick up imbalances very fast. But discriminative models, because they're discriminative, can be more robust to those imbalances. So one thing I'm excited about is that these results are grounded on some clear measure of prediction accuracy. And I think this makes those regions more trustworthy than regions that are just achieved by delineating them from a review. And the reviewers of this paper didn't agree with this, by the way. And the paper didn't go through PNAS because similar drawings had been published. That is an epistemological difference between the mathematician that I am and cognitive science. So this is, for me this is exciting because this is giving us an alley for what I call atlas incognition. This is one way where we can, as we gather more data, where we can hope to have more resolved atlases of cognition. Now, something that was crucial for this work was that we needed some ontology of cognition. And it turns out that these things are terribly hard to build. And even when you have them, it's extremely hard to label studies with such an ontology of cognition. And I see that NG is nodding because we have been doing this and they have been doing this. And let me tell you, it's just harder than you think. So we tried to go one step further and we tried to say, well, can we actually use the terms that people use in their own study, even though they're somewhat horrible sometimes because they're complete jargon? And can we still use these terms and build universal representations of cognition with this? And the idea being that we're going to do decoding, but we're going to do decoding with a latent structure in the middle. And that latent structure is going to allow us to do oppositions the way people do it, but still find commonalities across studies. And so in machine learning, this is typically a multitask learning problem. We're solving many related problems, but different. So it's many classification problems, not a multi-label problem because it's allowing us to go around the ontology problem. And the idea being that we're going to learn commonalities via the intermediate representations. So for this, the first thing that we want to use is deep learning, deep architectures. And they're really great for multi-output, so a multitask. And basically they learn intermediate representations that can capture a lot of information. Now, the problem, as we've heard in the talk before, is that they typically come up with a huge amount of parameters. And we probably don't have enough data for this. So we're going to simplify them.  So what we're going to do is that we're going to do basically a deep logistic regression. And I'll explain a bit more. So what we're doing, I know this slide is kind of complicated. I don't expect you to see everything there. What we're doing is actually a two-headed hidden layer, so a three-layer deep linear model. And why is it linear? It's because we have no nonlinearities in the middle, and empirically they didn't add anything. So we're stuck with no nonlinearities. So the first layer is actually trade unsupervised in a way that is similar to what the first presenter was presenting, or actually in a way that's similar to learning on ICA or PCAs. So we're using non-negative matrix factorization or addiction earning. It's the same thing on a huge amount of resting state data. And what we found is that the more resting state data you have, the better. And we're learning 512 components. So it's 512 localized brain modules. And then on top of this, we're training a factorized logistic regression or a deep logistic regression.  And what we found is, and so this logistic regression actually has multiple output heads because it's a multitask problem. So we're solving classification. We're solving decoding in each study jointly. And so technically getting this thing to work was really hard. So my student, Artur Mencher, did this really amazing work. And what he had to do was to use Bayesian deep learning techniques that we found out were good regularizers for this. So if there's one technical take home message, Bayesian deep learning is interesting. So what this gives us is intermediate representation that we call task optimized networks. And these are really powerful because we can use them then because so they're... I'm talking about these guys. And on top of this, what we have here is just a simple logistic regression. Oh, sorry. These guys, right? And on top of this, what we have is just a simple logistic regression. So these intermediate representations will improve decoding in each study. So if we compare logistic regression to learning on these intermediate representation, what we find is that we almost always get a gain in accuracy, ranging from 15% to actually sometimes a loss of a few percent. And what we're finding is that this gain is actually related to the study size. So in our group of study, the very large studies don't benefit. The small ones benefit a lot. And we can go even one step further and we can compare the decoding accuracy with a simple logistic regression and our deep linear logistic regression. And what we can see is that the less subjects we have, the more the impact of this model. And it makes sense because this model is actually transferring information from the big studies to the small studies. So that's one thing I'm excited about. We know that we're underpowered typically in cognitive neuroscience. We also know that we need many studies to be able to explore the different aspects of cognition. So I hope this is an ally forward for this. And so I can show you the corresponding brain networks. And I'm sure you can't see anything here. So let me zoom in. So what we have is that we have brain networks, but we can also represent how they're loaded in the original names that people are giving to their contrasts. And so you can find that there are all kind of horrible names. For instance, I don't know if you see, but in purple there's C01 and C02. C stands for complexity. It is people who are looking at the complexity of sentences in language. Now capturing this in an automated analysis is terribly hard. It really requires you to read the paper and sometimes to ask questions to the person who did the paper. What we're finding here is that we're able to use this information without manual labeling because we're able to use the original labels that people are giving. So what I've shown you here is that using multi-task decoding across many studies, we're able to extract some form of universal cognitive representation. And I call it universal because if I bring in a new study, it improves decoding power in this new study. And for this, we use deep linear models that basically share intermediate representations across study. And I think this is very useful because it will improve the statistical power of small studies. And so once again, if we look at the networks, they're somewhat meaningful, sometimes extremely meaningful. And if we look at the names that are associated to them, we understand them. So for instance here, it's motor, but it's also right auditory visual click or object grasp. But doing this in an automated way is extremely challenging. So as a human being, you understand that object grasp and motor are related things. But it's a knowledge representation challenge. I think it's an important one, but it's not there yet. So I want to say a few words really fast about learning across subjects, and then I'll wrap up. So learning across subjects promises us to give us biomarkers, and this is an important challenge. And I also hear a lot for this and for other things that heterogeneity is going to kill this research agenda. And this heterogeneity can be in the scanning, but it can also be in the clinics. So typically if you're looking at for instance autism, autism is a disease that has a lot of heterogeneity. And what we've been finding, so last year and this year with a new, with actually a competition that we ran in the lab, is that if you have enough data that you're able to sample this heterogeneity. So samples, so basically you're using, so if your heterogeneity is one across sites, then you're using multi-site data. And you're predicting across sites, then if you have enough data, you're basically able, as far as I can tell, you're able to address it. So I don't think that heterogeneity, well, I'm sure it will become a problem. But first I want to see it, because so far what I've seen is more data always performs better. And so we ran a competition, I don't have the results yet, but we ran a competition on autism. A prediction on a larger data set were in the hidden test set. There was a site that we were not allowed to share. And on this competition, people did 81% AUC, which as far as I'm concerned is huge for autism. And they actually did better on the hidden test set. And the reason is that the data quality was better. So more evidence that heterogeneity is not a problem. And then the other thing I'd like to talk about is we're really struggling with the labels with this research agenda. We sell them, have the information that we would like to have, but we can actually learn from labels that seem uninteresting. This is work that was done by Frans Lyem a few years ago. And what he did was that he tried to predict the age of people looking at their brain.  I can just look up their birth date and know their age. And the idea is that there's a difference between aging and colorological age. So he was able, using multimodal prediction, to go down to a mean absolute error of 4.3 years, which is quite nice. But then the amazing thing was that the discrepancy with people's colorological age and the brain aging actually correlates with cognitive impairment. And I mean, we were kind of hoping this, but not at all to see this in such a clear way. So my take home message here is that even labels that are not the most thrilling are bringing us interesting information because basically they're allowing us to extract quantitative information from brain images. All right, so I want to wrap up. I'd like to pitch the concepts of psychoinformatics as opposed to neuroinformatics, which is focusing on the mind and using brain images to focus on the mind. And I find that a prediction is a guiding principle for broader theories. Partly because if you're interested in cognition, you can use AI to model stimuli or the world. But partly also because explicit generalization across paradigms is something that's extremely powerful, though a bit challenging. And so this should allow us to go beyond a position. For instance, to use encoding models with a complete description of the task and not just, you know, tiny description of the task or to decode multiple facets of cognition. And this is useful even if we have imperfect labels. So we can extract common representations across many imperfect labels. We can extract surrogate biomarkers. I skipped over all the technical details.  So basically I spend my life doing technical details so you can find them in my papers. Or you can use the software that we developed, Nylon, that doesn't have all our fanciest models because I'm very skeptical. I'm very worried that my fanciest models are maybe not the best. And so we don't put them in Nylon by default. It has simple tools to easily scale. With that, thank you.