There was a really interesting question asked of Boris Johnson on Wednesday by Sam Coats from Sky News immediately following Joe Biden being sworn in as the US President of the United States. I thought it was a strange question at first, but the answer it elicited I think reveals some of the difficulties the Tories will have going forward. So let's take a look. Do you think that some senior politicians in Britain seem to? The President Biden is woke. I can't comment on that. But what I know is that he's a fervent believer in the transatlantic alliance and that's a great thing and a believer in a lot of the things that we want to achieve together. OK, so that answer is not why I made this video. There's nothing special about it. It's an identikit 6.5 out of 10 formulaic response of a British Prime Minister to a new President of the United States. We had this thing in common. We both care about it. That's what I'm looking forward to working on. Case closed. But it doesn't end there. Before we go any further, when I first heard this, I saw it on social media, I thought this really betokens how stupid, how uniquely mediocre the British media is. But I think it's more to it than that. On the one hand, you could say, well, look, more than 100,000 people have died of COVID. I think more than 1,600 people died on the Wednesday when that question was asked. On the one hand, you could say, well, given COVID, this is a really banal, stupid, pointless question, has zero relevance to most people's lives in this country. That's what my initial thoughts were. But then Johnson got himself in a bit of a muddle. And I think his inability to give a straight answer and that muddle, like I say, I think, sort of points towards problems the Tories might have in the terrain of the cultural going forward. And insofar as nothing wrong with being woke, what I can tell you is that I think that it's very, very important for everybody to, and certainly I will put myself in the category of people who believe that it's important to stick up for your history, your traditions and your values and things you believe in. He is really reaching there. He is really reaching. But what I want to say is the Labour Party, Keir Starmer, anybody who wants to attack Boris Johnson politically come 2024, January 20th, 2021, Boris Johnson said there's nothing wrong with being woke. There's nothing wrong with being woke. I'll go on to the rest of the answer in a second. What was interesting is that his spokesman afterwards told the Daily Mirror they weren't actually sure what the word woke means. So we've got Boris Johnson, the Prime Minister, saying he has no problem with woke and we know why. It's because Joe Biden and Kamala Harris, you might not agree with their policies.  I would think that. But clearly on issues of sort of socially liberal issues, trans rights, they've repealed the legislation that Trump introduced to stop trans people being in the army. Kamala Harris has her pronouns in her Twitter bio, little things like that. These are things which if it was a politician in Britain, Boris Johnson would be going for them. And so in that sense, it was a very clever question because it really gets to the heart of, well, you want this relationship with the President of the United States, which is the Prime Minister of Britain you kind of have to have. But at the same time, your kind of golden ticket electorally means you can't really go to town on that anymore. Can you? Which I think is interesting. So like I said, the aid says they don't really know what it means. Boris Johnson says he has no problem with you being woke. Let's go to Sunday, Sunday, not a year ago, not six months ago, several days ago. This is Robert Jenrock. He's a relatively senior minister. I think he's Secretary of State for Housing and a few others. We will save Britain's statues from the woke militants who want to censor our past. Now, this is the line which is where woke is repeated again. That awful sin. Latterly, there's been an attempt to impose a single, often negative narrative, which not so much recalls our national story as seeks to raise part of it. This has been done, at the hand of the flash mob, or by the decree of a cultural committee of town hall militants and woke worthy's. So we have a problem with woke worthy's, if you're Robert Jenrock. We don't have a problem if you're Boris Johnson and Boris Johnson's advisor, who speaking to the press doesn't even know what the term means. So it looks like the tour is a bit of a mess when it comes to their war on woke and clearly they've had a war on woke for a long time. Even though I don't really like the way the word is deployed in the UK context. It comes from African Americans. Basically, it means the culture war basically means if you believe in equality under the law, right? It basically means I want to treat other people like I'm treated myself. That's basically what being woke means. Essentially, you know, it's not much deep. It's not much deep. There's more to it. It's much deeper than that. So they're in a bit of a pickle. And they're not quite sure where to go next. And I think that was revealed actually in the rest of Boris Johnson's answer. Whereas, you know, you can be woke, but for me personally, I think, you know, and he started to reach for the all the all the certainties of conservative ideology, our traditions, our history, our values. You can't see the free market anymore because the tour is running a half trillion pound deficit this year. He can't say private enterprise because they were paying the wages of more than 10 million people this year on furlough. So the toys are having to go to their safe space. They're happy place of values, tradition, sort of Berke and conservatism, which doesn't really mean very much. You know, it's one thing to say church, family and faith, but Boris Johnson doesn't get a church. He repeatedly cheats on his partners and his wives. So I guess that that leaves the flag. Sorry, flag, family and faith, church, family and faith, whatever. You get the picture. That kind of conservative idea of of celestial power being translated into the earthly realm through the monarch of the divine right of kings. And, you know, that's kind of effectively continued to some extent through these Berkin conservative arguments, 18th, 19th century. Anyway, we don't need to go into that. My point is he was appealing to conservative arguments, which are very, very old and not new. But let's pick those apart. The traditions. Tradition doesn't mean anything. You know, people have had traditions of cannibalism. Doesn't mean it was good or incest or polygamy. There's all sorts of really screwed up traditions. And we don't do them anymore because they were wrong. It was traditional to think the world was flat. That was tradition. It was a tradition to think that, you know, the. People in sub-Saharan Africa weren't actually humans. That was a tradition. Slavery was a tradition. They did it. Tradition in itself is a good thing, is is clearly wrong. Clearly, it's an odds with the idea of human progress. We'll put that to one side. History is an interesting one because that, of course, comes through the Robert Jenrick article as well. It's about statues and public discourse and the kind of story we want to tell ourselves about what Britain stands for and where it comes from and what its values are actually. So history. Here's where I disagree with you, Boris Johnson and Robert Jenrick. You aren't worried about censorship of history. You aren't worried about people rewriting history. You're worried about history being told in the first place. You're worried that right now the one-sided account we get of Britain will change to more accurately reflect the facts. What you want isn't history. There's a word for it. So that's a P. It's called propaganda. That's what you want and you don't want any deviation from that. You want a set of historical facts, which aren't entirely accurate, generally aren't accurate at all, purely because you agree with them and they're advantageous to you and you like the sound of them, not because that's actually how things worked out. Now, I'll ask you this. Maybe you're British, maybe you're not. Were you aware that in the mid-19th century, British and French soldiers went to Beijing and they torched the summer palace and they burned it for three and a half days? Several hundred people burnt to death inside. So many treasures were looted that today, just from that one episode. They can be found across 40 galleries and museums around the world. Did you know that? Did you know that millions of people died in the 1940s in the Bengal famine or that millions died at the end of the 19th century and multiple famines in South Asia and India? Are you familiar with the Irish famine? The fact that today, Ireland has a population smaller than it did 150 years ago. That is not normal. That doesn't actually, that isn't really there in any country with a major population. That level of population crash. And that's because you had effectively the political imposition of famine by the British state in the 19th century. Now, there are multiple episodes of that. You know, we could talk about, are you familiar with the fact that there were concentration camps in Kenya after the Second World War when the British were fighting against the Mao Mao insurgency? Did you know that in Malaya, Britain innovated tactics which were used by the Americans in Vietnam? Did you know that the first use of napalm, recorded use of napalm in war, was by the British in Greece against Greek partisans immediately following the Second World War who'd helped defeat the Nazis? Now, you probably didn't know those facts. They happened. And that's because we don't teach history. We teach, sadly, to too great an extent, propaganda. Or, let's be fair, we've moved away from that in the last 30, 40 years and the Dories want to go back. They want to go back to Wellington and Nelson, and why Britain's always under the side of justice and righteousness and why generally speaking, brown people and foreigners are always wrong. Doesn't matter if it's true, that's the propaganda they want you to believe and to internalize. So, no, you don't care about history, Robert Jenrick. Boris Johnson definitely doesn't care about history, the complete opposite. The people who are bringing down the statue of Edward Coulson and actually asserting the facts about who he was and what he did, they're the people that care about historical facts. And then, finally, values. Values. This is something of a bugbear for me and it's not just with the Tories. You see it with politicians across the political spectrum. Kier Starmer says it, I believe in values. What values? Fred West had a set of values. Dr. Harold Shipman had a set of values. They're not particularly good ones. So, what values? I don't, by the way, I think any politician is as monstrous as those, but this is the question you have to ask. And then, adding to that, just saying you have values, like saying, I'm an honest person.  It's not a declarative act to be honest. It's through your actions. People don't say, oh, that guy's really honest because he keeps on telling people he's honest. So, he must be honest. No, they say, well, I've observed their behavior a long period of time and they embody the characteristic, the quality of honesty. Okay, so show don't tell when it comes to values. And Boris Johnson, when he shows, we know what his values are. He's a pretty nasty guy. You know, I don't need to go into the multiple details of this from being involved in the potential beating of a journalist who'd upset his friend, Darius Guppy, to somebody who was with him at the spectator. While he was married, there is the claim that he heavily promotes this person having an abortion. By the way, this was the reason why he was expelled from the shadow cabinet in the early 2000s. He was a rising star on the Conservative Party. I think he was 40 at the time. And this was a big blow. Story after story, after story like this. So if we want to talk about values, I don't think Boris Johnson is the best person to be, you know, leading that conversation. So, where does this take us? What I think it shows you is with Trump defeated, and I'm not particularly optimistic about the prospects for getting rid of the Tories anytime soon, because of demographics, because property values are going up, because of media ownership. I'm under no illusions whatsoever. Well, where I think they have a major problem now is that they can't really talk about the economy. They've got no message on the economy. They can't talk about low taxes and private enterprise because the high streets collapsed. We've got many, many precarious jobs. And realistically, we're gonna have 25 years of economic overhead of this, because of this, because of COVID. And they haven't had an economic model since 2000. We haven't had an economic model in this country since the 2000 net crisis. Tories come in, 2010 to 2016, we have austerity, budget cuts for no particular reason. We've lost economic decade on productivity, wages, GDP per capita, home ownership, bunch of statistics. We're clearly going backwards, life expectancy, people over 30 living with their parents, and so on. We've clearly kind of, we're not moving forward in a meaningful sense.  So there's no economic story they can tell. Brexit's done, and even if you think Brexit won't be as bad as the naysayers say, they're gonna have problems delivering what they've claimed they can achieve, right? The Tories, when it comes to Brexit, particularly on the hardest possible Brexit, you know, the real Brexit, are gonna really struggle in so much as they've really ever promised. Brexit was gonna be the solution to every problem when that's found not to be the case, even if things aren't terrible, which by the way, I think they very well could be. That's a problem for them.  No message on Brexit, like they've had since 2016. So you've got the cultural, now that was the plan. That was the plan. It worked alongside Brexit very well against Jeremy Corbyn, although I think Brexit was the primary reason they won that majority in 2019. But with Keir Starmer, they really wanted to lead even further into the cultural stuff. Islington Human Rights Lawyer, Romainer, you know, the left, you can't trust them. They care about these strange cultural issues. That's kind of undone when you've got the world's most powerful politician, Joe Biden, in charge of a country of more than 300 million people, 20 million, 20 trillion dollar economy, some of the world's most successful companies, geopolitical military superpower, and they're doing all the things which you say are beyond the pale. They're doing all the things, whether it's being inclusive to trans people, whether it's, look, policy-wise, Biden won't change that much to Trump in a number of areas, but rhetorically, on immigration, on LGBT rights, on foreign policy, they're not gonna be anywhere near as hawkish as their predecessors. And so that leaves Johnson isolated because they've left the European Union, they've burnt a lot of their bridges with the Europeans, and now Trump's gone too. So you have a context where the Tories are kind of rudderless when it comes to the story that they want to tell. And I think summing up, this tells us about the profound limits and problems of 21st century conservatism. It hasn't got an economic agenda like Reagan and Thatcher did in the 80s because the growth is no longer there.  It's called secular stagnation. And so it's very hard to be a right-wing populist when you're administering economic inertia and generally speaking, budget cuts, and generally speaking, all the things which you've championed for decades, rising home ownership, even if there's rising inequality, a section of society doing pretty well, that will no longer be happening. And so they kind of appealed to the free market stuff. Brexit was a bit of a sticking plaster and it was a good one, it worked, it's got an 80 majority. The cultural things, what they've got now, but is it enough? Is it a project that allows you to cement changes as seismic as we saw in the 80s? Which is what they wanna do. The 1980s reforged British society through right to buy, smashing the trade unions, privatizing loads of businesses and so on. Boris Johnson's big pitch is to recalibrate the British state and politics in a similar way. I don't think that's possible when your primary political instrument weapon against those opposing you is a cultural war which no longer makes sense. When you've got rising unemployment, when you've got high streets that look like, frankly, they've been bombed, some of these places, actually many of these places were bombed and they was never built back up after 1945. It's very, very, very hard to keep on talking about trans people and pronouns and statues. It's incredibly hard. COVID clearly is the major variable there, but now Trump has gone. It's gonna be very difficult for Johnson to normalize that because he's the only leading politician now in Europe, North America who's talking like this. He's gonna be isolated and arguably the terrain of the cultural war will look increasingly irrelevant. That's my take from a very short one-minute clip, but I think there's something there. There's a glimmer, there's a chink in the armor that this polarizing of the electorate around often stupid, fatuous things may not work for much longer.


OK, so good morning, everybody. I'm going to be talking today about something that as organizers of Big Data Spain, we keep seeing each year. We bring here some of the biggest experts in big data and artificial intelligence. They talk to you about the state of the art of artificial intelligence or big data. And we have many things, the feeling that you see this as something of the future, something that is the next big thing that should not be worrying you today. So I'm going to try to get you at least a little worried. And I'm going to start by talking about history and not the history of Spark or Hadoop or Big Data, real history. So in the 16th century, Spain ruled the world as it should be, right? So Philip II had the greatest army that the world had ever seen. And in fact, in 1588, he sent that fleet, which was called the invincible fleet. Nobody was supposed to beat it, to England, to invade England. If he had succeeded, the Spain would still be the ruler of the world. And this talk could be in Spanish, which would be much better for me. But he failed. In fact, he came up with the concept of epic fail. So it was one of the biggest catastrophes of military history. And seeing that, Philip II came up also with one of the greatest excuses in history, which is, I didn't send my ships to fight against the weather. So it was so good that many people remembered the excuse and not the fact that he invented the epic fail. So many companies are facing now a reality which is not so different from this, because the world is changing very, very fast. We see the kind of things that artificial intelligence are going to bring into every kind of business in the next years. And many organizations have not been built to resist these chains. So something must be done. And it's something that may cause the survival of the company itself. So there are only two options. Either you start looking for excuses right now, or you start making some changes. We are going to be talking about the second option. Of course, if you want a very good excuse, you already have the one from Philip II. I didn't send my company to fight against AI or this environment. But let's take a look about what is really being done outside today. What should worry me? What are others already doing with artificial intelligence? And there are a lot of fields that have real results today. One of the first ones can be personal life recommendations. I'm sure you are aware of this. This is pretty much the first field where artificial intelligence explodes. And it's something that really produces results. We are all aware that personalization works. 70% of customers prefer personalized shopping, cross-selling works. It can rise sales by 20%, profits by 30%. And we have also this canned laughter effect that I don't know if you know. Probably you all have watched a comic TV. And then you start hearing some laughter. And the minute you start hearing the laughter, you tend to laugh. You cannot stop yourself. You laugh even before knowing what you're laughing at. This is social anxiety.  So this is the things that are achieved with artificial intelligence in this arena. And this is something that has been done for years now. It's not something even from the present. It's something already in the past. I don't know if you are aware with this fact, some retailer many years ago, it's not even know the retailer, made an analysis, an automatic system that was going to cross-check every pattern of people buying products and come up with proposals of what products placed together in the shelves to rise up cross-selling. The system told a lot of things and one of them was put the beer besides diapers. And nobody understood why. They thought it was a myth from the data analytics system, but they did it and they checked that cells in both beers and diapers came up. And it was only later when they realized that what was happening was that first time parents went to the store to buy diapers and when they saw the diapers and the beer, they remember how two weeks ago they would be having beers with their friends and now they can't. So they would buy the six pack of beers to have the beer at home. So this is an example of something that is not intuitive or maybe even counterintuitive to humans, but machines are doing much better and boosting cells of those products. Same thing with this example of Target, also very well known and again, not of today. This was years ago. This result has already been achieved years ago. They did more or less the same thing. They set up an automatic system that was going to try to guess based on patterns of behavior of the users, what profile did they match? If they were first time parents, if they were divorces, or if they were people who had just bought a house and depending of this profiling, automatically the system would address them with specific offers of coupons. And then one day a parent called the company to Target to complain because his daughter was receiving coupons of first born produce. He said, okay, are you trying to get my daughter pregnant? She has, she's not even 18. So they investigated and at the end of the day, what happened was that the girl was pregnant and Target knew about that before her own family, which is exactly what can be done right now with artificial intelligence. So if we jump ahead to today, what are we seeing today in the field of recommendation and personalization? Probably one of the leaders is Netflix. Netflix is right now generating one billion revenue because of recommendations based on artificial intelligence. So they have 75 million subscribers and every one of them receive a personalized experience, a personalized recommendation that is right now the reason why 80% of TV shows are watched in Netflix. This is very, very important because they have also tested that in this area of TV channels, you have only 90 seconds to convince the user of something that's interesting for them. If not, they are going to abandon the TV. So in those 90 seconds, they have to recommend something interesting for the user. And it's a very, very complex scenario because it's very counterintuitive. In fact, they handle the term that against intuition, I'm going to recommend this show against this other one. How this works? They have a complete tagging of every minute, of every show that they have in their catalog and tagging, complex tagging that has been done by people who have watched every minute of the shows and they have a very profound profiling of every user of Netflix. When they connect, what shows they see, if they see them in a binge watch episode or they see week by week, and then they combine everything to make decisions, decisions that are not easy. What show should they recommend to a guy that connected yesterday? Something related of what he saw yesterday of what he saw one week before. So this is not something that humans can do. This is something that artificial intelligence is doing for Netflix and is doing this with this rate of success, one billion revenues for Netflix. Another example, we do stay in the field yet of personal life recommendation, but we moved to a food company. In this case, McDonald's, they launched an app APP to analyze customer behavior in some of the countries. This was, I think, in Netherlands, Japan, several others that covered 40 million end points. So this APP, mobile APP, received instant offers which were decided, depending on the behavior of the person and the weather where he was at. For example, if it's hot outside and I'm walking near a McDonald's store, I would receive an instant offer for a Sunday in that particular shop. So with this cross information and real-time offers, coupons, they got a result of 700% increasing redemption of these offers and a return to the stores twice and 47% of increasing expense. So you see that these are real results that are happening today have already happened. It's nothing of the future. More examples, Walmart, another retailer is storing every hour 2.5 petabytes which I'm a little lost of what is, but to give you an idea, it helped me to understand the magnitude of this number is more than everything that the humankind has written in his history. So you put together all the information in the books written in the history of humankind and it's still less than what Walmart is storing every hour. So they combine and analyze this information to anticipate customer needs, optimize operations and also even do facial recognition. They started with that as a kind of anti-theft mechanisms but now it's using it to measure, to gauge the frustration of their customers. So they can warn a customer representative about people getting frustrated because there are too many queues or whatever. So this again is something that is used today. But moving out of this field that may be more or less familiar with many of us, we will talk about real things that are being done today in other fields, not recommendations, personalization. For example, Netflix probably uses even more artificial intelligence to stream their contents than to personalize them because they have a huge problem and they need to serve content instantly, of course, to every one of the users and they need to do it from a lot of different content providers. So they have to select the correct one, the one that is going to work best for the user. And the behavior of the users is pretty bad known. I mean, you have there two examples of the throughput of a typical connection to Netflix. So Netflix needs to know what's going to be to your throughput in order to encode the content according to your capabilities but those capabilities look like that. So what to do, what they do is to analyze thousands and thousands of patterns of real throughputs correlated with devices, with locations, with times of the day to try to predict, to guess what's going to be your throughput. And based on that, they pre-encode the content that they are going to serve you. So they know better than you how your bandwidth is going to behave in the next second of minutes because they need to know that in order to encode the content accordingly. So again, a fantastic example of artificial intelligence in good use. More examples that we all know them but maybe not so well. We all know Amazon as one leader of artificial intelligence. We know about deep learning, about Amazon Go, that store where people don't have to check out because they are seen all the time. Amazon knows what they are doing and they are charged without more operations. We all know also about Amazon's recommendation algorithm. It drives, in fact, 30% of their total sales. And we probably know, I don't know if you know about this, the search by image functionality. In fact, it has been in the Amazon app for now some time but it's now integrated with the Snapchat and allows you to make photographs or videos or something that you are interested in and launch immediately to Amazon to buy it. These are pretty cool examples and really usable in fact, they are generating revenue but probably what is less known is the magic that is happening behind the scenes at Amazon Store. So we have there a completely automated process based on intelligent robots that are making a lot of decisions for Amazon from the time you click on the buy button. So from that point on, until you have the box at home, there is a complete race in order to serve you the package on the less time, the better. So what we have, we have an instant selection of the warehouse that is going to serve your order based on a lot of things. Of course, distance to your home but not only that, a stock, busyness of the clerks. If that warehouse is very busy, you may be redirected to other one that in that time has more clerks or they are less busy than the rest. They recognize defects automatically. So if the robot select a product and that product is defectuous, it will be returned to the store. You will not receive it at home and they are able with this system that we'll see in a minute to have 50% more inventory, 20% down in operating cost and 15 seconds to assemble one package. So at the end of the day, they click to ship, went down by 15 minutes, which is a lot. Take a look of how it works. Oh, we don't have sound. Well, this has captions at least. Well, I hope we get sound for the next one. But anyway, you have seen here how these robots, which are called Kiva robots. This was an acquisition from Amazon some years ago. Make all the decisions for the pickers. In fact, what is called the picker, which is the Amazon guy who stands there in the storage years ago, used to actually pick something, to move to the shelf and pick something. Now the robots are bringing stuff to them. So they pick the shortest route to the nearest clerk and they bring everything to them. And when the clerk receives the product, he also is receiving the correct box and the correct measure of tape to box it. So actually, the time that they spend handling the package is very, very small. So everything else is automated and it's not a matter of automation itself. The matter here is the intelligence that drives that automation so that the decisions that they take, these robots are the correct ones, are the more efficient ones in order to maximize the results. Do we see there how they are pushed into the correct tracks, the ones that are going to be closer to your home in order to complete the order in the less time possible. This is what all retailers now are competing with and that's why it's so hard to compete with this. By the time you take an Amazon delivery, by the time you have opened it, you have spent more time in contact with that package than the whole personnel of Amazon. So it's that efficient, okay? More examples, augmented emotional intelligence. We have heard a lot and we will keep hearing a lot about chatbots, which probably will be the next big thing in artificial intelligence, the possibility of really substituting customer care with expert systems, with automatic systems that talk to you and solve the problems to you. But the jury is still out if that's a reality or that's something for, let's say, next year. But I wanted to show you something that is a reality one now, which is what is called augmented emotional intelligence, which is the ability to help real people to make better decisions when they are serving the client. Let's see if this video can be heard, I guess not. Well, I will try to describe it for you when we see it. But the thing here is that when the customer representative is speaking with a client, in real time, there is an analysis of what is being said and an emotional context that is going to be displayed in order to get those advices that we are seeing on the radar, that you are speaking quickly, you are talking a lot, you are not generating enough empathy with your client, try another approach which you see there, empathy cues, and on the same time, we are analyzing everything that is being said. So these artificial intelligence systems are accompanying you when you are serving the client in order to give you real time tips about how to improve the experience of that particular client. So we are going to combine an analysis of what you are saying with an analysis of how you are saying it, and we are going to try to correct you, to improve your behavior for the next interaction with the client, and also to shift that call to a supervisor if we see that it's not being handled properly. So we have that option. Okay, let's see if we can recover the sound later. So more examples, shifting to different areas of applications that are really being used today. Fraud control, this is also a very big area for artificial intelligence and something that is really producing results, and very interesting results. One very good example would be PayPal which is processing, as you may know, $500 billion a year in payments, so for us, for them controlling fraud is a very big thing. What they do is each time that they detect fraudulent operation, they make a pattern of it, and they apply it, they train a model in order to avoid that globally that specific fraud is repeated anytime in the future. So right now they have thousands of those patterns that are compared in real time to each operation that you do. And I mean in real time, even before it happens, that's why I compare it to minority reports. You probably have seen that moving of the pre-crime thing that avoided crime even before it happened. So this is kind of the same. Artificial intelligence allows these kinds of banks and payment organizations to detect an anomaly, detect a pattern of something that is going to be fraudulent before it happens. So we can avoid it and not wait until it's too late. Right now in PayPal, they have spectacular results. They have gone down from 1.32% of fraud against revenue, which is the average in the sector, to 0.32%. So you see the advantage that they got from using this kind of artificial intelligence systems. In fact, I don't know if you know that they have acquired just some months ago a company, a specific company, for this artificial intelligence fighting about fraud, which is called Simility, for 120 million. So this is a niche, this is an area in which artificial intelligence is used, and is used in a very interesting way, in a very productive way. More examples, shifting from the personalization and recommendation wall, which is something that may be familiar to you, to more obscure areas in which probably you are not aware of how much is being done already. We have the energy and utilities areas. Here we are talking about forecasting energy for the big distributors, the capacity of predicting energy demand so that they can control the supply and optimize efficiency in order to serve the demands when something happens globally, in a city, in a center, whatever. To energy efficiency. Here the best example is Google DeepMind. Google DeepMind is a company that Google acquired a couple of years ago or more, that they specifically wanted to boost efficiency of the data centers, the cost of the energy used in their data centers. So this is an artificial intelligence system that analyzes everything in the machines, in the behavior of every component of the data center and starts patterns to boost efficiency. So they say, Google says that it reduced cost by 40% once the machine learning system was finished. You can see there an example of how when these data models once trained were put in production, the savings that they generated immediately compared with the previous energy waste. And then we have the energy accessibility front, which is kind of translating this, shifting this to the user, to the end user. So how can every one of us profit from the same level of artificial intelligence? So we can take a look at how these guys do, and we have to give you the pitch because we can hear the sound. But basically you put a device, just as you see, grabbing your electrical input and from the moment you plug in, it's going to sample your electrical input by millions of time a second, which is of course much more than whatever system not based in artificial intelligence can do. So with this information, this artificial intelligence system is going of course to give you a real time situation of how much you are spending but not only that, as you turn on and off the different device of your house, it's going to detect a pattern, the pattern of behavior of these devices and identify them so that you can recognize which one of your devices is the one making the waste and receive usually insights about when to plug on or off the different devices. And of course it also recognizes when one of them is not behaving properly. If the test failure before you even realize you have some problem there. So again, something has been done today. And manufacturing going farther from the user to the back and to the biggest companies, so to speak. We can talk about manufacturing in two of the biggest companies there, Siemens and General Analytics, which are doing pretty much the same. We see here the Siemens example, they launch MindSphere as a global system that monitor records and analyze everything in the supply chain from manufacturing, design delivery to find problems and to provide solutions even before humans know that there are problems involved. This means a huge insight, a huge assimilation of every data that is being generated and acting on it. This is so huge that the German government came up with the term industry 4.0 that probably you have heard of because of this, because of these advances. So we can again hear it, but let's take a look at what they do is basically to digitalize everything that is happening in every manufacturing site that they have so that they receive instantly data from all this particular system and gain insights about them. So the idea here, the holy grail of these systems is maintenance, is the possibility of finding out about a piece that is going to be grown in a matter of days or minutes because there is a huge spend of money in these kind of companies in regular maintenance. Having a guy that periodically goes once a year or once a month to an installation to check if everything is right. So if you can save that cost and instead get warning beforehand that this happens, you will stop downtime practically to zero and you will save thousands and thousands of years in this personal that has to go to those sites. Same thing or more or less the same thing is trying to do or is doing general electric with this, what they call the billion manufacturing suite that they deploy in their factories in order to build a whole intelligent system that links everything, design, engineering, delivery, distribution, everything is correlated, everything constitute a sentient being that is going to monitor everything that's happening. They deployed in the first factory that they deployed, it was in India, they improve efficiency 18% and they are processing now one terabit every day of this kind of data and doing this kind of the analysis. So again, something that is being used today. And to finalize, I wanted to show you another example to maybe take it out of the common path. This is something, it's a pity that we can hear it, but it's an example of artificial intelligence applied to agriculture. So this is an expert system that is going to recognize weeds or elements in a plantation that needs to be removed or treated in a special way. So what they did was have cameras in this kind of, I don't know the name of the truck, but they are going to be exploring everything that is on the ground and train it, train a model with what a weed looks like, what the different types of weeds look, which kind of safety area they need to live around each of these plants in order to put herbicide on them, et cetera, and once the model is trained, what they do is to launch these trucks on their own so they can apply herbicide more or less or apply good products to the good herbs and they are saying here that they reduce by 10 the personnel that they need to take care of these cotton plantations, which is what we are seeing here. So again, it's something very creative and that's why I'm showing it to you. It's a creative use of artificial intelligence in an industry or in an area that probably you would have thought that has nothing to do with technology, with artificial intelligence or with this big data. We train models of recognizing different types of herbs and from that point on, we are going to save products, to save personnel, and to boost productivity enormously. So since we can't hear that, I will not dig deeper in those videos, but we will talk about what to do to be one of these. So I hope I can have you have convinced that there are real big, big results of artificial intelligence being used today, not tomorrow, and even with that, most of you will live here tomorrow, probably with one of two syndromes that are very common. So let's see if you recognize this yourself in any of these syndromes. First of all, this is very good, Amazon does it very good, Google, Netflix, but I'm not one of them. I'm in fact fed of hearing about Amazon, about Netflix, about artificial intelligence.  I'm fed of this. It does not work for me. So this is the first syndrome. And it's really something that you should be happy about because if you saw here today and tomorrow use cases that apply to your company, then it would be already too late for you because at the end, when this goes to the maturity, either you are different or you are cheaper.  We are probably halfway through this circle. So at the beginning it's very difficult to stand out but you have less competition in the market. Halfway through it is still very difficult to stand out or more difficult, this is the effect of nothing that I see really solves my particular problem but you start having more competitors that are solving those problems. And by the time that you come here to be at Spain and say, okay, that's the solution to my problem, you will be in the saturation phase when the thing you see will be in everybody's system. So you cannot differentiate with that. It will only be a matter of being cheaper than the other ones, which is something that we don't want. If you see the image behind the graphic, it's a commercial from BMW, which they realized this a lot of years ago and they shifted tracks in order to not sell their cars because their cars were at the end of the day the same product than the other manufacturers and shift to an emotional message, which is something where they could differentiate with the competition. So this is an example of shifting tracks in order to be different, okay? Second syndrome, if it works, don't change it, right? So why should I change things that are working perfectly in my company and have been working for years? So this is the Blackberry syndrome, blockbuster, AOL, all those guys thought that are at a particular time. But I'm guessing that you are still thinking, okay, but this is the plain crash effect. That's not going to happen to me. This only happened to these guys because they were unlucky. But see if you recognize yourself in this story that this is something that is shown in many MBAs. The problem of not questioning your plan. At the time, the Space Shuttle, the American Space Shuttle was the most advanced vehicle in the world. But it lacked because of the effects in the design that were due to the original design of Roman chariots, Roman word chariots 2000 years before. Why? Because those propellers that you see needed to be transported from the factory which was in Utah to Cape Canaveral to the lounge site. And they had to be transported through these tunnels that have had a particular width. And you may think, okay, somebody will have designed those tunnels with the intelligence to know what's the proper width. But no, the width came from the width of the rail tracks which was a very weird number, four feet and eight and a half inches. Why? Because they simply used the plans of the English immigrants that came to America hundreds of years before. And these guys simply reuse the plans of the tram tracks that were used years and years before. The tram guys reuse the plan of the tram wheels, the wheel axis that were again reused from the plans of the horse wagons which went hundreds of years before. Why the horse wagons had this special width? Because they had to go through English roads that had routes, had routes made by the Roman word chariots hundreds of years before which are the only ones that in 2000 years put intelligence in that width, four feet and eight and a half inches. It's the width of two Roman horses side by side. So you can actually say that the space shuttle was designed like this, like this of two war Roman horses specifically. And still it works. So you may think why it's grown, it works. It was in fact the most advanced vehicle in the world but it could be better. That's the thing, we are in a space when we do not think it's to work. We need them to be the best in order to compete because the market allows us to be the best and we have to fight for that. Okay, so at the end of the day, you need to innovate. You need to put everything that is circulating here, these new things that everybody else is doing to put, you need to put them to good use in your business, in your organization. And before this, you need an innovation framework. Something that is not okay, I'm going in the next break before the next talk, I'm going to think how I can use artificial intelligence in my business. No, you need to have a mechanism in track in your company to create, test, scale, and renew your ideas. You need to have a thesis about innovation. You need to start from your particular vision about how your business is going to go in the next years and what's my innovation strategy for the next years because I need to have a goal, I need to have a horizon in order to go there. And then I have to deploy an innovation funnel, a mechanism running all the time that gets me from idea generation, which is the hardest part of all, to testing those ideas, scale them, and finally, if they work, adding them to the core. And you will notice that I have not talked about technology. Innovation, you could say that has nothing to do, in fact, with technology. You have to have ideas first, and then comes technology. So you have also to keep track of how good you are doing with your plan. I mean, to have these families good, but you need to measure every quarter, every year, if you are producing results, if really your investment match these adjacent of transformational products that are going to reinvent your business because innovation is not incremental, it's revolutionary.  You see the kind of changes that these guys that I showed you are doing in their business. Do you need to come up with something that is comparable to those kind of changes? Okay. If you are questioning how far am I from this scenario, you can take this little quiz. You don't have to do it in public and raise your hands. Don't be embarrassed, but you ask yourself these questions. How is your focus? You focus on cost reduction, or you focus on operational efficiency, or you focus on exploring new opportunities and markets. What's your budget, annual, departmental, or is based on products, like the venture capitalists do? Your processes are linear, are pre-planned, or are iterative, experimental? And the hardest of all the question, in your company, what's the culture about failure? It's prohibited, is something bad, or is something that is assumed as necessary? So these are the questions that you should be making yourself to see how are you close enough to the innovation. Okay. So how to get there? If you fail the test, tips that can help you to pass it next time, from our experience, helping clients to get there. First of all, add digital agitators to the mix. You cannot pretend to know about everything. You have your business, you have your experts in your business, and there are people who are focused exactly in this, in having the experience, the skills to have these ideas and to really revolutionize, reinvent your business. So have some of them in your team. First, second, start thinking from inside, from outside instead of inside out. What I mean with this, many companies have grown so complex, so tangled inside, that they start translating their complexity to the user, to the end user. For example, there are retailers that have food and non-food organizations, because internally, the logics are different, the personal is different, but for the end user who is making an order, there is really no difference. So you are really translating with this complexity something that is only your problem to the user. So you should start thinking the other way around what the user needs for me and how should I be organized to comply with those needs. Use co-creation dynamics. The reality is that most of you, all of you have the knowledge to be different, to be unique. That knowledge is only in you, but it's usually hidden. You need to encourage the creativity of the people that needs to come up with this revolution idea. And this is something that is already invented.  So do this. Get your team together and this is something that may be a challenge. Probably in a big company, in a company that has been going on for decades, your super heroes, your IT, your management, your business people are there, but are straight to different locations. They don't talk to themselves anymore and it's difficult to get them together. I compare this to the scenario of the Blues Brothers. I don't know how old am I and how many of you know about the Blues Brothers movie, but this was a movie where these two guys belong to an old band, an old Blues band, and they were going after every member of the band, saying we are on a mission from God, we are putting the band together. So that's something that you must do in order to get your heroes back together because normally they will be far away in your company and they need to be close and working together. So get your team together and be very, very fast.  So you need to promote failure and it's something that may seem counter-intuitive in many organizations, but it's the only way to come up with the velocity that these other guys have. Amazon, Google, every example that we saw before have engineers testing idea thousands of times a day, thousands of tests to see which one works. So you need to be very, very fast to move on part with them and have your own ideas working. If you are not embarrassed by your first version of your product, by your first release, you've launched too late. This is what the LinkedIn co-founder said and it's something that we push again and again to our clients.  You need to shorten your cycles. And finally, and that's my last tip, be brave. I mean, this is a tremendous era for all that we are here. We are privileged. We are being witnesses of the first IT revolution in 30 years. We have not seen anything like that, like what we are seeing now, like artificial intelligence, since probably the internet. So we are in a position to do something, but it must be something revolutionary, not incremental. You have to think how to grow wheels and get out there and do things that are really revolutionary. Coming back to the beginning, I would say that you have to auction and choose the right one. Don't get out here today saying, okay, that's all very good, but in my case, I have a lot of problems. This can't be done. My boss is not going to allow it. The technology is not ready. Do you know what? Let's wait for one year. That's making excuses. So stop making excuses and start making history in your company. You have the chance. So take it. Thank you. It's the time for the question. Okay. Any question? I have one. Yeah, why didn't they all your sound? I have one. If no one have one, I can ask you. Okay. Would you prefer? Let them or I start. No, no, let them see if there is something. I can see it. So it's complicated. Go ahead. You say that innovation is not about technology. I like that part, but not have a whole track about technology here at BDS. Isn't technology a very big part of this? Of course it's a very big part of this. And that's why Big Data Spain has a technology track. But I would say again that that's not the problem of most companies in order to be competitive, in order to come up with these ideas. Technology is there for us. We don't have to launch into these technology proof of concepts without thinking why we are doing it. Because it's there for us. The problem that we have is a business problem. How I am going to use that technology in order to be different, in order to have a product that is ten times better than what my competitors have. So once I have that question answered, then I can go to technology. But I can assure you that you are not going to have a problem in the technology side. That's why it's true that I did not mention technology almost in any time because it's not the important key here. We're going to be out of time. So there is no time for more questions. If you have more questions, you can ask him. Right now we have ten minute break.  Because our next guest, she came from the stock home. She's going to talk about the privacy, the policy. I'm in his company in Spotify and he's a really sweet guy, girl in this case. So I hope you soon in ten minutes. So be back. Thank you. Thanks to you. Thanks.


In this video I'm going to talk about solving linear equations. This is going to talk about identities and contradictions. So sometimes when we solve these equations some weird things happen and I'll show you kind of what those weird things mean. Alright, so here we go. I have an example of solving an equation.  Now this looks like a problem where I have, I got variables on both sides, I got variables on the left, I got v's on the left and a v on the right. So what I want to do is, okay I just want to solve it so I want to get all the v's to one side. Alright, so I'm going to start solving this. First thing on the left I see that I got v's here so I'm going to collect them together. Positive three, negative four makes a negative one v. Notice I don't put the one there, I just leave this negative v. Now the one is kind of redundant. Alright and on the right side I'm going to distribute that negative. This makes negative five minus v. Okay. Alright, now just like normal what I'm going to do is I'm going to make the decision, do I have my variables on the left or on the right? Let's just choose left. So what I want to do is I want to move all my variables to the left side. This one's on the left, I've got to move this one to the left side. So a negative v, I've got to add v to both sides, add v to both sides. Okay, so now what happens is that's zero, that's okay. So this equals negative five. But then this happens here.  And that's what's weird. I mentioned at the beginning of this video, sometimes weird things happen. And in this case, what happened is that the variables went away. What does that mean? Well in this case what that means is that, well we have two things that could mean it is either an identity or a contradiction, which one is it? Well look at what we just have here. Look at the bottom of what we've just solved. Negative nine is equal to negative five. Negative nine is equal to negative five. That is never true. This here is never, never true. Negative nine is never going to be equal to negative five. Those are two very, very different numbers. So that's never going to be true. So as you're solving these equations, if you get to something weird like this, you can actually use this weirdness to kind of evaluate what this is. If this is never true, this is what we call a contradiction. If this is never true, this is what we call a contradiction. So basically what this means is that there is no number. So here's a V, here's a V, here's a V. There is no single number that we can plug in to each one of these variables and get the same thing on the left side and on the right side. So basically means that no, that the variable is not equal to any number that we can find. So that's what a contradiction is. If you find something that's never true, it's a contradiction, which means we can't, there is no answer to it. Okay, so let's do another one. Let's do another example. 2 times the quantity x minus 6 equals negative 5x minus 12 plus 7x. There we go. Alrighty, so looking at this one, again, I'm going to solve this just like normal. And again, looking at this, it looks like I got variables on the left side, variables on the right side. So it looks like one of those type of problems. Again, I'm going to treat this like normal. I'm just going to start gathering things together that are alike. And I'm going to move the variable to where I deem necessary. So anyway, here we go. Alright, so I'm going to take the 2 and distribute it. So this is 2x minus 12 equals, alright, so negative 5x and a 7x. That makes 2x minus 12. Okay, now if you start looking at this, look at the left side and look at the right side. Back up a little bit, look at the left side and look at the right side. It's the exact same thing on the left and on the right side. Okay, so this is what we call an identity. And this is what we call an identity. If you see that everything on the left side and everything on the right side is happens to be the same, this is what we call an identity. What it means is that actually any variable is going to work. Anything is going to work. I can plug in the number 5. So if I put a 5 here, 2 times 5 is 10, 10 minus 12 is negative 2. 2 times 5 is 10, 10 minus 12 is negative 2. Negative 2, negative 2, it works. I can plug in whatever number I want to and it's always going to work. Okay, that's kind of the definition of identity. Alright, now the thing is, is not all students are going to see this right away. Okay, when you start solving it, you're just going to want to keep solving and keep solving. Alright, so if you want to keep solving, I'm just going to go through the normal process. So I have everything gathered, so now I want to decide, alright, let's get all the variables on the left side. That's seriously what students like to do. So let's subtract 2x, take this x and move it over to the other side. So subtract 2x, subtract 2x and what happens is all the x's go away. So now this kind of, this looks like a contradiction, but if you look at the very last, if you look at the very last line here, we have negative 12 is equal to negative 12. Negative 12 is equal to negative 12, which is actually very different from our first example. In this case, negative 12 is always equal to negative 12. This always happens. Negative 12 and negative 12 are the same number. Okay, so we can see the difference between the contradiction last time and the identity this time. Always true, that makes it an identity. And again, definition of identity is every number is going to work. What we also say in math land is that all real numbers are solutions. All real numbers are solutions. So again, you can plug in whatever you want to and you're going to get the same thing on the left side and on the right side. Okay, so that's how you find identities. That's how you find contradictions. And there's a couple of examples of both of them. It basically comes down to what you see at the very end. At the very end, is it always true? Then it's an identity. If it was never true, like our first example, if it's never true, then it's a contradiction.


Mayor Benjamin, members of council, newly elected member of council, city manager, members of the staff, and friends. I want to thank all of you for the recent election. And I see many of you in the audience today that participated vitally in that election. And it means a lot to me to be able to continue to serve. It has been my great honor to have served the last four years on the Columbia City Council. I have worked in municipal government all of my adult life on either the elected side or the administrative side. I have worked with and taught both municipal elected officials and the fine appointed employees who make us elected officials look good. In the last four years, I've gotten to know many of our staff and the great employees of the city of Columbia. I can tell the citizens of the city of Columbia that we have a great staff that is as good or better than any municipal employees in the state of South Carolina. Our city manager has hired the brightest and the best. And they work hard to make our city worthy of being called the capital of the state of South Carolina, as the mayor just mentioned. I look forward to being with all of you during the next four years. And as the mayor said, here am I, send me. And remember, we are Columbia.


I'm going to start from going way back in December when I talked about optimistic provide, which is addressing a problem that there is in IPFS that the DHT provide process is very slow. So you can see here the delay that it take the latency that we have that we see when we try to provide something so simplistically this means when we someone wants to publish something to the DHT. This takes quite a long time because we need to find the right peers the peers that are going to be more most easily findable later on. So what we also find out found out through some measurements is that okay it takes so long to go and find the appropriate peers and finalize the process but at the same time we figured out that actually if you go back and check after all this time that 10 or 50 or 100 seconds that we took, you know, to find those 20, which is the right number, peers that the provider record should go to, we actually have found those within the first second. And then the process was just hanging and trying to find even even closer peers. And yeah, and this is the figure that shows that it's mostly less than 0.5 seconds, but it could go up to a second or a second or two. So we thought okay there must be a way to try and find those peers and finalize the process much faster. That's why it's called the, well, some of the proposed solutions are called optimistic provide, and there were two approaches that were proposed one is called the estimator based approach and I'm not going to go into that today. The other one was the double query approach. So what we do there is that instead of going and finding, you know, asking around which is the closest peer to the one that I want to find according to the CD of the content I want to publish in the network, and trying to get as close as possible. Let's try to ask two guys at the same time. And that was actually the third idea and the thinking behind that behind that was that, you know, when we independently ask to completely relevant peers, you know, what is the closer beer that you know, for the CD, when we start getting common answers from peers that are coming back to us then we're probably have, you know, the, those nodes are common between both queries are probably the ones that are getting the closest ones because you know we're converging to that hash space. So we went on and the update here is that we implemented that, and we have some very initial results which I wanted to share with you today. And it seems that unfortunately, the results are not very accurate. So it's not necessarily a positive result that I'm presenting here today is just progress update and what we plan to do next. So if you go and check what happens when you go and ask peers one by one, like the single query approach, you see that you go in this graph the X axis is the normalized X or distance which very simplistically means what is the distance between where I want to reach, and what I have actually, which beers I have actually found to store the record.  So it means that this process is very, very slow but very efficient at the same time, because it goes as close as possible. So going and checking the double query approach, we see that it's not bringing very accurate results. So that 0.0 something 0.02 that we've we're seeing with a single query approach now it can go up to 10 and 20 and 30%. It's still, it's completing faster. And we can see that more than 60% of peers are finding indeed, you know, those final peers very quickly, but these does not, these does not continue for the entire process for all of the provide operations that we have tested with. So what does this lead us to think it leads us to think that we need to perhaps play around with this and have perhaps not two queries but maybe even do three queries and try to see what is the intersection of answers that we're getting any, you know, if we can convert faster when three separate queries bring us back the correct results. It means that we need to also investigate other approaches such as the estimator approach that, yeah, I didn't talk about it today but I'm going to talk about it in a future session. Yeah, and also ideas that you might have so if you know if you can think of something that, you know, an estimation approach which is going to give back results much faster. We're more than happy to receive feedback and more ideas you can find here. I can share those slides. There is a proposal the discussion and the project page where we post updates and everything. So, yeah, that's me. Thank you very much. And yeah, thanks for listening. I mean, your screen was frozen the entire time so we didn't see the graphs. Could you really. Yeah, you should have said, sorry, people said in the chat but I guess like nobody wanted to interrupt. Could you say, could you send the links to the graphs and and links to the. Yeah, that's fine. And, and the implementation links just so we can look at the methodology. Yeah, absolutely, absolutely. Where's the place the best place to send out nowadays. I'm going to put in the chat, I guess, perhaps. Yeah, exactly, exactly.


stuff found. Rob has one and it's called Tune My Music. He says it's a website that takes playlists you've created on one streaming platform and moves them to your account in another. So if you were switching from, you know, Spotify to Apple Music or Title to whatever, you can absolutely just take your playlist with you. Very cool, Rob. Thanks for the, thanks for the note.


A Crow Wing County man has been charged with 10 felonies for allegedly possessing child pornography. According to authorities, 34-year-old Aaron Cecil Enlund of Crosby was charged on March 1st with 10 counts of possessing pornographic material. Enlund was charged after an investigation that was led by the BCA Internet Crimes Against Children Task Force and the Crow Wing County Sheriff's Office. According to the Crow Wing County Attorney's Office, the website Tumblr had reported 10 images and video files that were uploaded by a user account. Tumblr then provided the information about the user and the IP addresses to the BCA. A subpoena was sent to charter communications and the person using the IP addresses was determined to be Enlund. Authorities then executed a search warrant at Enlund's home where officers located a cell phone containing over 100 images of child pornography. Enlund is scheduled to appear in Crow Wing County District Court on March 18th. If you enjoyed this segment of Lakeland News, please consider making a tax-deductible contribution to Lakeland PBS.


In this video, we provide the solution to question number two for practice exam number four for math 1050 And we have to solve the exponential equation 9 raised to the negative x plus 15 power is equal to 27 to the x power Now we can try to solve this equation using logarithms But it's much easier to observe that the bases in play here 9 and 27 are both Powers of 3 so using some exponential laws we can make life a lot easier for us on the left hand side We have 3 squared because that's 9 to the negative x plus 15 And so as you have an exponent now raised to an exponent We can multiply them together and the left hand side becomes 3 to the negative 2x plus 30 power Similarly on the right hand side 27 is the same thing as 3 cubed you raise this to the x so multiplying the exponents together We get 3 to the x power So now we have 3 to the negative 2x plus 30 power and that's equal to 3 to the 3x power Since the bases are now the same we can cancel out the base and thus get the linear equation negative 2x plus 30 is Equal to 3x I'm going to add 2x to both sides This gives me 30 is equal to 5x and then I'm going to divide both sides by 5 Thus giving me x equals 30 over 5 aka 6 And therefore we see the correct answer is then D


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Hey everyone, welcome to figure fantasies over here to discuss Tia's build What you know what pieces should be with her especially when building your 10 month team? Okay, um, she has a lot of buffs towards teammates with the same brand Sorry for that. We will go to that in a while. So first we will have to take a look at Tia's Skills, okay, so Tia definitely is a defender So she although she has good damage to boot so Again going back to her basic attacks or attacks the first enemy again very basic Bonuses of up to 50% from basic attack when you have leveled it up then her ultimate Let's go through her ultimate. Some of you guys might be might be wondering why her initial energy is at zero So there's a reason for that. She's gonna be generating energy With every With every ultimate that her teammate does so if you surround her with teammates that can Can you know let out their their their ultimates faster Then she will generate more energy and faster as well. Okay, so let's go over her ultimate attacks the current target And deals a great amount of damage and energy regeneration is Zero as well upgrade effect boost ultimate damage by 36% Reduces the next damage taken for all allied figures by 50% as a starter battle and when unleashing the ultimate So she has a very good What they call this she has a very good kind of buff Because she loses damage of all her allied figures take note of that all allied figures It doesn't necessarily have to be 10 ma But it's all allied figures level 3 is there is a 50% chance to boost She is ultimate power by 30% after any allied 10 ma figure unleashes their ultimate so Level 3 only kicks in if it's Allah. It's an allied 10 ma figure This effects tax up up to three times and is cleared after tea unleashes her ultimate So there are a lot of damage going on here There are a lot of buffs as well and take note Tia herself cannot restore energy But can receive energy recovery bonuses. So this is where Zephyr comes in Okay, let's go to her passive guys Reason for fighting at the start of the battle Tia enters enhanced form After an ally unleashes their ultimate and all okay So this is where Zephyr comes in gives her energy and also this is where Empress comes in because Empress unleashes her ultimate as quick as it can be So they are actually the perfect trio to be together. So Zephyr Empress and Tia So Tia will be healed and gain 25 energy So this is where all the magic happens in terms of energy gains over every other teammate that has That is Unleashing their their their ultimate she gains 50 energy while her damage reduction is increased By 16 percent for five seconds, which can be stacked up to 14 times. So 16 times 4 That's roughly that's roughly 64 percent damage reduction again So upgrade effect crowd control immunity boost healing effect by 28 percent Gains two stacks of damage reduction at the start of the battle Okay, so a lot of you know a lot of things going on in her kit controlled The definition of controlled immunity crowd control immunity is she has immunity to frozen stun knock knock up and Locked so a lot going on in her kit and the last one is her Special which is hidden command. So this is the usual has a 25 percent chance of reducing damage taken by 50 percent when attacked So that is it and the rest level to boost crit chance and defense by 10 and blah blah blah, you know the rest okay, so we're off to Tia's parts, so let's see how we're gonna be building her There are two versions of Tia that we're going to try to build so let's move to her parts here Okay, so So far you can build Tia two ways Either you equip her with life steal or ultimate set the reason why I'm doing life steal because I want to make her so so irritatingly Irritatingly sturdy or resistant that I want to incorporate damage reduction life steal and everything that is my goal here, but if you guys want to Improve her damage output. You can actually use ultimate set. So four-piece ultimate set then the two-piece defense set stays It doesn't move away. So you only interchange Life steal with your ultimate set. Okay, so anyway Those two are your choices in terms of parts. Let's go to the badge I opted for this one as well. So different. It's a defenders exclusives or eternal valor badge So boost block rate by 10% also restores 3% of missing health every second when health is below 50 Percent, I know it's an overkill, but again my point here is to keep her You know keep her from dying and probably bring her to up to near nearly indestructible She has a lot. She has good buffs going around to her teammates So it's good to make sure that she's around the other options for the badge Let me just go over Gallery so Not this one this one is Also good. So when it start bad This is your eternal bursting badge when the battle starts grants a shield to all your melee figures that absorbs damage equal to 21% of the wearer's max health. This is also good This one Recover for energy when the passive electric current strike is triggered. So this one is good because it also Generates her energy So again, all of these Defender based badges are good So you can actually try them out and mix and match for now I'm gonna use this one the eternal valor badge because that is the only Badge that I have that I can I think give to her at this point. So for the other things I Don't know if Probably if you want to add more lifesteal, but it's going to be overkill I would I would recommend that three exclusive defender badges for the violet color Not sure these are centered towards damage I don't know if anything fits her here or fits her kit But definitely for the three defender badges eternal valor badge Eternal bursting badge or the eternal twilight badge These are the only three that I'm recommending on her the rest I'm not sure if it's going to be compatible with her kit again I don't see, you know, I don't see any compatibility Based on the purple badges that we have so that is my recommendation for the badge let's go back to see you here and Is if you guys have noticed I already if you guys watched my summoning video And if you remember I only got to you up to five stars now It's ready. That's right. I in that video in the summoning video. I only got her up to four eight to three now she's at five did some pulls after and Kind of had better luck after that video. So she's at five star at this point I also included her a A a adornment the adornment is available in the adornment store So it's most or marble store in the adornment store. So it's gonna be here It's actually this one. I bought it already for it's actually here. This is a good deal. So Look at this is a sure shot of getting her adornment While, you know, you are waiting for a better one So but this one this adornment is going to be good as well. This is going to give your team buffs Let's go back and So this one in ancestry is ultimate boost the ultimate power of all Allied figures of the same brand by sixteen percent after unleashing the ultimate While taking effect for Tia immediately this effect cannot be stacked. So it's a sixteen percent buff on all Take note on all Ultimates of all figures. That's actually good. So Moving on to team composition guys So for the team, let's go to brand Okay, I mentioned earlier that She's compatible with Zephyr, of course Zephyr gives energy So she should have a battery wherein she could get some energy and also she is compatible very much with Empress Empress as she kicks in her ultimate Then the passive of Tia also triggers that is why you need Empress in that team as well It would be a very very sick team. I tell you so The other two the other one that I mentioned is Mikoto because again Mikoto could benefit from the buff that Tia is giving and also her twin Koroko so Koroko can benefit as well from the buff that Tia can give so those five They're gonna wreck havoc if you bring your your you know your This team to the floor. I'm sure that You're gonna be using you could use it in some of the 10 my exclusive stages if you can't use Koroko Koroko in that lineup I Could probably recommend another Another Vanguard to replace probably Rin could be good as a Replacement For a 10 my exclusive team that that is what I mean So that is the team that I think could you know could benefit from Tia in some of the content and Please do build her with a good 10 my team because again 10 ma has more benefits When you pair them with her, okay guys, so my final thoughts for Tia Interesting kit. I know why people like her so much the the artwork for the base and the sculpture of the figure itself is Nice, so the outfit is provocative and What more could I say anyway? Hands down, I think she's going to be the best defender for 10 ma you're gonna be For going cruises at this point. I don't think cruises will be your primary defender anymore for for 10 ma so Although you could bring them together, but she Tia will will be your mainstay. She will as soon as I get her to three Five diamonds. She's gonna be unstoppable. So again build her well guys Either ultimate set or lifesteal set, whichever you prefer You prefer her to be tanky then build her with a lifesteal set If you prefer her to have more damage then build her with an ultimate set So that is it guys. Thank you very much for staying this far. Take care. Stay safe. This is the warden and I'm out of here


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