Hi everyone, my name is Paul, I've got a lot to go through so we'll kick off. This is the country that I live in, this is New Zealand, this is in fact the South Island, we've got two islands, we've got the North Island and the South Island, it avoids confusion, we named them that way to avoid confusion. So this is, I live on the North Island in fact, I work for a company called Fairfax Media and we are one of the largest media and publishing companies in Australia and New Zealand. We are in the newspaper business, which I don't know if you've heard is in a bit of bother, things have changed for us quite substantially, so this talk is about us and what we're trying to do to survive the situation that we're in and I described the situation a bit more, it's a case study essentially. I don't have answers, I only have ideas for how we can progress this.  You're all good? Great. My wife insisted that I put this photo in, I'm sorry this is me pre-beard, kind of beardish, but I'm agile lead at Fairfax in Wellington, Fairfax New Zealand. So we've got agile teams, I was really pleased to see Mary's talk earlier that we tick a lot of those boxes, we're hypothesis driven, we are working towards continuous delivery, we can always improve, we do a lot of good things and the internal teams are set up really well and now we also work with a lot of vendors as well and we consider those vendors to be our partners and we try to develop long term relationships with our vendors, we don't want to have this short term project mentality, we want to develop that relationship. I've been in the business of software for about 25 years now, initially a software developer, about 10 years ago I moved into an agile space after working for a big government project which didn't go too well, we failed, we didn't fail to deliver, that was a horrible thing, we actually delivered on time and on budget but when the customer actually saw what we delivered they said it's not what we wanted, which is the worst feeling in the world when you build something for a customer that they don't actually need or want and it took another 6 months, so it took us 10 months to get to that point and then another 6 months to rework it into something that was actually usable and I thought at that point I left, took 3 months off, thought there's got to be a better way of doing things, I really had it had enough I came back in, I got pulled back into several startups, I started one of my own and then another startup where we were allowed to do things how we wanted and we took things in an agile way and to us agile just meant collaboration with the people we were building things for and regular collaboration, they were actually part of our team, that kind of thing so that's my story, I joined Fairfax a couple of years ago I was looking for a challenge and I think I found one most people know who Kodak is, right? I don't think there's anyone young enough in the room to know who Kodak aren't they were a big Kodak and Fujifilm, there were two big players in the world as far as film was concerned everyone has photos like this, I'm sure you've got stacks of photos like this in your attic somewhere or lying around somewhere or in albums and what people don't realise is, well, one Kodak when it bankrupted in 2012 that's the first thing, but the other amazing thing is they actually invented a digital camera they invented a digital camera in 1975, this is the first digital camera here it's got a, this is the inventor by the way, he was 24 when he invented it and they've actually got a cassette on the side here this is like a normal audio cassette that we all had in those days and it took 23 seconds to download the photograph once it was taken, it was a very small CCD, it was all based on CCD technology one of the first uses for camera, definitely the first use for camera, sorry but it was one of the first uses and he took it to the executive and they looked at it and said no one's going to watch, no one's going to want to look at photographs on their TV surely why would anyone want this? and the marketing and executive basically said that they weren't going to progress this idea they also realised what a huge disruption it was going to be on their business and they didn't want that disruption they pretty much owned the entire product line from start to finish from film to printing and processing and so on and even when Steve and a colleague invented the first digital SLR in 1989 I think it was they got the same reaction from the board, no they just didn't want to know the technology wasn't, to be fair the technology probably wasn't in place they couldn't see that the technology was there to enable this kind of approach to photography but they still maintained that it would be a huge disruption on their existing business model and they didn't want to disrupt their existing business model it's really hard to do that by the way, really hard, I know from experience so our code at the moment in the printing or newspaper industry we had a very similar experience and that's why I wanted to put code out there because it's a very close analogy to what we've done we entered the digital market ourselves but we were scared of digital the newspaper was making so much money for us our revenues were huge from advertising primarily but we just didn't want to challenge that business model and even though we could probably see it coming we still had our heads in the sand so this is a bit of a history of us in Wellington we're approximately 150 years old in New Zealand so printing started back in 1865 with the evening post then a competitive kicked off in 1907, the Dominion these were bought by Rupert Murdoch's company in 1972 by then there was about 40 or 50 publications he eventually merged the evening post and the Dominion into what we now know as the Dominion post it's a morning paper we went live with our online offering in 2000 Murdoch sold to Fairfax Family in 2003 in the US in the meantime advertising revenue was reaching its peak of about $50 billion a year for newspaper in 2007 most of us know that there was a global financial meltdown and advertising revenue went off a cliff I'll come back to that and then iOS apps, Android apps and so on and by 2011 advertising revenue was halved in the US to $25 billion and it wasn't until then that we got our mandate to transform into a digital first company we'd been resisting for that long the writing had been on the wall for that long but we still resisted and it wasn't until 2012 when our new CEO came in he had a digital background he said right what are we doing this is no longer a print industry a digital industry and you guys need to transform this business we still have printing plants of course our latest upgrades to our printing plant cost $20 million we've actually consolidated we share print plant with our major competitor we share distribution costs for them as well New Zealand is not a big country I guess most of you already know that but there's only 4 million of us distribution is quite high though it's about $40 million a year for example for print alone it's quite a major task we've just recently had a huge success in the sense that we've launched our digital first authoring platform which means effectively we've got an operational backbone which enables us to print focus on digital publication first and foremost but then allows us to syndicate content through to other formats quite easily and it allows the journalists to be in one application and one way of entering their content and they become a digital first newsroom so just a graphic for you to see what happened in 2007 this is well it reaches its peak here in the US this is in billions of dollars and then 2007-2008 when the meltdown happens it goes off the cliff and everybody expected it to come back but of course it didn't come back it just has declined further and further along the bottom here the grey line we've got the digital revenue and that's what we make from digital advertising not significant at all for us not to support the business that we have anyway or the current business model that we have and then of course the middle line is Google and their global revenue and they're currently about $60 billion in global and about $16 billion in the US so Google and a number of other social media types took advertising away from us essentially we also lost other sources of income like classifieds for example which went to eBay and Craigslist and locally for us it would be Trademe we don't have eBay in New Zealand as such which is the major player and a number of other factors contributed to this so digital disruption the adventure begins Jean Ross she's based at MIT Sloan and she has a theory that she calls smack it and she says it sounds it feels like it sounds smack it you know it's social media mobile analytics and internet of things and she says these have all come together to the confluence of these technologies that's provided the opportunities for disruption in this market or in any market there's also things that are followed up behind this like cognitive computing and biometrics for example all of these things contribute to different ways of delivering or changing the value proposition of something that you already do and enhancing it to make it better so it's much easier for someone to obviously enter our market and compete against us our printing press costs a hundred million dollars plus in one plant no one could afford to enter our market and compete against us in that situation journalists were tied to a newsroom or a news outlet and they wanted to work for the best news outlet then they had to be the best at what they did but now that's all gone the internet's leveled everything for us and technology is a great leveler it makes it much cheaper for people to enter and compete against us the other contributing factor of course is Moore's law and the fact that Gordon Moore predicted in 1965 and revised in 1975 that transistor density on integrated circuits were double every two years and combined with David Hess his observation he's also Intel or was Intel that the increase in speed of transistor technology would mean that raw computing power would double every 18 months now hard for us to think what that means that's an exponential growth and that exponential we don't really think easily in exponential terms it's easy for us to think in linear so 30 linear steps, 30 meters pretty easy for us to see whether that's taking us it's going to take us to the end of this basketball court exponential steps though are harder for us to see five exponential steps take us to the end of this basketball court but if I was to ask you guys how far do you think 30 exponential steps would take us anyone, any ideas? it's a long, long way so not just once around the moon but well, around the moon and back again and out to the moon again or 26 times around the world it's one billion meters so exponential is huge and there's a really interesting guy called Ray Kurzweil he's at the Singularity Symposium or you can find him online at Singularity Symposium and he is one of the guys who predicted the internet back in the 80s and he basically said that he attributes his ability to predict the future in terms of technology because he thinks exponentially or he tries to extrapolate his thoughts in exponential terms so linear this is not the path we're on technology is accelerating and the curve that we're on is accelerating faster and faster as we've to give you another example this is the 1995 Cray 2 computer it's about half the size of the Cray 1 which was 1975 that's about approximate real size compared to an iPhone 5 which has 2.7 times the processing power of the Cray 2 and it's about a thousand times smaller you know for me, growing up with this the Cray 2 was like the standard everyone wanted to get near a Cray 2 but now I've got an iPhone 6 in my pocket I don't even know at least four times, five times more powerful than that so back to Jean Ross at MIT she says there's really only two ways and she believes there's two strategies that you can take but you can only take one, you can't take both because you're going to confuse the problem if you do and she said funny enough you'd probably end up in the same place if you took one of these strategies or the other you'd probably end up in the same place but the first one is customer engagement you focus on how you're going to change your value proposition to create a customer experience that no other company can deliver and you're probably going to enhance it with technology but you're focused on the customer experience and what the customer gets this example here is a company in the Netherlands called Burtsog they're a community care nursing care organization they wanted to solve a problem and the problem was a tiered health care system where people on the front line were giving health care quality or health care based on what the person had paid for so if they'd only paid for a basic health care package they would only get basic health care and that meant a professional a registered nurse being on the front line making decisions about what care that she couldn't give or he couldn't give to somebody in their care which is of course a huge conflict of interest for someone who's in a caring profession so they formed back in 2000 it's in middle 2000 so I think it's 2005-2006 they formed with a specific purpose of offering a single tier care health care system they operate in small teams they have a maximum of 12 nurses or 12 caring professionals in each team they organically became agile in the process because they have very few managers no sorry strike that they have 50 back office staff they've grown to approximately 12,000 carers in their teams now so it's a large organization very little back office in comparison and very self-organized what it does mean is they can deliver health care in the previous system as well people in care could see up to 40 different people in the old system now they get a maximum of 12 people and of course that tight-knit group of 12 is able to have some coherency and consistency in their health care strategy the alternative is a digitized solution and digital offers unique experiences in terms of like enhancing existing products I think it was Mary yesterday as well who talked about GE I believe and the fact that GE have large through the digital solution approach as well they wrap existing large assets like turbines and jet engines with sophisticated data gathering technology which then feeds that back to someone who can optimize and enhance the performance of that large asset Uber did a similar thing they took a market that already existed they haven't changed it substantially it was not disruptive as such they've provided the digital solution which makes it much easier and safer to order a cab and go somewhere, go from A to B that's the job that we're trying to solve here is how do we get from A to B and Uber have made it super smooth as far as I'm concerned anyway it's a much easier much easier experience than ordering a taxi so Fairfax back to Fairfax in our digital strategy and how we're facing disruption we've gone for this approach where this has occurred quite naturally for us but it seemed like we had to lean out our processes and we've created this concept of the lean newsroom or publish ready newsroom so what we're doing is trying to reduce waste as much as possible and support we've got 600 journalists in our team in New Zealand we've published 1200 stories a day we've got quite an operation and any time that we can save those guys in terms of publication is obviously saving costs overall for the company what we used to do is go through a series of sub-editing steps so in traditional print editing or journalism the journalist creates the basic story, outline maybe something quite substantial but then it goes through the sub-editor looks at the title and makes sure the title fits the page they make sure the copy fits the page and so on there's a whole series of steps which means that the original journalist often has really doesn't recognize the final piece of work that's published or printed we've taken all that away now it's just a single person who's responsible from beginning to end publication including on the print side still where we have the print side where those stories are going through to print so we built a software platform we feel like we're quite ahead of the game I'm sure other people are doing similar things in our industry because it does seem quite natural that we had to do this like I said it's what we would call our operational backbone it's what keeps us alive in terms of being able to produce content this is our critical system if you like and this is where we have to have uptime we have to produce content to to survive this is our newsroom by the way we work in an activity based working environment so nobody has a fixed desk we all come in in the mornings we've got lockers we can pretty much work related to the activity that we're doing if we need to work with these guys we've integrated our technology teams with the newsroom in the process of making it a much tighter relationship we don't see us as separate anymore we actually operate we'll locate within this space and work with them as close as we can it's amazing what you learn by osmosis when you're sitting in the environment your customer is working in we've gone down the path of sustaining innovation every company does someone like Clayton Christian talks Clayton Christian from Harvard talks about sustaining innovation versus disruptive most established companies naturally fall into a sustaining innovation model which is what I mean by sustaining innovation is we seek to enhance the profitability of our existing products by going to our more involved and sometimes more demanding customers and trying to increase the profit for them making niche products essentially for people who want to pay us for them so this means that we're looking to move up into our market in other words and we're doing that with a lean start approach like I said earlier we've gone hypothesis driven development driven so we think about problems that we want to solve we test out these problems as quickly as we can well we test out the solutions that we think might work for these problems as quickly as we can we encourage a metric driven culture we want to see results you measure you get what you measure basically so it's really important to think about the measurements so just to give you some more background information we're not in a bad position considering the population of New Zealand is only 4 million we've got half the population as an audience we're not in a bad place we just have to commercialize our product we've got content heaps of content but the problem is in any innovative kind of endeavor is how you commercialize these are the two examples of what we do in terms of like validating ideas as quickly as possible it's a concept called the button to nowhere which means we haven't fully built the product it looks like a fully working product on the surface of it we're really just getting you to click through to a certain point where we can say for example we asked you if you want to log in or maybe register because you want to sign up for this product at which point we present you with a screen which says sorry we haven't finished building this out yet but thank you for your interest please enter your email and we will get back to you when we've finished but we've got some very valuable information at that point which we know people are interested or we can judge the scale of the interest in it the other approach we use is called the Wizard of Oz so I think most of you might be familiar with the Wizard of Oz but it's basically it looked like the genuine thing a big scary guy who was all powerful in fact it was just a guy behind the curtain working a few mechanical bits and pieces so again we build something out but it looks like it's all powerful but in fact it's mechanical in nature or manual in nature behind it but we're just looking for feedback as quickly as we can the other approaches of course are things like A-B testing and so on we just want to learn as much about an idea before we commit to developing it out the third sort of step to our strategy is taking an integrated approach this is really trying to say stop these silos, we don't need silos we're a digital company digital is now everybody's responsibility it's not an IT thing I shudder every time I hear the word IT because I've worked in IT departments this is a whole organization responsibility and we need to start thinking like that it's not one it's not one silo that's responsible for this the important thing with this though is that we like to maintain this concept of the church and the state in the newsroom which means you want to separate those two out you don't want the newsroom to be biased by the commercial because then you get things like sponsored content and native advertising it suckers you guys as the audience into something that looks like a journalistic piece but in fact it's an advert maybe informative but it's an advert even though heaps of people are experimenting like the Guardian the New York Times with that approach we are well aware that we shouldn't be messing with our audience in that way and we need to find alternatives to commercialize things out so we do separate that idea of the newsroom and the commercial and the way we do that is by focusing our internal teams on the newsroom and our external partners on the commercial the content and curation and discovery is at the heart of this for us that's why a lot of people come to us for the news they could get the news many other places hopefully they come to us because they're like minded and they like the content that we're providing they like what we're reporting it's very much like I'll talk to you later about the analogy I've got so Clayton Christensen from Harvard he said the important thing you have to do in this position is think what's the job that you're trying to what's the job that your customer or audience is coming to do when they're on your using your product and he states it quite clearly people don't want to buy a quarter inch drill they want a quarter inch hole just in the same way that when you hire an Uber you don't want a car you want an A to B journey you don't want to be a car owner so we've started shaping our thought processes around what is the job that we're trying to what is the job that the person is trying to do on our site and a lot of that stuff for us is looking at content discovery in terms of people they want to find content easily they don't want to search they don't want great they don't want to have to work to find the things they're looking for fourth step for us is to become a modern broadcaster so we're diversifying into multiple channels we're going through talks to merge with a competitor at the moment in New Zealand no longer a competitor but seen as an ally we actually share printing presses with them already and now we're looking to acquire we'll merge each other into this they will provide radio for us we'll provide internet and newspaper across the country and this is some of the things that we're exploring in terms of other alternative revenue streams this one over here is a community-based website which allows people to sign up and they get news and information in a hyper-local sense you know this is my community this is my friend group and social group in that community it puts them in touch with their neighbours essentially and also events and news that relate to their local or their locality Stuff Nation is a what we call user-generated content it sounds quite sterile but it's people blogging on our site for us so it's curated content in the sense that they are they're blogging and the fifth thing for us to do is to perform some organisational surgery there's something that Gene talks about a lot we've talked already about maintaining the separation of church and state and we view editorial as the audience draw card and commercial as the way of making money but we really need to chop out the silos and think of ourselves as one big organisation that well whatever size the organisation needs to be to support the business model that we're trying to create so that's what we're currently doing that's our approach at the moment we also realise that this thing called disruptive innovation which Clayson Christensen talks about is something that we have to be fully aware of because what disruptive innovation what Clayson means by disruptive innovation is when a technology enables somebody to come in and undercut your market and do something in a cheaper way than you can already do it and essentially what they're doing is taking out your they're either coming in underneath you and taking your customer that isn't feeling so loved because you're not focused you're focusing your sustaining innovation up here and your low profit customers are basically ignored and that means somebody can come in and take that customer from you using a cheaper or better technology approach it's also possible for them to come in from an adjacent market and adjacent markets in our environment will be something like social media that was an adjacent market no one really saw how much that would take the news away from us or news feeds away from us this is the only video store that's left in my city I thought I'd put this up here because this is something that we need to think about these guys are essentially the reason they survived is related to the curated content they nearly went under they nearly closed but the community rallied around them and they're a bunch of movie nerds they love movies I've been in multiple quizzes with these guys we've never ever beaten them we're always second to the guys from Arrow Street they know a lot about their stuff you walk into the shop and you can say I've seen these films and this and I like these directors and they will recommend something to you and they're usually always right they're always spot on in terms of this and their recommendations which is why they've survived it's a similar situation with bookstores you know a lot of what we would call bookstores back in the day or maybe 5-10 years ago and now what we see is stationery shops we'd buy our stationery from them but we'd never go in there to buy a book from them anymore but we still have those books stores that curate content and they know their stuff and you go in there because you want a recommendation and so for us that's where our disruptive thinking is happening at the moment we need to start really innovating around this the problem with innovation well as someone suggested these guys when they were on the threat of going under their collection were so important someone suggested putting it in a museum and that really is the writing on the wall for these guys that they need to change their business model quickly and maybe find a better way of recommending movies to watch that they can commercialize in the same way we have to find a way of commercializing commercializing our content because pretty much that content is available in multiple sources but we believe it's the recommendation that will get us the money or the audience at least so just some things that are on our radar this is our home page over here we probably won't have a home page soon virtually nobody goes there anymore they all come directly from Facebook or Twitter they're all linked in from somewhere else they go directly to an article page they go directly to a landing page they don't see our section pages we're going to a distributed content model so we have the home page we have a fairly good looking adaptive home page as well but we just don't see a future for it at the moment the other aspect of that of course is that social media has created a news news of its own if you like you have a group of people that you trust to feed you relevant or trustworthy information and that becomes a truth for you that information is you see that as news and an example this is a Guardian article how technology disrupted the truth this was talking about the British Prime Minister and the fact that the Daily Mail was reporting based on social media that the Prime Minister committed an obscene act with a pig's head it just wasn't true there's no proof out there that it actually happened but social media made it a truth and the Guardian is saying is this valid news what's happening in this regard but that's a problem for us to deal with I think and I don't know how we're going to solve that problem we have other things to consider on our radar we've got the internet of things we don't know how that's going to affect us and then we've got Watson over here and other cognitive computing kind of approaches that might take away they might be a Watson might be a perfectly good curator of the news for someone so what can we learn I think these are my takeaways for you is that digital disruption is only going to accelerate and consider restructuring to adapt to the rate of change that's going to happen lean start-up experiments or something like that are only going to help you need to separate maybe an R&D department to look at new revenue streams and the reason you need to separate your R&D department out is because you can't disrupt yourself just like Kodak couldn't disrupt themselves with their digital camera it's just not in an established organization DNA to disrupt its own business model so the approach that's suggested is that you take maybe a small team in a skunk works type operation and you spin them off in a separate organization maybe they report into a board member but they essentially have a separate budget and they're a separate entity for all purposes because they will be the people that will be building the commercial future for you if you like or alternative commercial futures it's a bit like the the approach where you think the conformity bias I think it was is where you're saying well we all believe that this is what's going to play out and this is how it's going to happen and that might be the majority rules but your R&D department is the one looking at the alternatives and the minority approach to really seriously how we might be disrupted in the future and disrupting our own business model I put this slide up this source is from Russell Reynolds Associates the percent of the executives who respond that their business will be moderately or massively disrupted by digital in the future media is up there it's happening across the board and I don't really want to be a harbinger of doom for you guys but you need to think about this you need to think about your digital first strategy it will come to you it will affect everybody the way we have changed with technology is not going to go away it's only going to accelerate so three things to think about is will you focus on customer experience or a digitalized solution how will you sustain your current approach how will you face digital disruption in your market and that's all from me I think we've got plenty of time for questions so please yep so it's interesting there's a small detail so I see the company grows so in 2012 Android in 2012 you say there's a new CEO coming in and you want to implement digital strategy so I hope you know what the detail about what happened before 2012 because I consider that I will have some sort of digitalization but I'm not sure whether it's really the strategy you mentioned those apps happened really it was a rogue product manager who decided to spin up his own team and start creating the apps much to the chagrin of the newsroom who didn't want it at the time because they saw it as distracting so one they saw the website as taking away business from the paper business and then they saw the Android and other mobile apps taking away business from the digital the website so it all got really it was really really confused so they what happened was they still had their heads in the sand they were still trying to ignore the digital we were in the position in New Zealand where we were actually a couple of years behind the rest of the world I don't know if that's literally but things seem to happen we get warning that things are happening and I just don't think the message it got through that we needed to become a digital first organization until it was clear that media companies in the UK and so on were seriously disrupted there's companies like the independent in the UK who have gone completely online they have no more they don't print anymore they don't have enough numbers to print and so on does that answer your question? but basically heads in the sand rogue product manager built the apps anyway it wasn't until 2012 when we actually had a strategy around digital is there another question? hmm that they needed to, sorry I think it's a good question I'm not sure if I know the exact catalyst but it was definitely that we got a new CEO who's got a technology background and I just think he just took the full by the horns and like that was it I think that's essentially the as much as I know of the story yeah we do so we use we use the Adobe platform for we use the Adobe platform for content management and they've got a great experience manager which allows us to gather analytics and we've got some great insights people to tell us you know basically we're looking at different strategies around our analytics gathering that we can target new markets basically it's like the one of the situations that you mentioned there's been almost that they haven't used actually for ID as to pay infrastructure are there any other cases of for the people that are into this so the one example there's a few examples of companies doing this but there's the one I've got clear sort of clear sight of was one that Clayton which was the first online bank online trading bank they they had this idea for online trading but they realized it was seriously going to undercut their business so for example if you wanted to trade in those days you had to telephone a broker and it cost you $80 to do the transaction but they realized that online trading would be significantly cheaper and that people would be self-serving around that but it would totally disrupt their existing model so what they did was they basically looked for a volunteer group to take this idea forward they took them out of the building one day and marched them across to another building and they set up their online trading brokerage and then they basically that company got so large and profitable that they consumed the other trading bank cool thanks very much everybody


time of enormous energy, if only there was little more clarity and balance when we were young, tch, how many things, how many things would have happened and how many things would not have happened. Because I continuously keep hearing, sattguru, if I had only met you when I was twenty-five, so we thought let's engage with the youth and see how close to truth can we bring them. So this is going to be gossipy. See, right from ancient times, whenever somebody wanted to know the truth about something, they always relied on gossip. Something comes out in the newspaper, you don't go by that, you go and ask around. When they say something, that becomes the truth. So gossip has always been a conveyor of truth, not the gospel, because it's dead serious. So gossip has been reliable, though it gets exaggerated, it gets multiplied, everything, people learn how to listen to gossip, filter gossip and get the truth out of it, don't you? But now with social media, gossip has gone global, it's no more local gossip. So I thought let's raise it to the next level. When you gossip with a mystic, your gossip goes cosmic. This is not going to be an absolute, this is it, that is it. Because people have this funny idea, truth means absolute. We want to dispel this. Truth is not an absolute. Truth is in many ways. The question is, what will be your source of truth? In what way will you experience this? Will you experience this watching a sunset? Will you experience watching a full moon? Will you experience with love? Will you experience with compassion, service or will this life? Will become the basis of your truth? If you rely on the sun… sunset or moonrise, one will happen only once a day, another will happen only once a month. Only the life that you are is the basis of your truth. Now it can be with you every moment of your life. So in this context, we will unfold this youth and truth.


Hey, guys, it's Bridget. I want to give you an update on my sessions. So a couple of big new things this year. One is I am going to be doing some group work with you more publicly. I usually do this kind of behind the scenes, where I personally invite people into groups with me. And now I want to do some more lighthearted, playful kinds of groups and topics and include that opportunity for many of you for psychic group sessions. Now, psychic group sessions are not in lieu of a private psychic reading. And in psychic group sessions, you're going to have to pay attention when those are announced to know what the topic is and what the expectations are. Because many of those will have a Q&A for a few people, but it's not in lieu of a personal psychic session. And it's not to answer private psychic reading type of questions, unless, of course, that is what the specific psychic group session is for. But psychic group sessions are to be able to have psychic connection through channeling based on a talk topic and to be able to have, so I can actually interact with you a little bit more and then give an opportunity for some Q&A. So it'll be on video format. It'll be something that we're going to be playing around with and kind of seeing what format works well and what doesn't kind of a thing for 2020. So I look forward to doing that. So make sure you watch for that. The psychic group sessions will be announced on my Facebook page at Bridget Inspired and on my Instagram page at Bridget Inspired. I will also try to share them at Above Life Channel on Facebook also. And the prices will vary on that based upon group size, topic, and length of session. So make sure if you see them coming out early in January, February, March, that you jump in on them right away because I'm going to be experimenting with the formats, with the pricing, with the duration and stuff of the session. So psychic group sessions, that's something you want to really pay attention to here in the beginning of the year. So let's see how that goes. And then I also want to let you know that I've also opened up once again my psychic plus life coaching packages. So I offer packages for people who I are a consistent client. So it's a minimum of three months, consistent, consecutive monthly sessions, an hour in length minimum. Some people do choose to do more than that. Some people will do two hours during the month, two sessions a month. Some people will do an hour and then follow up half hour session during the month. And whatever package of the sessions works for you, that's what we'll work through. But the minimum, the bare bones is three months, one session a month. And the rates for those session rates actually broken down are less than the rate if you just do sessions every now and then. So I wanted to make it a little more affordable and reasonable for people that really want to have support, encouragement, not just psychic reading information. This is not psychic reading. It is a psychic session where we will be connected to your healing team and your spiritual helpers and connected to messages from your intuition. But it's more to affirm what you already know. And so it's really for people, the psychic plus life coaching packages are really for people who like that consistent support. Not somebody to tell you what to do or give you the advice that you need to do next, but to allow you to have a sounding board with energetic support to work through your stuff, to be in a safe place where you can really talk about things.  Or maybe things are awesome and you just need a new coach that's unique and intuitive, then I might be a fit for you. So if you're interested in that service in particular, you can send an email and I will chat with you about what the options are. I need to make sure that we're clear on our expectations when we enter into our psychic plus life coaching session packages, okay? All right, you guys. So those are two big new things for this year. I'm looking forward to connecting with you, to finding more ways to connect with you. Again, I think those psychic group experiences are gonna be awesome because I think it'll give more of you an opportunity to step into connection and kind of really get a feel for this, this type of work, this energy and what's really possible for you at a rate, a very affordable rate. So it's much cheaper to work in a group for individual participants than it is to have private session. I know private session can be an investment and I don't want that to be a barrier for people to be able to at least step into some psychic connection, at least step in to some empowerment that comes with being intuitive and for yourself. My goal, whether it's in a group session or a private session or coaching session, is always to empower you to inspire your spirit with hope and to encourage you to live your life. Because this is your life, I cannot live it for you. I'm not gonna do predictions for you.   It's your life, so live it, just live it. This is Bridget, thanks so much for watching and I look forward to connecting with you very soon.


So this here as soldiers are doing shoot move and communicate They're doing battle buddy team drills bounding Taking cover behind a palette. I here you can see soldiers low crawling It's one of the movement techniques when navigating low obstacles. So yeah, they're all health care providers technicians I think the highest-ranking individual we had the 06 Colonel Dentat commander was out doing some of these drills all the way down to the newest privates working in pharmacy and radiology Right here. They're just bounding one soldier sets up takes point Lays down fire on the enemy That suppresses the enemy it gives the other soldier an opportunity to stand up and bound They alternate and that's how they cover ground to get closer to their objective If we get out there and we can provide good training to the soldiers and get after these army warrior tasks And the soldiers can have fun while they're doing it. It's even better It takes a little more we instill that in them. They're getting good training and not they're not miserable This year, this is Staff Sergeant Conley's the answer I see of our SRP on Fort Riley He's also an expert field medical badge holder one of the few on the installation So right now he's he's going over different movement techniques The soldiers are battle buddy paired up and they're demonstrating and practicing these these movement techniques to move across a 25 meter field the one soldier Imitates a casualty that's unconscious Severely wounded that can't move on their own and they're just practicing the several different movement techniques to get a soldier Out of out of fire and back into cover Take these the knot will catch on the other side Yeah, what they're doing there. They're strapping the soldier up and moving them to an HLZ helicopter landing zone To to evacuate them out of the area What we're seeing here for patient loading. This is hot and the difference is the helicopters on it's running It's ready to take off cold in perspective is just the Helicopter isn't running So that's all this is is where we've moved the soldier from point of contact or point of injury to behind cover We've transported them on skater litter to an HLZ for evacuation And then we finish that up with the the hot and cold training on how to actually load a patient into an aircraft So this is Sergeant Rasmussen, he's an NCO in our radiology department here at the hospital He is also a professional weapons instructor. So that's a great asset here within the hospital Right here what he's doing is the assembly and disassembly of an M17 pistol for one of the soldiers There's several several parts to being trained on the chute aspect of army war tasks and battle drills this portion weapon familiarization is the Disassembly and reassembly of the weapon soldiers Were also required to go to a range and qualify either on the M17 pistol the M4 rifle So what we're doing here in a classroom environment is doing the familiarization with the weapons and to include that that disassembly and Reassembly of the firearm while learning what all of the components are and how they work in conjunction to make the weapon Right here. This is Staff Sergeant Blake He's he's going over the proper There's new standards for the M4 qualification where we utilize this wall for stability when we're firing down range And he's he's just going over a steady practice name We're using a laser mounted boar scope so that although we can't fire in the classroom The soldiers are able to monitor the placement of their bullet during the firing process by using the The boar scope with the laser on the target on the other side of the classroom So this is c burn training chemical biological radiological and nuclear What they're doing is they have what we call a pro mask gas mask And they're they're demonstrating the proper technique on how to don that mask Within the set time limit now bystander at every soldier as you can see here from the moment Gas is announced in the area. They have nine seconds to open up their the pro mask case on their left hip Don the mask clear it And then close the mask and then signal To their their battle buddies on the left and right that there's gas in the area Some of these skills Although we learn them we do them over time if you don't do them for a while you You lose that edge and for something as critical as donning a gas mask during a chemical attack Nine seconds is a standard Nine seconds is a standard because if you don't do it with that time and you don't Know how to fit the mask properly and clear it properly Those seconds can cost you it's valuable time that can make the difference to a life and death


Hi everyone, Joe for jazby's case breaks calm coming at you with a panini prism basketball Salo pack break number one five three with the final ten immaculate basketball spots being given away Big thanks to this group for making it happen And there are all the teams right here So the first dice roll be for the break the pack break second dice roll will be for the giveaway snake eyes for names and teams one and To Eric down to Eric one and two Atlanta down to Miami. All right, there's the first half of the list right here Brian Timberwolves Sean Maddock Hornets could be could be some surprises here. Have we seen it before? Yes It's possible People sometimes ask hey in these filler packs Where you're giving away spots in a bigger break? Have you actually pulled anything nice out of here? We have and we'll be doing that one box break in a separate video We've got boy on Bogdanovich silver John Morant green Those two-sharp horns are not the ones we're looking for about red-white and blues Erin Baines Marvin Bagley and Westbrook All right, so nothing too crazy here, but Slip back to the screen right here. Let's see who's gonna win spots in that one box break of immaculate basketball Which is a promo break as well a wax party promo break details of the wax party jazby's case breaks calm one out of four five times top ten after five good luck one two three Four and fifth and final time after five So from 11 on down, let's get that over from 11 on down sad times, but thanks for giving it a shot Happier times to the top 10. You're in the break Matthew Brian David Brandon Mark Ryan Steven Sean CJ and Kenneth So we'll see you for that one box immaculate basketball break jazby's case breaks calm. Bye. Bye


Live from San Francisco, it's theCUBE, covering Flink Forward, brought to you by Data Artisans. Hi, this is George Gilbert. We are at Flink Forward, the conference put on by Data Artisans for the Apache Flink community. This is the second Flink Forward in San Francisco, and we are honored to have with us Stefan Nguyen, co-founder of Data Artisans, creator, co-creator of Apache Flink, and CTO of Data Artisans, Stefan, welcome. Thank you, George. Okay, so with others, we were talking about the use cases they were trying to solve, but you put together the sort of, all the pieces in your head first, and are building out, you know, something that's ultimately gets broader and broader in its applicability. Help us now, maybe from the bottom up, help us think through the problems you were trying to solve, and let's start with the ones that you solved first, and then how the platform grows so that you can solve more and more a broader scale of problems. Yes, yeah, I'm happy to do that. So I think we have to take a bunch of stepbacks and kind of look at what is the, let's say the breadth of use cases that we're looking at, how did that influence some of the inherent decisions and how we've built Flink, how does that relate to what were presented earlier today, the stream processing platform and so on. So, starting to work on Flink and stream processing, stream processing is an extremely general and broad paradigm, right? We've actually started to say what Flink is underneath the hood, it's an engine to do stateful computations over data streams. Let's say it's a system that can process data streams as a batch processor or processes, you know, bounded data, it can process data streams as a real-time stream processor or produces real-time streams of events. It can handle data streams as in sophisticated event by event, stateful, timely logic as many applications that are implemented as data-driven microservices also implement their logic. And the basic idea behind how Flink takes its approach to that is just start with the basic ingredients that you need that and try not to impose any form of various constraints and so on around the use of that. So, when I give the presentations, I very often say the basic building blocks for Flink is just like flowing streams of data, streams being received from systems like Kafka, file systems, so on and so on. It had systems like Kafka, file systems, databases, so you root them, you may want to repartition them, organize them by key, broadcast them depending on what you need to do. You implement computation on these streams, a computation that can keep state, almost as if it was like a standalone Java application. You don't think necessarily in terms of writing, writing state or database, think more in terms of maintaining your own variables or so. Sophisticated access to tracking time and progress, so progress of data, completeness of data, that's in some sense what is behind the event time streaming notion, you're tracking completeness of data as for a certain point of time. And then to round this all up, give this a really nice operational tool by introducing this concept of distributed consistent snapshots. And just sticking with these basic primitives, you have streams that just flow, no barrier, no transactional barriers necessarily there between operations, no micro batches, just streams that flow, state variables that get updated and then fault tolerance happening as an asynchronous background process. Now that is what is in some sense the, I would say kind of the core, the core idea, yeah, and what helps link generalize from batch processing to real time stream processing to event driven applications. And what we saw today is in the presentation that I gave earlier in how we use that to build a platform for stream processing and event driven applications. That's taking some of these things and in that case, I'm most prominently the fourth aspect, the ability to draw application snapshots at any point in time and use this as an extremely powerful operational tool. You can think of it as being a tool to archive applications, migrate applications, fork applications, modify them independently. And these snapshots are essentially your individual snapshots at the node level and then you're sort of organizing them into one big logical snapshot. Yeah, each node does its own snapshot but they're consistently organized into a globally consistent snapshot, yes. That has a few very, very interesting and important implications, for example. So just to give you one example where this makes really things much easier. If you have an application that you want to upgrade and you don't have a mechanism like that, right? What is the default way that many folks do these upgrades today? Try to do a rolling upgrade of all your individual nodes. You replace one, then the next, then the next. But that has this interesting situation where at some point in time there's actually two versions of the application running at the same time. Yeah, and operating on the same sort of data stream. Potentially, yeah, or on some partitions of the data stream you have one version and some partitions you have another version. So you kind of, you may be at the point we have to maintain two wire formats, like all pieces of your logic has to be written in understanding both versions or you try to use a data format that makes this a little easier. But it's just inherently a thing that you don't even have to worry about it if you have this consistent distributed snapshot. It's just a way to switch from one application to the other as if nothing was shared or in flight at any point in time. It just gets many of these problems just out of the way instantaneously. And that snapshot applies to code and data or can? So in Flinks, in Flinks architecture itself, the snapshot applies first of all only to data and that is very important. Because what it actually allows you is to decouple the snapshot from the code if you want to. That allows you to do things like we showed earlier this morning if you actually have an earlier snapshot where the data is correct, then you change the code but you introduce the bug. You can just say, okay, let me actually change the code and apply different code to a different snapshot. So you can actually roll back or roll forward different versions of code and different versions of state independently. Or you can go and say, when I'm forking this application, I'm actually modifying it. That is a level of flexibility that's incredible to, yeah, once you've actually start to make use of it and practice is incredibly useful. And it's been actually almost, it's been one of the maybe least obvious things once you start to look into stream processing but once you actually start to production or stream processing, this operational flexibility that you get there is, I would say, very high up for a lot of users when they said, okay, this is why we took Flink to streaming production and not others, the ability to do for example that. But this sounds then like a, like with some stream processors, the idea of unbundling the database, you have derived data at different sync points. And that derived data is for analysis, views, whatever. But it sounds like what you're doing is taking a derived data of sort of what the application's working on in progress and creating essentially a logically consistent view that's not really derived data for some other application use, but for operational use. Yeah, so is that a fair way to explain? Yeah, let me try to rephrase it a bit. When you start to take this streaming style approach to things, which it's been called turning the database instead of unbundling the database, your input sequence of event is arguably the ground truth and what the stream processor computes is a view of the state of the world. So while this sounds at first super easy and views, you can always recompute a view, right? Now in practice, this view of the world is not just something that's just like a lightweight thing that's only derived from the sequence of events. It is actually the state of the world that you want to use. It might not be fully reproducible just because either the sequence of events has been truncated or because the sequence event of events is just like too plain long to feasibly recomputed in a reasonable time. So having a way to work with this in a way that just complements this whole idea of event-driven, log-driven architecture very cleanly is kind of what this natural tool also gives you. Okay, so then help us think, so that sounds like that was part of core Flink. That is part of core Flink of Flink's inherent design. Okay, so then take us to the next level of abstraction, the scaffolding that you're building around it with the DA platform and how that should make that sort of thing that makes stream processing more accessible, how it empowers a whole another generation. Yeah, so there's different angles to what the DA platform does. So one angle is just very pragmatically easing roll out of applications by having a, like one way to integrate the platform with your metrics, alerting, logging, CICD pipeline and then every application that you deploy where they're just like inherits all of that, like every application developer doesn't have to worry about anything, they just say like, this is my piece of code, I'm putting it there and it's just gonna be hooked in with everything else. That's not rocket science, but it's extremely valuable because there's like a lot of TDS bits here and there that otherwise eat up a significant amount of the development time. Technologically maybe more more challenging part that this solves is the part where we're really integrating the application snapshot, the compute resources, the configuration management and everything into this model where you don't think about I'm running a flink job here, that flink job has created a snapshot that is running around here, that's also a snapshot here which probably may come from that flink application. Also that flink application was running, that's actually just a new version of that flink application which is the, let's say testing or acceptance run for the version that we're about to deploy here and so like tying all of these things together. So it's not just the artifacts from one program, it's how they all interrelate. It gives you the idea of exactly of how they all interrelate because an application over its lifetime will correspond to different configurations, different code versions, different deployments on production A, B, testing and so on and like how all of these things kind of work together, how they interplay, right? Flink, like I said before, flink deliberately couples checkpoints and so on in a rather loose way to allow you to evolve the code differently than and still be able to match a previous snapshot into a newer code version and so on. We make heavy use of that but we kind of give you a good way of first of all tracking all of these things together, how do they relate? When was which version running? What code version was that? Having a snapshot so you can always go back and reinstate earlier versions, having the ability to always move a deployment from here to there like forward get, drop it and so on. That is one part of it and the other part of it is the tight integration with Kubernetes which is a initially container sweet spot was stateless compute and the way stream processing as an architecture works is the nodes are inherently not stateless, they have a view of the state of the world. This is recoverable always. You can also change the number of containers and with Flink and other frameworks, you have the ability to kind of adjust this and so on. Including the state, including repartitioning the. Including repartitioning the state but it's a thing that you have to be often quite careful how to do that so that this all just, it all integrates exactly consistency like the right containers are running at the right point in time with the exact right version and there's not like, there's not a split brain situation where this happens to be still running some other partitions at the same time or you're running this, you're running that container goes down and is this a situation where you're supposed to recover or rescale, like figuring all of these things out together, this is kind of what the idea of integrating these things in a very tight way gives you. So think of it as the following way, right? You start with, and initially just start with Docker. Docker is a way to say I'm packaging up everything that a process needs, all of its environment to make sure that I can deploy it here and here and here and here and just always works. It's not like, oh, I'm missing the correct version of the library here or I'm interfering with that other process on a port or so. On top of Docker, people added things like Kubernetes to orchestrate many containers together forming an application and then on top of Kubernetes, there are things like Helm or for certain frameworks, there's like Kubernetes operators and so on, which try to raise the abstraction to say, okay, we're taking care of these aspects that this needs in addition to container orchestration. We're doing exactly that thing, like we're raising the abstraction one level up to say, okay, we're not just thinking about the containers, the compute here and maybe they're like local persistent storage, but we're looking at the entire stateful application with its compute, with its state, with its archival storage, with all of it together. Okay, let me sort of peel off with a question about sort of more conventionally trained developers and admins and they're used to databases for batch and request response type jobs or applications. Do you see them becoming potential developers of continuous stream processing apps or do you see it mainly for a new generation of developers? No, I would actually say that a lot of the like classic call it request response or call it like create, update, delete, create, read, update, delete or so kind of application working against the database. There's this huge potential for like stream processing or that kind of event-driven architectures to help change this field. There's actually a fascinating talk here by the folks from DriveTribe who implemented an entire social network in a stream processing architecture, so not against a database, but against a log and a stream processor instead. It comes with some really cool properties, like a very unique way of having operational flexibility to at the same time test and evolve and run and do like very rapid iterations over your- Because of the decoupling? Because of exactly, because of the decoupling, because you don't have to always worry about, okay, I'm experimenting here with something. Let me first of all create a copy of the database and then once I actually think that this is working out well, then okay, how do I either migrate those changes back or make sure that the copy of the database that I did, that bring this up to speed with the production database again before I switch over to the new version and so like so many of these things just like the pieces just fall together easily in the streaming world. Would it, I think I asked this of Kostas, but if a business analyst wants to query the current state of what's in the cluster, do they go through some sort of head node that knows where the partitions lay and then some sort of query optimizer figures out how to execute that with a cost model or something? In other words, if you wanted to do some sort of batch or interactive type. So there's different answers to that, I think. There's first of all, there's the ability to look into the state of link as in, you know, you have the individual nodes that maintain state during the computation and you can look into this, but it's more like a look up thing. You're not running a query as in a SQL query against that particular state. If you would like to do something like that, what Flink gives you as the ability is always to, there's a wide variety of connectors. So you can, for example, say I'm describing my streaming computation here. You can describe it in an SQL. You can say the result of this thing, I'm writing it to a neatly queryable, you know, data store and in memory database or so. And then you would actually run the dashboard style exploratory queries against that particular database. So Flink's sweet spot at this point is not to run many small fast short-lived SQL queries against something that is in Flink running at the moment. That's not what it is yet to be able to optimize for. A more batch oriented one would be the derived data that's in the form of like a materialized view. Exactly, so these two sides play together very well, right? You have the more exploratory batch style queries that go against the view and then you have the stream processor and streaming SQL used to continuously compute that view that you then explore. Is there, do you see scenarios where you have traditional OLTP databases that are capturing business transactions but now you want to inform those transactions or potentially automate them with machine learning and so that you capture a transaction and then there's sort of ambient data, whether it's about the user interaction or it's about the machine data flowing in and maybe you don't capture the transaction right away but you're capturing data for the transaction and the ambient data. The ambient data, you calculate some sort of analytic result could be a model score and that informs the transaction that's running at the front end of this pipeline. Is that a model that you see in the future? So that sounds like a former use case that has actually been run, not quite... It's not uncommon, yeah. It's actually, in some sense, a model like that is behind many of the fraud detection applications, right? You have the transaction that you capture. You have a lot of contextual data that you receive from which you either build a model in the stream processor or you build a model offline and push it into the stream processor as, let's say, a stream of model updates. And then you're using that stream of model updates. You derive your, let's say, your classifiers or your rule engines or your predictor state from that set of updates and from the history of the previous transactions and then you use that to attach a classification to the transaction. And then once this is actually returned, this stream is fed back to the part of the computation that actually processes the transaction itself to trigger the decision, whether to, for example, hold it back or to let it go forward. So this is an application where people who have built traditional architectures would add this capability on for low latency analytics. Yeah, that's one way to look at it, yeah. As opposed to a rip and replace, like we're going to take out our request response and our batch and put in stream processing. Yeah, so that is definitely a way that stream processing is used, that you basically capture a change log or so of whatever is happening in either a database or you just immediately capture the events, the interaction from users and devices and then you let the stream processor run side by side the old infrastructure and just exactly compute additional information that even a mainframe database might in the end use to decide what to do with a certain transaction. So it's a way to complement legacy infrastructure with new infrastructure without having to break or for break away the legacy infrastructure. So let me ask in a different direction, more on the complexity that forms a tax for developers and administrators, many of the open source community products slash projects solve narrow sort of functions within a broader landscape and there's a tax on developers and admins and trying to make those work together because of the different security models, data models, all that. So there's a zoo of systems and technologies out there and also of different paradigms to do things. Once things follow, once systems kind of have a similar paradigm or idea in mind, they usually work together well, but there's different philosophical tastes. Give me some examples of the different paradigms that don't fit together well. For example, when, maybe one good example was initially when streaming was a rather new thing. At this point in time, stream processors were very much thought of as a, just a bit of an addition to the, let's say the batch stack or whatever other stack you currently have. Just look at it as a kind of an auxiliary piece to do some approximate computation and a big reason why that was the case is because the way that these stream processors thought of state was with a different consistency model. The way they thought of time was actually different than the batch processors of the database which use timestamp fields and the early stream processors. They couldn't handle event time. Exactly, just use processing time and that's why these things, you could maybe complement the stack with that, but it didn't really go well together. You couldn't just say like, okay, I can actually take this batch job, kind of interpret it also as a streaming job. Once the stream processors got a better interpretation. Exactly, so once the stream processors adopted a stronger consistency model, a time model that is more compatible with reprocessing and so on, all of these things all of a sudden fit together, fit together much better. Okay, so do you see that vendors who are oriented around a single paradigm or unified paradigm, do you see them continuing to broaden their footprints so that they can essentially take some of the complexity off the developer and the admin by providing something that, you know, one throat to choke with the pieces that were designed to work together out of the box, unlike some of the zoos, you know, with perhaps the former Hadoop community. In other words, everyone seems to be trying not everyone, a lot of vendors seem to be trying to do a broader footprint so that it's something that's, you know, like a, that it's just simpler to develop to and to operate. There are a few good efforts happening in that space right now. So one that I really like is the idea of like standardizing on some APIs. APIs are hard to standardize on but you can at least standardize on semantics. Which is something that for example, Flink and Beam have been very keen on trying to, you know, have an open discussion and yeah, a roadmap that is very compatible in thinking about streaming semantics. This has been taken to the next level, I would say, with the whole streaming SQL, with the whole streaming SQL design. Like Beam is adding Stream SQL and Flink is adding Stream SQL both in collaboration with the Apache Kelzad project. So very similar, like again, very similar standardized semantics and so on, Ansi SQL compliant. So you basically get a, you start to get common interfaces. Which is a very important first step, I would say. Standardizing on things like. So SQL semantics across products that would be within a stream processing architecture. Yes. That's an example. I think this will become really powerful once, once other vendors start to adopt the same interpretation of streaming SQL and think of it as, yes, it's a way to take a changing data table here and project a view of this changing data table, a changing view, a changing materialized view into a different, into a different, into another system, right? And then use this as a starting point maybe compute another derived view. So you can actually start and think and think more high level about things. Think really relational queries, dynamic tables across different pieces of infrastructure. Once you can do something like that, interplay in architectures become easier to handle. Because even if, you know, even if the, even if on like on the runtime level, things behave a bit different, at least you start to establish a standardized model and thinking about how to compose your architecture. And even if you decide to change on the way you're frequently saved the problem of having to rip everything out and redesign everything because the next system that you bring in just has a completely different paradigm that it follows. Okay. This is helpful. To be continued offline or back online on theCUBE. This is George Gilbert. We were having a very interesting and extended conversation with Stefan Nguyen, CTO and co-founder of Data Artisans and one of the creators of Apache Flink. And we are at Flink Forward in San Francisco. We will be back after this short break.


The active national chairman of the People's Democratic Party, Umarad Damagum, has called on party members to work towards the unity of the country for the survival of democracy. Damagum said the PvP still has hope in the nation's judiciary with regard to the ongoing court case challenging the victory of President Bola Ahmed Tinibu in the last presidential election. Damagum made disclosure during his congratulatory visit to Governor Kefa's Agbu of Tarabah State at Governor's House in Jalingu. I want to make also appeal to our general supporters that they should have patience with us. This is a trying moment for us. We lost the presidential candidate but we are still hopeful. There is no time the court and the judges have been put on trial like now because all of you know what happened during the last election. Tarabah State, I want to assure you that we have not made the wrong choice. We are here for you to do what is right, to unite ourselves together so that we can make progress. In 1999, Tarabah is pitted and by the grace of God we continue to be pitted. We have not any other party apart from us.


Environmentalism fundamentally has to be motivated by love, love of life, love of this earth, love of not just the Amazon but of like the forest behind your house, of the place where you grew up, of the animals that you interact with, not because they have some instrumental utility and that we should navigate according to some complicated self-interest calculation. That's not why we're here. As human beings, we're not here to maximize our rational self-interest. I think it is actually motivated by love, but the rhetoric is about fear. The rhetoric is about force. It's about, for example, let's pressure and force people to change. Let's force the corporations to change. I'm not saying that we should just always ask nicely for change, but we have to understand that pretty much every human being on some level cares about this world and cares about the beings on it, not because of some threat to themselves, to their profits, and so forth. Environmentalism has to return to that.