Celebrities protect the interests of the Empire. Notes from the edge of the narrative matrix.  You don't oppose Russia because you're an anti-imperialist. You oppose Russia because you're an imperialist. The only people who say Putin can end this war anytime by withdrawing are those who deny the U.S. Empire's aggressions which led to this conflict, which is just a nonsense garbage position based on lies. They don't actually want peace. They just want victory for the Empire. The real unbiased position, which supports peace, is wanting both Russia and the Western Empire to begin engaging in diplomacy, de-escalation and détente to end this war. But Empire simps will call you treasonously biased if you support anything other than total Russian defeat. This dopey propaganda-addled notion that the West did nothing wrong and Putin attacked Ukraine solely because he is evil and hates freedom actually prevents peace from happening. If one side only acknowledges the reality of the aggressors of the other side, peace is impossible. If you don't understand how a war was started and perpetuated, then you can't understand how peace can be started and perpetuated. The Empire deliberately works to prevent the public from obtaining this understanding because the Empire wants war.  You've got a whole internet of information at your fingertips. Use it. It's impossible to overstate how much our society is shaped by the fact that those who are given the most influence and the largest platforms will experience our status quo systems as working very nicely and having a vested interest in preserving those systems which benefit them. The media-owning, culture-manufacturing class of the super-wealthy elevates people to wealth and celebrity who look like they will be good protectors of their class interests. Those people will necessarily speak fondly of the status quo political systems which let them be rich. These are the people who put on all the shows, movies and music almost everyone consumes, thereby engineering mainstream culture to the benefit of the super-wealthy. It shapes the way people think, speak, act and vote, what they feel entitled to, what they think is possible. A rich celebrity who makes millions of dollars a year in a fun, easy and egoically gratifying job is not going to be spotlighting all the lives who are being destroyed by the status quo systems which elevated them. They're not going to favor the revolutionary changes that are needed. They're not going to be calling for a massive, sweeping overhaul of the systems which are crushing ordinary people to death and creating widespread misery. At most, they're going to be telling you to vote Democrat or Republican and quibbling about minor disagreements on tax rates. But these are the people with the loudest voices in our society. Not just the loudest, but many orders of magnitude more amplified and influential than the voices of the ordinary people who are suffering under existing systems. These loudly amplified, rich celebrities shape and direct mainstream culture. This dynamic plays such a massive role in hiding from mainstream attention the ways our status quo systems are exploiting, oppressing and abusing people while killing our biosphere and pushing us toward nuclear annihilation, that it's hard to wrap your mind around how far it goes. The way everyone's thinking about the world is so pervasively informed by perspectives that are favorable to the status quo prevents them from even noticing how bad things are for everyone else. It's widely assumed that if you're struggling in this mess, it's because of your own failures. If any media you turn on depicts people who are doing basically fine and are content with the way things are, while you're barely able to keep your head above water, the take-home message is that the problem is with you, not with our systems. That you are what needs to change. The failings of the status quo are hidden in mainstream culture and people aren't permitted to consider the possibility that there might be a better way for things to be. People don't know, and they don't know that they don't know. They are kept in the dark about what's possible. People are like, oh yeah, right Caitlin, it's always Americans fault. You're always blaming the US for every conflict just because it runs a globe-spanning empire which dominates the planet with violence and coercion and works continuously to keep all the other countries subjugated to it. They're like, right, right, blame everything on the violent unipolar planetary hegemon. It's like saying, okay sure, we're trapped in a room with a tiger and sure, we keep getting eaten and yes, your leg is missing and you've got a large bite out of your torso, but you can't blame all that on the tiger. It's not fair. Some of it might be Steve's fault.  People whose opinions are grounded in facts and logic don't need to resort to accusing those who disagree with them of being secret agents working for foreign governments.  It's so arrogant. It's one thing to draw a line and say the world must never let anyone cross this point even if it means risking nuclear Armageddon. Quite another to make that line something as trivial as the question of who governs Crimea. It's not legitimate to risk all life over that. This is especially true because the US Empire provoked this war and because even the Crimeans themselves prefer to be Russian. But even if none of that was the case, it still wouldn't be legitimate for the US Empire to risk the lives of people in Africa or South America by backing an offensive on Crimea.   All these armchair warriors saying, we need to be brave and take a stand, are willing to gamble billions of lives who do not consent to being gambled over a war they're not even fighting in, all while refusing to deeply contemplate what nuclear war would entail. They're cowards. I just want the rapidly rising threat of nuclear war to be treated, reported on, and discussed like the supremely important issue that it is. It's the single most important matter in the world and it just gets casually mentioned here and there like it's just another issue.  I've been writing about the growing risk of nuclear war for years and people have been calling me a delusional lunatic and a Putin puppet the entire time. Meanwhile, we've demonstrably and indisputably been seeing massive steps toward that outcome and it's still being dismissed. Even if you believe that all this nuclear brinkmanship is justified and good, you still need to fully acknowledge the reality of the risk and the unfathomable horrors that would unleash upon our world and you need to do it with all the respect and solemnity the subject deserves.


in San Francisco, it's theCUBE, covering Apache SparkMaker community event brought to you by IBM. Now, here are your hosts, John Walls and George Gilbert. And welcome back inside the Galvanized campus here in San Francisco as theCUBE continues our coverage of the Apache SparkMaker community event sponsored by IBM. The general session is tonight, you'll be able to see that live here by the way. We'll be streaming that keynote session and also bringing you interviews from throughout the week at the Spark Summit, which is tomorrow and Wednesday as well at the Hilton, just across town. But today we're in Galvanized, a really neat space, and George Gilbert is sharing it with me today, George. It's been a pleasure to have you riding shotgun here. And we are joined by John Akron, who's the CTO of the Silicon Valley Data Science Group. And John, we appreciate the time here. Thanks for being with us. Great to be here. Tell us about, first off, what you all do. I realize, as a consultant, you have a pretty wide portfolio, but you have some areas of core expertise to know. You're happy to share it with your client base. Absolutely, absolutely. So we are maybe starting a trend in naming Silicon companies after what they do. So we bring a Silicon Valley approach to doing data science for our customers. And what that means is we're about a 70-person consulting company these days, growing fast as a good Valley company does. And we work with companies about four basic ways. We help them answer their strategic question of what should they do with data. So most companies have a business agenda. They want better, deeper relationships with their customers. They want a more optimized and resilient supply chain. They want more optimized and resilient manufacturing, et cetera. And so for us, data strategy is okay. So what investments in technology, capability, people and process do you need to make to unlock that business opportunity with these kinds of data technologies and capabilities? So once they've made those kinds of decisions, lots of folks have that already in hand, we work in architecture advisory to answer the question of, okay, well if that's what you want to do and that means we need to build a recommender system, does that mean I need a Hadoop system with this or that or the other thing? So what architecture and what specific technologies will build that thing that unlocks that business advantage? And we call that architecture advisory. And then mostly what we do with customers is help them build those things out. So we have teams of engineers, data scientists, architects, designers and project managers that come from a range of Silicon Valley companies, consulting companies and places like that. And we work very closely with clients to then build those capabilities with them. So let's go back to the first piece, data strategy. How has that evolved over the past, even 12, 18 months with Spark, catching Spark if you will, with really kind of lining up the landscape in that regard. How has it changed for what you're telling people where they should be going and how they're gonna get there? Sure, so there's a couple of axes on which the questions become really interesting. One is, you know, there's these new technologies, things like Spark and the machine learning libraries that we can put on top of Spark and the ways that we can feed data to Spark in a streaming manner through something like Kafka to get a streaming capability in place. And all of those kinds of innovations open up newly addressable areas for data technology to serve the business. So often the focus of a data strategy for us is, okay, we're working with a customer, what does that mean? A good example of this was some work we did with Edmunds.com where the core question was, has NLP technology developed fast enough that we can take these unstructured views of what a car is that come in the form of a PDF that BMW sends you to describe what a four series is? And can we use NLP technology to recognize that BMW's X Drive is the same as Mercedes Formatic is the same as Audi's Quattro is the same as Ford's four-wheel drive, et cetera? So does NLP open up a new way of doing this that then brings some fundamental new value to the business and those questions are what we're answering in a typical data strategy? The other dimension is, to what purpose are we, or what is the scope of a data strategy and is it truly strategic? More and more, we're seeing businesses really interested in opening up strategic new top-line capabilities with data, yet a lot of what folks call data strategy is really a series of tactics around controlling access, cleaning, securing, you know, when you go to- It's more like protocols and procedures than not exactly. When you go to a typical data management conference and talk about data strategy, it really focuses in on those tactics and there's a new view emerging and we're both trying to catalyze and participate in that view that the focus should really be first on what are you trying to do and then those tactics become very, very important but the strategy is, you know, what investments do I make in capability now? And we have an enlightened self-interest, we're technologists and we will geek out on Spark and Hadoop and Kafka and the likes with the best of them, but we work for a living and we get hired by other companies to help them do something and it turns out unless you're doing something really valuable, nobody really cares about what you did with Hadoop, right? So the enlightened self-interest of these data strategies is we wanna position companies to do valuable things with these technologies and open up real business value as opposed to academic prototypes. But it's interesting when you talk about, you know, the conferences, it's almost like hijacked by guys who are, you know, trudging along, solving day-to-day problems and you wanna elevate the discussion, that's a different level in the organization. How do you reach the people who wanna engage in that discussion? So it's interesting, there's both a top-down way this works, you know, the business press is increasingly talking about the real value of these things, right? And most CEOs are at least aware of some of the stories of data around various industries. It's hard to miss Amazon, for instance, and what they've been able to do or Google for that matter, or Yahoo or some of those ilk. So we are speaking at least to a C-suite audience typically that is somewhat enlightened if not fully understand or made it from, hey, that looks interesting, to this is how that might work in my world or with my company. So there is that increasing C-level, business-level awareness of what data can do that's outside of the IT department, so to speak, creating some top-down pressure and momentum for these kinds of different views of data and how we're gonna apply them to an organization. And then there's sort of enlightened folks within the organization who become change agents. So sometimes it's a bottom-up somebody in the IT department who's thought, hey, there's a better way at doing this. My VP of engineering, when he was at Yahoo and started hearing about what one group was doing with the dupe was that he was working in some paid-search stuff and he's like, hey, I can use that to do some of the stuff I'm currently doing in a different architecture to do that better, right? So you get these people also from a bottom-up perspective who are seeing value opportunities and articulating it upwards. So in the best circumstance, you get a combination of those two dynamics and a lot of will to move and innovate. You're talking about your three problems in sort of architecture, data strategy architecture and build-out. How do those then kind of call us around the analytics platform then? So that's obviously there's relationship there. Absolutely, absolutely. And it's been tempting and business has for many years been able to sort of relegate the kind of the database choices and the underlying data infrastructure to operations and IT and it hasn't had a huge impact on business historically. And I think one of the recognitions of, sometimes I think of the, I guess the 10s, we're in the 10s, it's not the odds anymore, it's the teens. Here in the teens, it's revenge of the nerd's time. In that, actually that platform can make or break a lot of business value. If you're building a SaaS product and you platform it on something that has a poor cost to serve characteristic, if you have a database and we've done projects with companies who start out and they implemented something on Oracle and then they were massively successful. And it turns out that if they'd continue to grow that that they'd give all their money to Oracle and actually end up with an economic product. Whereas if you put that on a modern scale out platform you're able to preserve the cost to serve economics of it. So the platform isn't just a technology choice, it actually can massively impact the profitability of a SaaS product or a service offering. And the other thing is that within that platform you can make it easier or hard to innovate on data. And so when you think about, when you sort of strip away the stack diagrams and things like that and just think about what you're trying to do with data. You're trying to, you typically have some business problem in mind, you're trying to discover some data that is relevant to that business problem and then you want to acquire and ingest it into your architecture and you probably store it somewhere to integrate it with the rest of your world view to better answer that question and then ultimately take that analytical capability and serve it back out to the business in some way to impact a decision. Sort of it just described at a very high level what you can think of as a value chain of data and a well architected platform takes friction out of all of those stages and a poorly architected platform is fraught with friction at all of those stages. And the same thing can be said on the process side. So do your processes make it easy to traverse that or do they make it hard as well? And so the platform is really a very important component to how companies are able to innovate. And we've worked with lots of large companies where they've got a very talented data science team, for instance, that they are starting to put in place. But their ability to access data and do anything with it is sometimes non-existent, sometimes incredibly, it takes them literally three months of going door-to-door asking people to get more of it, et cetera. So it really can have a phenomenal impact on what folks are able to do. Let me take the one part of that answer and unpack it when you're talking about like the value chain of data. We know that, I love this quote that came from a VP of marketing at Lotus, referring to legacy applications, meaning those are the ones that work. So if you've got this new value chain of data and just analyze, operationalize, you don't want to throw the legacy stuff out, you want to augment it. Is there a set of, are there certain ways of thinking about how you do that without breaking things? Yeah, so you're changing the engine's plan while the plane's engine, while the plane is still in the air. Yeah, all four of them. Yeah, and there's both technical approaches that make that easier and then sort of a more strategic approach. So whether it's engineering sort of a green field architecture for someone, I should say architecting a green field approach for someone or working with somebody who's got a fairly developed internal infrastructure already. Abstracting at the right level in the right places to make it easier to change your mind later to isolate concerns of components and that kind of thing is really, really important to making an architecture extensible and really evolve with technology and capture the benefit of these new approaches. Within that, we typically use services approaches to implement that abstraction, which is to say that we have some legacy application. It's used to consuming some set of customer information. We build a service first that surfaces that customer information and then we point the legacy application at that. Now it's talking to a service and we can go change the thing that is implementing that without disturbing that application. Meaning change the service. Yeah, change the data infrastructure that's providing it so that the applications that are consuming that are none the wiser and that's not just for once, that's for all time. Now you've got a nice application that is intermediated by the service to the underlying infrastructure and as you need to innovate and evolve that, you can without disrupting these consuming applications. So microservices, architectures are the trend you're seeing of people reaching to this approach to accomplish that kind of thing and famously Amazon's been tremendously successful at when you think about what they have to do to make inventory across hundreds of thousands of retailers feel like a single pane of glass, the complexity that they are managing behind those services is amazing and they're able to do it because they use that service as a approach. And it sounds like that microservices approach would be appropriate not just for the legacy monolithic apps but for the Greenfield ones too. Absolutely. It's the separation of concerns. Yeah, I've been fond of telling clients that basically anybody that comes in and says they've got their future state figured out, I would throw out of my office because if there's one thing I've learned in let's say 20 odd years of doing these kinds of projects and building things with data, it's that whatever we think we understand about the world today, two years from now, there's gonna be a bunch of options we can't anticipate that will change the way we'll think about things. And so we should be architecting and building for a state of constant change and innovation, not some city on the hill that we exquisitely design and set out a multi-year roadmap to get to. Well, okay, that actually raises another pretty serious question which is you have the legacy app which itself is generally monolithic because modularity was very difficult back then. So how do you make that future proof or as future proof as your microservices Greenfield app might be?  In other words, abstracting away and using a legacy approach, a mainframe in some cases, a legacy specialized industry-specific application, I don't know, to run mining equipment or something. And those things indeed work and you don't replace them until you can improve them or at least lift and shift them to modern architectures. And typically we're leaving them in place and then forking them for other purposes, right? So on the inputs, maybe we'll do that same services trick and start feeding them both the inputs and feeding the outputs to services for the rest of the world, whereas their stove-type pipe stays unchanged at least as far as the consuming applications. Oh, so you put essentially new interfaces on either side. Exactly, so it's forking the pipe of data, right?  And then similarly, if that application is providing valuable outputs back to the business fork the responses too. So we'll do this like with inventory systems in a supply chain or something like that. You're still getting the updates in the same way. We're just listening in on that same pipe basically of where those updates are coming from so that we can handle them elsewhere. And on the same time as it sends out updates about inventory, we're listening to those as well. And so actually that's a great example of a Spark application. We actually built for a major retailer to manage real-time inventory over the holidays, right? So you're sort of taking the batch 15 minute interval legacy inventory application on the one hand and you're listening to those updates in real-time and keeping a real-time Delta over here in memory alongside of it. Oh, you have a shadow. So you're basically shadowing it. So now I'm still using my legacy inventory system as intended but I've got this real-time service sitting next to it that allows me to do fundamentally different things on the holidays and I think they credited that with something on the order of a 20 to 30% lift in online sales for them. All around Black Friday, if I'm not mistaken. I think I read the case study on the website. Old Dogs, New Tricks is what it sounds like. Good deal. John, thanks for being with us. We appreciate your sharing the information and your time. Hey, it's my pleasure. It's been a good time. Good to have you. The Cube continues from San Fran right after this.


All right, videos come in from Alexei Navalny's funeral and from the ceremony at the church and then the ceremony at the burial site at the graveyard, the cemetery. And it's quite stunning. Thousands and thousands of people came out, both in these are different people because there's a distance between the two, both at the church and at the cemetery. Think about this. This is Moscow in February 1st of March. It is really cold. You can see how well-dressed they are, how coats and everything. It's cold. There's snow on the ground. But more importantly, in both events, security forces are out in force. They are taking pictures. They are documenting who is there. Anybody who comes there is, in a sense, risking getting on the wrong side of the Russian security forces. They were chanting Navalny, Navalny, Navalny. They were clearly supportive of Navalny. And I think this show of support, in spite of the risk that these people are taking on by being there, is an illustration of why Putin had to kill him. Navalny, for whatever reason, and I don't know Navalny well enough, and I don't really understand the psychology of charisma particularly well, was incredibly charismatic and really brought out and became a symbol of the opposition against Putin and the opposition against the current regime in Russia. Whatever his qualities as an individual human being, he became that symbol. And he really rallied people around him. Now, I don't think he was a real threat to Putin. But who knows over the long run? Who knows if something bad happens? What could result? I think the Russian people are basically sheep and have accepted Putin and accept pretty much anything Putin does. But Navalny stood something in them that scared Putin. And therefore, Putin had to get rid of Navalny and did and did. And there was some talk about maybe there was going to be a prison exchange when Navalny was going to be released together with the Wall Street Journalist in exchange for this guy in Western Europe who sent us a life for murder. But I don't think Putin wanted Navalny in the West either. Putin didn't want Navalny alive. He tried to poison him once. And he sent him to Siberia. And he killed him. And now he's dead. Tchaikovsky, by the way, is unconvinced. In his lecture, Friedman, each of you, he does what he always does. This is a standard practice. I'm only asking questions. I'm only asking. I don't know what the truth is. But I'm just asking questions. You guys can accuse me for just asking questions. But is it possible? Is there an incentive maybe for the Biden administration to actually kill Navalny? I'm not saying that happened. I don't know. Indeed, I have no evidence that that happened. But I'm just asking questions. That's what I do. I'm a journalist after all. So I ask questions. That is so dishonest. That is such a logical fallacy. And it blatant attempt to manipulate people. It is the embracing of the arbitrary, all in the name. This is how conspiracy theories get going. Very few people start out with conspiracy saying, no, this. Yeah, they really do this. The aliens do come down. You say, yeah, well, is it possible? I don't know. Maybe it's true. I don't know. Yeah, I think one of my goals in life now is to do as much as I can in the little world in which I live, which is pretty small, to point out how disgusting, awful, horrible. And what is it? Adam Carlson, a weasel, Tech of Carlson, actually is. I mean, I wasn't very successful in convincing people that Trump was, all of those things. And I probably won't be too successful with Tech of Carlson after all, his interviews have gone millions of years.  It's probably therapeutic for me to try anyway, to know that I am at least on the side of justice and truth.


Hello, I'm Philip Cohen here to answer the question, what is life expectancy? Life expectancy, as we usually use the term, is the average lifespan for members of a hypothetical cohort aging through the measured mortality rates of a given period, usually more or less the present. Life expectancy is a statistical projection of those current conditions. It's a useful way of summarizing the mortality situation for a population in terms that the average person can understand years of life lived. It is also the source of a lot of misunderstanding. What life expectancy is not is the age someone can expect to live starting now. It is not how long someone born today will live, we have no way of knowing that. It is not how long some members of a previous generation have lived. We might be able to know that if we wait long enough to find out, but that's usually not what we want to do either. And life expectancy is not a prediction or a forecast of what will happen in the future. Remember, life expectancy is the average lifespan for members of a hypothetical cohort aging through the measured mortality rates of a given period. The example I'll use today is the average lifespan of U.S. residents living their whole lives under the mortality rates observed in 2017. They're born in 2017, they live their first year in 2017, they live their second year in 2017, they live their whole life in 2017 exposed to those risks of dying that we have already measured. And we'll see how long the average member of that hypothetical cohort lives. In the United States for 2017, the answer was 78.6 years. Formerly, demographers call what I'm talking about period life expectancy. It is the life expectancy of a hypothetical cohort living through one period in time. For our example, we'll start with the mortality rates for every age in the United States in 2017. I've converted the death rates to a log scale here so we can see the fine differences at very low rates of mortality, which we have at young ages. You can see that age zero is the most dangerous year in the early part of life when a little more than one half of 1% of American babies died in their first year of life in the year 2017. Those who made it out of that year experience much lower death rates through their early years until in their teen years, the death rates start rising. People experience accidents of violence and so on. And then later in life, other kinds of diseases, diseases of old age start to come into play like diabetes and hypertension and cancers and heart disease until by the older ages, the death rate has risen and risen and risen until the finally at the very end, everybody will be dead. So we'll take our hypothetical cohort, 100,000 individuals and we'll subject them to those observed mortality rates that we saw in the year 2017 in the United States. We lose about a half of 1% in that first year of life. Then we don't lose very many more for the next 10 or 15 years. And eventually you see them start to drop off as mortality rates eventually rise. You don't get below 90,000 of that 100,000 member cohort until almost age 60. And then you see the mortality rates as they rise. We start to lose more and more until you get eventually all the way down to zero members of the cohort left after age 100. So just looking at the experience of those 100,000 people, we can calculate how long the average member of that hypothetical cohort lived. In this case, United States 2017, the average member of that hypothetical cohort lived 78.6 years. That was the life expectancy in the United States, that top line number that we hear so much, life expectancy 78.6. Technically it's life expectancy at age zero, but we usually just call it life expectancy. One thing you can see is that as soon as you make it past that first year of life, you can start to expect to live longer than the life expectancy at age zero. For example, people who live to age 20 in our figure have a life expectancy of 59.4 years left. That's the average years left for people who reach age 20, which will get them up to age 79.4 on average. If people live all the way up to age 70 in this hypothetical cohort, you see on average they will have 15.7 years left to live, which will get them to age 85.7. In fact, some people live past age 78.6 altogether, and those people obviously are expected to live beyond age 78.6. Using our data from 2017, if you make it to age 100 in the hypothetical cohort, you have an average of 2.2 years left to live. This is why it's not correct to say, I'm 75 years old. I live in a society where the life expectancy is 78.6. Therefore, I have 3.6 years left to live. Once you've made it to age 75, your life expectancy is considerably higher than the life expectancy at age zero. So we return to what life expectancy is. The average lifespan for members of a hypothetical cohort aging through the measured mortality rates of a given period, that statistical projection of current conditions, gives us a good picture of what the mortality experience of that population is without giving us a prediction or a forecast of the future. It's just a way of summarizing the mortality situation for that population in terms the average person can understand years of life lived. Now, if you want to know the actual life expectancy in the United States, today, I always recommend checking the National Center for Health Statistics page, and I've provided the information there.


My name is Alex. I grew up in a Christian home, and I was born in a church, pretty much. I've been going to church my entire life, but I haven't really followed the ways of church exactly. Like, I believed in it, but not to, like, a passionate point.  Alex, do you believe in Jesus Christ as your personal Lord and Savior? Yes, I do. Do you promise to follow Him all the days of your life? Yes. Based on that decision, we're going to baptize you in the name of the Father, in the name of the Son, and in the name of the Holy Spirit.


You have a great prototype, but it needs to get to market. It needs to get to commercialization. It needs to get to users. And we have a real gap right now in social innovation of groups that will support that. So my plea is, particularly to funders, focus on proof of concept to commercialization. That valley of death, it needs to be supported without it. There is no impact at scale. Our innovations are products that empower people living on less than $4 a day. And we've chosen to work in medical devices. There's three things to know about the products we do. The first is that they're world-class, meaning that they perform on par or better than the best products on the market. My second point, which is that they need to be market-driven. So the products need to be affordable. And then the third thing to know about our product development is that they're user-centric. And this means not just designing for the end user, but designing for everyone who is in that customer chain. That could be the purchasing decision maker, and it could be the technician who repairs it. Our Brilliant's project started when an Indian doctor approached one of my colleagues and said, you know, everyone's focused on the big ticket items in neonatal health. But there's low-hanging fruit. And there are babies that are literally dying. They don't have phototherapy. They don't have treatment for jaundice. Brilliant's is phototherapies. And that's just blue light to treat severely jaundice babies. We licensed it to the largest maker of neonatal equipment in India, named Phoenix Medical Systems. We fixed the price so that there's price transparency, very rare with medical devices. But we also said, if you sell to public or rural hospitals, we will take less royalties. DRIV also works in mobility. And another product we've designed is the Remotion Knee, which is a prosthetic knee for above knee amputees. It's a four-bar mechanism that mimics the natural gait of how humans walk. We've worked with the diaper foot clinic and they have that first version of the knee and it's been fit on over 6,000 amputees. We think about the entire product lifecycle. So not just the design of the thing, but the problem we're trying to solve and how do we get to impact. It's about a four-step process. The first is identify, which is understanding what the problem is. And it's not just who the users are and what the markets are, but what is the price point. The second step is design. And design is what you traditionally think of with product development. It is brainstorming around what are the crazy, far-out ways we might be able to solve this problem. It's prototyping, it's iterating, it's talking to users to get to a final embodiment that will go to commercialization. The third step is deliver. And this is manufacturing, distribution, marketing, selling. If you're working in medical devices, it's also, it could be regulatory. You need to be thinking about this delivery phase in that identify phase. You need to be thinking late stage as early as possible in your design process. Shouldn't you want to be able to measure the impact? Are you in fact solving the problem you set out to solve? Where are possible we design impact assessment into the products? So with Brilliant's, the phototherapy device, it self-tracks. So we actually know from the device how much it's used and from those numbers, we can calculate the number of babies treated by Brilliant's units. We can estimate the number of babies treated by Brilliant's who otherwise would not have received effective phototherapy. And from those numbers, we can estimate the numbers of deaths and disabilities averted. In using the private market to deliver our products with it also means is that you need to design not just a very affordable product, but an affordable product that has profit margins built in. So that, for example, if DREV disappears tomorrow, the product will continue to be sold because the financial incentive structure is in place for that. One of the things we recognize very early on at DREV is that we can't do everything, particularly around delivery. We work with all kinds of partners. We work with NGOs. We work with for-profit companies. We work with faith-based organizations. What we're really looking for in our partnerships is who is the best entity to help us achieve our mission. And that means getting the products to our target users. We get a lot of questions of, how come you're working with a for-profit? Is DREV just using philanthropic funds to support a for-profit's work? We raise philanthropic money for our identifying design phase. So think about that as like product R&D. But once the product hits the market, it needs to be entirely economically self-sustaining. And we are structured like this because we think this is the best way to scale a product. And it also holds us accountable at the same time to making sure that we're actually designing a product that solves a problem. And when you have partners that are working together to bring a product to market and everybody has skin in the game, that's how you solve the problem and that's how you get the products to impact.


Hi everyone, Joe for jasperjasecasebreaks.com coming at you with 2021 Panini Zenith Football. This is first off the line edition and we're doing all 12 boxes. This is random team break number two, all card ship, a lot of nice stuff in here. So big thanks to this group for making it happen. I appreciate everybody who bought their spot straight up. Congrats again to these people who tried those fillers and won those spots as well. Thank you. All 32 football teams are in. Let's go. Let's roll it. Randomized names and teams. 10 the hard way. 5 and a 5. 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10th and final time. After 10 we've got Chris down to Corey. 5 and a 5. 10 times for the teams. 1, 2, 3, 4, 5, 6, 7, 8, 9 and once more, right? 5 and a 5. 10th and final time. There's 10. Niners down to the Titans and here's how it shakes out. Chris with the 49ers, Aaron Jennings with the Dolphins, Dusty with the Eagles, Chris M with the Packers, Nolan with the Seahawks, Sean Peterson with the Patriots, Steven Last Bob Mojo, Los Angeles Chargers, Evan with the Commanders, Sean with the Colts, Thomas with the Chiefs, Sean with the Cowboys, Renee with the Jaguars, Jared with the Bears, Simon with the Lions, Martin with the Panthers, Chris with the Rams, Dusty with the Broncos, Alefonzo with the Steelers, Jeffrey with the Falcons, Gale with the Buccaneers, Sean with the Vikings and Bills, Jim with the Saints, Mark with the Cardinals, Michael with the Ravens, Dusty with the Bengals, Chris with my Raiders, Mike Joseph with the Jets, Steven with the Browns and Texans, Nolan with the Giants and Corey with the Tennessee Titans. So let's sort by column A. There are two last Bob Mojo stars right here. What did I do? Oh, I know what I did. We released more spots. But anyway, we'll leave those two last Bob Mojos there. All right, we're going to pause the video. When we come back, we're going to see if there's any trades and then we will have the full case break. Stick around. Be right back. Okay. Welcome back, everybody. No deal. There's a lot of trade chatter, but no deals were done here in Zenith football first off the line. A pretty underrated product, I think. I think this stuff looks really sharp. All right. So there it is. Zenith first off the line. Good luck. Good luck. Good luck. Top load I need to use for this. Just swing it. All right. So you can see all the 12 boxes up on the top camera right there. Let's do it. Two autographs and one memorabilia card per box on average. Six cards total. So three hits and then three other cards. I think it should be, yeah, a base card on the bottom. Let's use this blank card right there. There's two to that. Well, Josh Jacobs and number Josh Jacobs. That's to 49. That'll be for the Raiders. That's going to go to Chris Hansen. Five out of 49. And your hits. We've got Juju Smith's Schuster, Chase Claypool and Deontay Johnson. Those are nice trio of patches there. Eight out of 10. It's a nice looking triple relic for Alessonzo and the Steelers. Nice team summit card. And we've got a Brandon Cooks autograph, 42 out of 100. Inscriptions. See, let's use another blank card to kind of show you the acetate look right here. That's pretty cool. That will be for Stephen Flatt and the Houston Texans. And back here we've got Simi Feoco, 38 out of 50. I wonder if this speckle is the first off the line exclusive. Let's see if it's in the item description maybe. Yeah, look for one rookie patch and autograph sparkle out of 50 or less. And one pinnacle inscriptions autograph in every first off the line box. All right, so there you go. I'll give you an idea of what to expect out of here. All right, there's Jaylen Waddle, Daniel Jones, and a Josh Allen Epix to 99. We've got a Z Jersey's, Joe Burrow. Nice. 106 out of 149. Bangles. That's going to go to Dusty. Did what on purpose Rex? There is 25 out of 50, Tyron Matthew. Nice parallel there. Chiefs. That's going to be for Thomas Mosley, Kansas City. And the sparkle. Cadarius Tony. Out of 30. Nice RPA. I like that sparkle design. That looks sharp. New York football giants. That's going to be for Nolan, Tray Lance, Jared Goff, and we've got the Big Ben Rothsburger Ariel. What are the Steelers going to do to replace Big Ben? There's Andre Johnson for the Texans, Z Jersey's. 99 out of 149. Stephen Flatt in the Texans. And we've got an Aaron Donald, Super Bowl champion. 44 out of 100. Instead of 99, they added one more. Oh, you're talking about the Brandon Cooks. No, I think the base ones are always 100. Are going to be 100 for these pinnacle cards. That's for the Rams, Chris Hansen. And a nice Chuba Hubbard piece of the panther maybe? Yeah. That is 9 out of 35. Chuba Hubbard patch and autograph for Carolina. That's going to be for Martin and the Panthers. Next box. And we've got an out of five, Derek Henry. Out of fives and under. Train whistle, Corey. The world famous train whistle. All aboard the Big Hit Express. And we've got a team summit, triple relic. Russell Wilson, DK Metcalf, Tyler Lockett, 31 out of 50. That'll be for Seattle, Nolan with the Hawks of the Sea. And we've got Rams edition of Jared Goff, 29 out of 50. That's another ram for Chris Hansen. And we've got Davis Mills for the Texans, two-color passion auto. 11 out of 50 sparkle autograph for Stephen Flatt and Houston. Oh no, your TV internet cut out when I pulled that Henry. Come on, TV. It just couldn't handle the train whistle. Don't worry, this is all on wax. We're recording this. So you'll get to, once this video is uploaded, you can replay the moment over and over again. In fact, I'll tell you what, ladies and gentlemen, we stream in 720p, but we actually record in 1080p. So when you re-watch your breaks, they're actually being better quality than if you were watching it live. 27 out of 50. There's Nick Chubb for the Browns, Z Jersey, 37 out of 149. Cleveland, this is for you. Stephen Flatt with the Cleveland Browns. And we've got an Aaron Jones, 003 out of 100. Chris M with the Packers. And we've got a Travis Etienne. Ooh, nice patch right there, too. Eight out of 50, or eight out of 30, Sparkle. Panini hitting you with that nice Jaguar's patch right there. Jaguar's owner, Renee. Rex is wondering, so who's considered the goat of the NFL prior to Brady? Good question. Joe Montana, maybe? Speaking of Brady, there he is. Oh, and we've got Patrick Mahomes back there. So this will be a randomizer. Buck and Nier, well, we'll do a front-back randomizer at the end, that's what we're going to do. This was numbered, I'd randomize it between the teams, but there may be others like that. All right, we've got Josh Allen, Z Jersey's to 149. Sean Peterson with the Bills. Gardner Mintchew, Jaguar's, 51 out of 100. Maybe there wasn't really a clear goat before Brady, Rex. Not sure, anyone else have any thoughts on that? Renee with the Jaguar's, and then we've got Rondale Moore, three-color patch, Sparkle, 19 out of 35. Mark Rao and the Cardinals. Pat Friarmouth, McAfrey, Devonta Smith, 9 out of 10. Joe Mixon, Z Jersey's to 149 for Cincinnati, Dusty with the Bengals. And then we've got another Aaron Jones, 004 out of 100. It's another one for Chris M. And we've got a Simifoco. 10 out of 50, Sparkle, two-color patch, Sparkle, and Autograph, RPA. Another one for Dallas, that's going to go to Sean Peterson. Redemption on the bottom. Got a Jarvis Landry, three out of five. Cleveland, this is for you. Stephen Flatt with the out of five. Stephen. All aboard the Big Hit Express. Got a Joey Bosa, 49 out of 50 for the Chargers. That'll be for Stephen Flatt as well. And we've got Steve Young, 24 out of 50. Nice. This'll be for Chris Hansen and the 49ers. Nice one, Chris. And the Resemption is Anthony Schwartz for the Browns. Cleveland, this is for you. All right, four boxes to go. Loaders there. Got an Ariel Drew Brees. Got a Thurman Toss, Jersey, 21 out of 149. Sean Peterson with the Buffalo Bills. Buffalo! Buffalo! And we've got a Dion Sanders, neon Dion Sanders, 29 out of 50. Dallas, that's going to be for Sean Peterson. And we've got a Chuba Hover, two-color patch and auto. 24 out of 35. Sparkle for Martin and Carolina. Another redemption. Got a 5 out of 10, Josh Allen. Buffalo! Tara McLaurin, Z-Jersey's. 9 out of 50 for Evan. And the Washington Commanders tried to trade, couldn't trade Mojo. A little something here. And AJ Green, Bangles Edition. 11 out of 100. Is that his jersey? Or is he, oh no, it's not. He's number 18, it says right there. It's Dusty with Cincinnati. And the redemption is, oh! Another Bangles receiver. That's rookie patch, autograph, Sparkle Jamar Chase. Nice Jamar Chase, your offensive rookie of the year. Got a Jalen Waddle, 26 out of 50 for the Dolphins. It's going to be for Aaron Jennings. And your hits, we've got a Clinton Portis Relic, 65 out of 149 for Evan. And we've got another Bangles receiver. Chad Johnson, 38 out of 100. AJ Green, Chad Johnson, Jamar Chase, three great wide receivers for Dusty and the Bangles. Jamar Chase might end up being the better of those three too, isn't that crazy to think about? And we've got Matt Jones, return of the Mac, 13 out of 30. Sparkle, four color patch and autograph. Patriots, Sean Peterson, Pats. And the last box, good luck everybody. Got five out of 50 Devante Adams, where does he sign? Maybe he just re-signed with the Bangles. There's Joe Montana, Steve Young, Trey Lance. And if Trey Lance can be in the conversation with these guys, I think Niners fans would be very happy. Chris Hansen, with the San Francisco 49ers. And we got Clay Matthews, Rams edition, 11 out of 50. And that is for Chris and the Rams. And last but not least, it's Ian Book. Book it, three color patch and autograph, 38 out of 50 for the Saints. Who's got Nolans, New Orleans, Jim Murray. There you go, Jim, good to see you. Here's the Ian Book, little something for you. And that's that, boys and girls. Nice, first off the line break, that was a lot of fun. Let's do a front-back randomizer on this, which will include any other front, I don't think there are any other front-back cards, but it'll include any of the other cards if I missed any. Let's go back to the dice, let's go here. Front, back. Let's roll it, randomize it, two and a two, four times, side on top gets it. One, two, three, and four. So the front side will get it, so that'll be the, for this particular card, the Brady side. And that'll be for Gail and the Buccaneers. I'm Joe for jaspeaskasebrakes.com. Thanks for watching the Zenith first off the line break. I'll see you next time for the next one, bye-bye.


So HDMI 2.0a has been announced, you want to go right? Yes. So what's new with this? So HDMI 2.0a adds new HDR capability. So now HDMI is able to pass the new HDR standard, HDR which stands for High Dynamic Range. So many new content, everybody from Netflix to Blu-ray will start carrying new content that has HDR enabled, which will give much better luminosity and color and vibrance to the video. And now HDMI supports that within the HDMI 2.0a specification. So 4K is already awesome, but HDR is like a whole new level of awesome video? Yes, so 4K gives you resolution, but what HDR gives you is more dynamic impact. So everything kind of color, clarity, everything kind of pops out of the screen. So not only do you get clarity with 4K, but now with HDMI 2.0a you get HDR on top of 4K. But is it still realistic? Or does it kind of seem like animation style when it pops out, so much stuff pops out of it? Or is it actually like it really is supposed to look like in reality? So I think it depends on how it's recorded. So the director, whoever's producing the content can make it as realistic as possible, or as cartoonish or unrealistic as possible. It's up to them. Because some movies or TV shows, they want to make it very stylistic, artistic. So it may not look real, but it looks very good. Whereas someone else doing documentary or whatnot want to make it as real as possible. Because the camera doesn't have the same dynamic range as the eye. So with HDR you can do both. You can do it unrealistic or you can make it as very realistic.  Yes. So now it's going to be video in 4K HDR. Yes. So there's 4K HDR TVs starting to ship or already shipping? Yes. Many manufacturers here are showing HDR capable TVs already and they're already shipping in the market. Availability depending on the region. But they already have it. Netflix, Hulu, Relieve Amazon as well. YouTube maybe soon? Maybe YouTube, I don't know. Ultra HD Blu-ray that I've announced. They'll support HDR. So as soon as content comes out you'll have to have access to them. So this is the paper you're giving out with information? Yes, that's the thing. Thank you for doing that survey. So there's this white color gamut. What kind of stuff are you talking about here? Is it more colors? Is it more bandwidth or is it the same bandwidth? And just different data? It's just color space. So color space is what the industry uses to map color. So if you look up basically the VT 2020 color space specification that has more details in it. But HDMI is just data transfer, right? Yes, for audio video. There's no color? Well, it has to carry everything, right? Video has color resolution, frame rate, color pixel depth. So many things we have to carry all the information now with HDR as well. So all the information has to be present from source to the display so that the display can render everything properly. That's the new thing that's going to happen. Like 4K cameras will record HDR 4K. Yes, they already have that available. So professional guys, professional cameras have been able to do 4K for a long time. There's nothing new for them. And so now finding the consumer have access to that type of content. Is it required to have the high and the low and the middle? Some kind of average? You know, like with the light? Is that how HDR has been made? So the luminosity range, again, that's specified by the HDR specification. So that's a different specification. One of them is CE861.3. So that specification defines luminosity. And the luminosity really depends on the TV as well. So some TVs will have very large luminosity. Whereas, you know, other TVs might have less. It depends, right? Alright, so there it is. HDR HDMI 2.0A. Find more information at HDMI.org.


Hi, I'm Sandi Allnok, artist and paper crafter here on YouTube, and today I'm going to use the Garden Charmers stamp set from Penny Black to do a little watercoloring. So it's spring time, spring summer is a good time to do flowers and birds, so I'm going to use the bird from this set, but I'm going to combine it with this branch of flowers. If I were to use some of the other flowers, I have to do some depth of field stuff unless the bird was just going to be honking big. So I decided to use one that was going to work size-wise. So I've stamped the bird and then stamped this branch of flowers twice. So I'm going to finish off the branches that the bird is on by using the same kinds of things that are in the stamp already. See those little buds on the branch? I'm just going to add a few more of those so it looks like it belongs, like it's part of the same image even though it's not. And now it looks like I have all one image in a garden with the bird. So I'm going to start by painting my flowers and I've got my palette with my dot card colors. A dot card is something that is produced by Daniel Smith for some artists. They ask you to pick your favorite 18 colors and this was like picking between children. So these are the ones that I had to choose. I yeah, don't tell the other colors because they'll be sad that they didn't get chosen. This is quinacridone pink and I've put some color at the center of the flower and then I'm using clean water to move the color around. I'm not using a ton of water. It's a damp brush, not super wet.  In general, watercolor is best shown off when you have hard edges and soft edges and some deeply colored areas, some really light white areas and leaving that those edges and that sort of thing is what makes watercolor really sing. So allow yourself permission to not fill in every scratch. This is not Copic markers. We're not trying for perfection. We're trying for that that loose feel of watercolor, especially on a beautiful spring card like this. The brush I'm using is by the Silver Brush Company. I believe this is a number 12 and I am a firm believer. The more I do this, the larger brush you can get away with the better. So if you are looking for a challenge for yourself, go up a step or two in your brushes and it makes a difference, especially if you plan on someday trying to graduate to making a full-on painting yourself. That's always a fun goal to have and if you get used to painting with larger brushes, it'll be easier to think large and be able to paint large later. So now I'm going to add in the blue sky. I'm using Manganese Blue Hue, which is a beautifully granulating blue and you can make it really rich, but I'm going to start off with it fairly light and you can see with the brush, I just kind of suck the paint out of there and then put it on the palette so I can mix it to the consistency that I'm looking for.  I am going to get richer later with the color, but the reason that I did the flowers first is so I don't paint the blue right over top of the flowers, but I can paint blue right over top of that green when I get down to the branches down below. Then I'll start off with my richest section of sky up here in the big empty corner, which I like to leave an empty area kind of on a painting or on a card, either one, but on a card, especially because I need a place to put the sentiments. I'm going to stamp my sentiment there later and I'm going to throw some lighter blue here in the rest of the clouds, leaving some white, but I didn't leave enough white for myself as I was doing this. But the good thing about watercolor is that it lifts nicely and especially when you're using a light color like this, as well as a light touch of it, it's very easy to just grab a tissue or paper towel and lift off a little bit of color. But it still has that overall blue hue, so I'm going to need to add more contrast in order to make that not look so blue down there. I'm going to start by kind of softening out a few of my edges on my clouds because cloud edges are generally not hard. And then I decided it's time to go darker. So while this paint was still damp, a lot of people say don't paint on damp paint, but I'm a believer in doing what works. And on something like this, I want the colors to merge together, so I'm going to just continue to paint that nice rich blue color so I get some really good blue sky and have a multiple cloud type of scene rather than just one big cloud or that sort of thing. So I'm just going to intensify the blue in a few of these areas. Make sure you don't stop at one of the branches carried over across so that it looks like that continues in the scene behind that kind of thing. So now that all that's dry, I can jump in and start working on all of my branches and painting them with sap green. Instead of transferring that sap green over into the palette, the mixing area, the mixing well, I just put some water into the pan itself and dipping my brush into that and managing the amount of it, since I'm now used to doing this, managing the amount by just wiping it on the side of the pan. For some people, that's not helpful. So if you're just getting used to how much paint is on your brush, how much water and that sort of thing, it's going to be much more helpful to mix in the well because then you can see exactly how you're mixing it. Is it more of the consistency of milk that you want? Or are you looking more for tea? Or as a recent instructor that I took a class from, he had names for paint all the way up to soup and all sorts of thick things as well, so he had very interesting ways of labeling the mixing of his paint. But I just dropped some water into the well so that I could pull it from there. Now if you do that, you'll notice some of mine have sort of like a little hole in the middle. That's because the water settles down in there and then as it evaporates, it sort of pulls all the air, all the water out into the air and then the paint remains. And often that just ends up with a little hole in the middle. Not a big deal. It does not make the paint any less paintable. Now it's something like this too. I'm going in as I'm doing this and figuring out that there were some areas that I missed a pink flower and that sort of thing. And there might be some areas where I painted a petal of a flower with my green.  That happens from time to time. Don't beat yourself up either if it happens to you. Most people aren't going to notice but I have found that there are people here on YouTube who like to point out when you make the slightest little error that that a leaf got painted with the flower color or vice versa. Lots of the folks who are on YouTube are not veterans like me. Haven't been around a while. And you could actually by making a comment saying, did you notice that you painted that one thing wrong or that blood over there? Why did you leave that? It didn't work right. It looks terrible. If you say those kind of things to folks, they are probably not going to continue making free videos for you.  You know, it's just, yeah, just standing up from a fellow YouTubers out there because I see a lot of comments being made that are just not kindly. And on clumps of flowers like this, it doesn't really matter. I'm adding as you see an extra layer of that dark pink color and nobody's going to sit and analyze every single piece to see if it was a flower or if it was a leaf. It's just fine. Now for the bird, I decided to make him blue. I originally thought about doing a, you know, chickadee type of bird or you can do something with all different kinds of markings that you can look up birds on Pinterest or on Google to try to find exactly what bird you want to use. But I'm going to use some phthalo blue red shade and then drop in a little Indian throne because Indian throne is a really nice, rich dark blue. And I'm just going to add some of that and let it mush into the rest of the color. It's going to give that that rich pop of color against all of these black outlines and those beautiful pink flowers. And now I'm going to add a sentiment from this pretty pink posh set. Look at the beautiful script on these. Just love it. Add it on. You are amazing. Onto my card and put a couple layers of paper and made a five and a half by five and a half card. The painting itself is five by five. So there you go. There is my painting of this beautiful garden charmer's stamp set. Hope you enjoyed this and learned a little something from it. You can click on my face to subscribe to my channel, watch another video or go take a watercolor class over on my newly launched art classes dot com website. And I will see you guys later. Have a good one. Bye bye.