 So, first of all, thank you. After Jorge's presentation, it's difficult to do anything because I am not going to do any magician trick. I'm not able. You will teach me someday, please. So I am going to try to explain and to talk about AI. But we are seeing because AI is a buzzword. So everybody is talking about AI. We are talking in this event about AI in your company. You are talking about AI. I am shooting your house from time to time. You are talking about AI. But what are the companies really doing with AI? Most of the companies, in reality, are doing chatbots or something similar because this is something very normal. You are interacting with chatbots in your real life. So the company say, OK, I will create a chatbot. But is a chatbot real AI? This is one of the questions we are going to try to explain during this presentation. So the first thing about Stratio very fast. Stratio is a very young company. And just to explain how we are able to do the things we have done, how we are able to create real AI, we are a no company. We are very talented people doing exceptional things without procedures, hierarchies. So you have to change your culture and your organization to really do exceptional things. And also to get the most of the technology and AI, you also should change your organization and culture. In Stratio, this is maybe to the extreme, but this is the only way really to create exceptional things. So this is the type of company Stratio is, freedom and responsibility. We don't have any hierarchies. I am the CEO, but I am at the service of any Stratian. And this is one of the things I wanted to do in the presentation at the beginning, to thank everybody, all the attendees, you to be here, to thanks all the Stratians that makes this real AI, I am going to explain a reality. And to thanks our customers, our partners, and especially, and this is the reason today, to thank one of our partners, Telefonica. Telefonica, Chema Lonso will speak today, Chema and Elena in Elena Hill. They announced today a strategic partnership with Stratio to help to reinvent companies and to transfer companies all around the world with Telefonica. So really, we want to thank our partners and Telefonica especially today. This is the question. Is your chatbot intelligent? We are going to see some examples. Siri, do you know anything about Star Wars? A fine question. Now can we get back to work? No. No or yes, your answer is no. Hey, Siri. Remind me to upload this video today in an hour. Sorry, Stetson. I can't remind you in the past. OK, I'll remind you to upload this video. When would you like to be reminded? I want to be reminded today in an hour. OK, I had a call to be reminded today in an hour to your reminders. That's not, no. Who's there? Doctor. Doctor who? Are you got me? I have one. Do you want to hear it? If you think you can do any better. Why did the boy throw the clock out of the window? Do you know what the Star Wars, Lego Star Wars? I suppose it's possible. That doesn't make any sense. Don't understand. That doesn't make any sound. Sent. I'm sorry. I'm afraid I can't do that. Alexa, are you connected to the CIA? No way. Can you talk to play with us? You want to hear a station for porn detected? Porn no ring, don't watch your amateur girl call in sexy. No, no, no, no. No. No. Alexa, stop. Alexa, I need medical assistance immediately. Added medical assistance immediately to your shopping list. Oh, fucking hell. So these are some examples. This is technology. And these are small companies doing this? No. They are Google, Apple, Amazon, Facebook. Is this the real AI we want? No. So are the chatbots you are going to build, or you are thinking to build, or you have built? The AI you need? No. So this is something I want to explain. Some, we have seen these examples, but normally a chatbot has just predefined rules. This is the reason it was not working even well. Because with predefined rules, you are not intelligent. Normally, chatbots do not have contests. What means they don't have contests? They are not able to adapt to customers, to situations, to time, to different type of people. They are not able to interact, really interact, not just a defined question, a predefined answer. Why? Because they don't have contests. You are building your chatbot just like another silo. Because you want a chatbot, you will build an application on top that will have the same problems you already have in all your applications. First thing, the chatbot will not have data consistency. Why? Because in your companies, you do not have data consistency. You have data replicated. And you also have data without meaning. With data and consistency and with data without meaning, you will get an interaction with a chatbot that is just funny, but it's not useful. So everybody is talking about AI, so super cool AI. It is really like something sexy. OK, to go to move really forward, to go to real AI, first thing you must do is to solve data governability. It's like the anti-cool, anti-sexy, anti-data governability, really boring. You must do it. Without data governability, your data has no meaning. Without data meaning, your chatbot, your AI, will have no context. And without context, your chatbot will be stupid. So these are the bad news. To move to AI, first thing, solve data governability. Keep meaning. This is the normal thing. Data governability, you need data dictionaries, business glossaries, data quality. With this, you can do semantic, you can do ontologies, and you can move to real AI. So sorry to explain something that is breaking this buzzword and this magic, but governability is a necessity. So chatbots, without data content, without real integration, we call it marketing AI. I don't know the English word, but in Spanish, we could say that chatbots, without real AI, without context, without meaning, are just AI from postureo. Just that. If you want to put a stamp in your company that says, hey, I'm using AI because your CEO, your president, has to flash off, OK, do it. Build an AI. But don't cheat to yourself. That is just marketing AI. That is not real AI. What is a chatbot in reality? A chatbot should only be the human interaction of the real AI of your company. So a chatbot is something that can talk, listen, and interact. But it's just like the channel representation of your real AI that is thinking, has the context, has the meaning, and can interact. So a chatbot is only like a personification of the AI that you should have in your core system, just to be very clear. How to create this real AI? So allow me to repeat myself again. Chatbot is only the human interaction. I wait for human interaction from the real AI that you should build. So how to build this real AI in your system? The AI foundation, in our opinion, is first, as I explained, data with meaning, knowledge, tools to create data intelligence models, because you need to train that AI. The AI that you will build will be a small kid, really very, very small kid, two years old, three years old. That is the technology, the core technology. You will create or adopt a small brain. Then you have to teach and evolve that brain, that kid. How can you teach it? Well, we go to school. We have teachers. We have books. Here in a company, you need tools to create data intelligence models to train that brain and to make it grow. Why is that so important? It is extremely important, because the AI technology, you could adopt that. But the real AI that you should build in your company, that one should belong to you. You adopt the brain. But how do you train the data, the people, the tools that you use to make that brain to grow? That depends upon you. And that AI, after several years, should be your AI. And that one is different to the one from Google, from Amazon, from Apple, and, of course, from your competitors. Why is this so important? Because if you have the same AI that your competitors, you are not adding any extra value, any differentiation, if you don't have anything that will differentiate your data intelligence or your AI from the competitors in the future, then you don't have any future. If there is nothing that will differentiate you from your competition, there is no future. So if AI is strategically important for your company, that, of course, we think it is, it should be your AI. Nobody else's AI, your AI. And then to train, to create that big brain after several years, you need tools to train, to teach. Then, also, you need senses and sensors, because that AI should learn with you any interaction with your customers, with your employees. That is an opportunity for that AI to grow. If your AI is not able to talk with the people that is working in your company, with your customers, and so on, it will not learn as fast as it is possible. You need stimulus for the AI. So senses and sensors. Normally, from these three, data with meaning. Most of you, you don't have data with meaning. Sorry, bad news. You should solve it. Tools to create data intelligence models. You have some advanced analytics. You are using some of those tools, maybe not the proper ones. Previous generation's tools, but it's OK. You are adding the Q-tool, the data-driving Q-tool. Senses and sensors. Empty. Normally, no companies have senses and sensors to interact. And then, the technology core to evolve. Something that is self-aware and is able to evolve by itself. You, we, the market, are really far from that. But we are building that. So I am going to try to explain with examples and of these things the concept for us about real AI to simplify or even to make things a little bit more complicated, although we think that we are simplifying, is this. We call it sentient AI. This is the real AI that right now, now in three, four, five, six years, we should be building. We should start building this now. Because in technology transformation, in exponential technological evolution, if you are too late, there is a non-return point that when you start at that point, it will be too late. So you should start creating this real AI, sentient AI, right now. What is, in our opinion, sentient AI? The first sense is because you have to, the AI should listen, talk, view, learning, because it has to evolve. Reasoning to think. It's the chatbots that we saw they were thinking, not really. They were like predefined. What is reasoning? If you have to train your AI for anything you want the AI to solve, that is not reasoning. That AI is human dependent. The AI should be as autonomous as possible. So this is reasoning. Awareness. Awareness, well, the concept is complex, even for human beings. But awareness is to know what's around at any moment. I am talking now, and my communication channel is really very, very narrow. It is normally 64 kilobytes. The view is a little bit more. But in reality, my awareness is huge. My awareness is huge because I am seeing all around, listening, smelling, a lot of details, although my focus is just in these 64 kilobytes that I am using now. But the awareness is huge. It's everything that is around you. So a sentient AI should have awareness to be conscious about anything that is around. But this is one of the best or biggest advantages or benefits of AI. AI is or should be omnipresent. We can only be here, in one place. Our AI could be and should be in any place at any moment, in all our meeting rooms, in any customer employee, employee, employee interaction, all around. So this omnipresence makes this awareness really, really huge. And the possibilities are limitless. To interact, it has to be able to interact because with interactions also we learned to have the knowledge and the last emotions. If the interaction, talking, listening, has no emotions, then that interaction has no empathy. Without empathy, the communication that an AI can have with people will always be really, really very, very, very bad, very low. In fact, sometimes when you meet someone that has no empathy, a psychopath, for example, hopefully you don't know any psychopath. But if you meet someone, they don't have empathy. So a psychopath could use a knife and put it in your eyes. And this is a very bad example. But anyway, he will not feel any feeling. He could do it without any problem. So communication with people without empathy is almost impossible. This is the same for AI interaction. If the chatbot, if the AI, real AI, has no emotions, then it has no empathy. That communication is not real. It's artificial, very artificial. So tools. These are some of the tools that companies normally using, data exploring, discovery, then pipelines, workflows, scientists, data engineers, environments with workbench, matching learning, deep learning, TensorFlow, all these tools. What is the problem with all these tools? Because as I explained, you don't have data meaning, sorry, or not a lot. Of course, you will have some. But this is not really well solved in your companies. And the tools, you have some of these tools, and you're using it. You have been using SAS, SPSS, those type of tools. But you should jump first to distributed data intelligence tools, tools that are able to process and to manage data in distributed clusters. Because to have real AI, you will need processing power. So any tool that you are using in a single computer, that is 20th century technology. That is not able to cope with the challenge. You should jump to distributed tools. And all these tools should be completely integrated to build that core AI. What you are doing right now is doing reporting, doing some statistics or risk scoring data intelligence models, doing some chatbots with deep learning, or doing some real time workflows. But that is not integrated. That will not build this core AI system. That will not train your AI. All those tools should work together with data repositories centralized, with data training centralized, to build and to help this small brain that you will adopt, to allow it to grow and to learn and to train and to become something which is real AI, Syntium AI. This is a more complex view of Syntium AI. But as you can see here, the mind, this small brain that you have here should have external sensors. Because you must receive inputs from the external world. It should have also action execution. So you should be able to do things, real things. When we talk about AI and real things, everybody is thinking about a robot, a smart robot or a stupid robot moving like that, but a robot. That is not execution. Of course, a robot with hands is executing things. But you don't have to go there. Robots with human form is something complex. Even walking is not well solved right now. Execution, when we are talking about execution, is execution in your companies. It's to do things, processes, operations, interactions with your customers, decisions. Allow, improve, recommend. That is execution. It's not just the robot doing or taking something and moving it. We will go there sometime, but that is really long. Then you have inside the mind awareness. As I explained, you need to sense sensors and all this. This is what we call a syntax AI. We are going to see some of these things in real examples. So AI interactions, senses, and sensors. Data meaning, maybe you have some, but not completely solved. Tools, you are using tools, but they are not integrated. They are not building. The tools you are using are not building this central brain or allowing it to grow. They are not helping to create your AI. And then AI interaction, senses and sensors. Senses and sensors are the way to interact with people. Your companies are full of people, the employees. We prefer to call them people, not employees, and customers. How to interact with that? Well, this is a real example that we created in our company because the only way to teach is by example. We created this. We call it the space AI. In the space AI, you have different rooms. The names of the rooms, some of them are very strange names, but you have meeting rooms. You have exploring land, all these type of rooms. What is the difference between this and your normal floor distribution and buildings? Everything in space AI is sensorized. So the AI is able to sense, listen. We have microphones. We have speakers. We have cameras all around. You are thinking cameras all around. Oh, my god. Well, that is not so bad. It is watching, but we are not recording. So everybody feels a little bit better. Anyway, if you want to interact with real AI, it should be able to see what's happening in your office, in your company. It should be able to talk, to listen. So in any of these rooms, it is able to sense because it has sensors. How many sensors do you have in your company, real cameras connected to a core AI, or speakers and microphones connected to the chatbot? Normally, not a lot of them or known at all. So what we created was this space, sensing. Then the AI is able to identify people. And this is quite normal, for example. Technology maturity. One of the best things to measure what is the technology maturity of your companies is the reception. When you go to any company in the reception, they will have several levels. If you have to fill a paper, what is the technology maturity of that company? Really low. Paper, a pen. If you have a form, something more digital, a little bit better. If they are making a picture of you when you are entering in the company, OK, third level. What is the AI level? No paper, no form, no picture. You go and you enter. Because the AI recognizes your face, knows your name, knows the agenda because it has context. It has the date of the company. Now you are going to visit that company. And in fact, we'll recognize you. And we'll call the people that you will have the meeting with to have the meeting. So no reception. Simplicity is the last generality. So AI with visual recognition should change anything in a company, anything, from the entry point to the inner core. Of course, if the AI does not know you, should call or ask your name and ask for someone to go and to identify you. So this AI is not something crazy. If it knows you, it will allow you to go. If not, it will do something. It should be able also to chat in a meeting room. If you are discussing something and you want to know how many TVs I sold yesterday, you should be able to ask your AI system. Because your AI system is in your meeting room and is interacting with you. And should have the real answer, the real data. Why? Because it has context. It has data meaning, data knowledge with consistent data. So if it says, yesterday we sold 1,025 TVs, that should be the real number. But you should be able to interact and to chat about almost anything. Any business or company related thing, it should have the knowledge, including any document. How many times you have lost time analyzing, reading different documents because you are looking for something and you don't know in which document that is? Several times. And we will lose a lot of time doing those things. With the real AI interacting, you should only ask. And in less than one second, we'll analyze 100,000 documents, identify the real one you are looking for, and it will show you. Show it to you. So this is real interaction. Listen, see, talk, but like any normal person with emotions, empathy. So we are going to see a video, a very simple one, in which the AI to move a game is, in fact, is the game that you can play outside in the Stratio Wood. So you can interact. And the AI is identifying the feeling. And if you are happy, it will move. If you are not happy, it will shoot, and so on. You can play with this. This is AI feeling recognition interaction when we finish. But we will see the video right now. So you played, some of you played this game yesterday. This is a real video. We recorded it yesterday. It is not something we did last week. So you can play it with this game. If you are smiling, you will move forward. If you are angry, you will shoot. This is pretty logical. But this is also a lesson. Because to go forward in life, you should smile more. So this is one of the points. Anyway, as you could see in the video, there are emotions in the people. And these emotions with a real AI system, very simple, just to play a silly game, makes the interaction real. So this is extremely important. AI chatbot should have a feel, see how you are feeling to really interact. Of course, in this space AI, where AI is real, this sentient AI with senses and sensors should know and knows what people are. So you are talking about someone. I am talking in a meeting about romance. Could explain this better. The real AI in our office will say, OK, Romani is taking a coffee right now in the lunchroom. Do you want me to call him? And it will help. So here the point is sentient AI that is able to sense, has sensors, is able to interact, learn concepts, is able also to execute. Sentient AI should be like a normal employee. The AI agent in your company should be a normal, natural, citizen, a normal employee and should interact with you at any moment. Why? Even if now it's really silly, because as I said, when you start, the brain will be very, very small. Three years old kid. Because interacting with that AI in those meetings, with those questions, with those employees and customers will help the AI to grow. So almost the kid is very silly. You should pay attention to that kid and should be in your company right now interacting with anyone. Execution is one of the very important things. For us, there is another normal mistake. The mistake is that normally we think about systems. Systems that have services, programs. This is not AI. This is software. Software applications. AI should have capabilities. The ability to manage resources by itself, because I can add more resources if I need more processing power, ability to access data, ability to transform data into knowledge, to plan, to interact, talk, see, to execute, and to evolve and improve itself. And here we go to the last point, awareness. Awareness, as I explained, is to be aware about what is around you, but in our opinion, this AI you should start building a small kid but that you should help to grow and to build more smart AI should have objectives. Without objectives, the AI will not have a purpose. So the strategic goals of the company should be very clear for this AI. And this is the final point for awareness. So as I said, chatbots, in our opinion, are good, because it is a way to start. But they are not real AI in the way they are built right now. Real AI in a company should be the core. And the chatbot is only the voice manifestation or the voice channel of that real AI that is built in your core system that has context, has knowledge, and is a sentient AI. So with this, we have tried to put some real samples. You can see and ask anything in our booth later, or to me in the speaker corner. But the point here is to do things, to execute, as I said. Start today. Don't start in six months. The people, the companies are analyzing best options, how to do it, try different things, but start working. And then first to know to do. And then those that understand to teach. As I said, to teach by sample. The only way to teach is by sample, become an example. This is what we are trying in Stratio, in our building, in our offices, with our people, with our systems, build this sentient AI, making it grow with our customers. And through this, show samples that will help others to follow the path. So thank you again.