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The Future of Finance 2016

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Documents from The Future of Financial Services 2016
1
T h e F u t u r e o f
F i n a n c e | 2 0 1 6
sponsored by
Index
2
Understanding Exponentials /p.4
Will Weisman. Executive Director, Conferences, Singularity University.
What Does M...
The Future of Finance
3
The Blockchain Panel /p.53
Bill Barhydt, Founder/CEO, Abra; Chairman, Boom Financial.
Realizing Th...
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The Future of Finance 2016

  1. 1. Documents from The Future of Financial Services 2016 1 T h e F u t u r e o f F i n a n c e | 2 0 1 6 sponsored by
  2. 2. Index 2 Understanding Exponentials /p.4 Will Weisman. Executive Director, Conferences, Singularity University. What Does Money Want /p.8 Bob Pisani, CNBC “On-Air Stocks” Editor. Machine Learning, AI and Big Data /p.12 Neil Jacobstein, AI & Robotics Co-Chair at SU, Former CEO of Teknowledge Corporation. Quantum Computing /p.17 Marcos López de Prado, Senior Managing Director, Guggenheim Partners. Energy and Smart Networks /p.21 Ramez Naam, Energy & Environmental Systems Faculty, Singularity University. Robotics /p.28 Rob Nail, Associate Founder & CEO, Singularity University. Uber Yourself Before You Get Kodaked /p.31 Rob Nail, Associate Founder & CEO, Singularity University. An Interview with Ray Kurzweil /p.37 Ray Kurzwei, Director of Engineering at Google, Co-founder & Chancellor of SU. Exponential Computing /p.41 Brad Templeton, Director, the EFF & Founder, ClariNet The Death of Products, When Everything Becomes a Service /p.45 Marco Annunziata, Chief Economist & Executive Director of Global Market Insight, General Electric Company. Business Decentralized /p.50 Brian Forde, Director of Digital Currency, MIT Media Lab. Index The Future of Finance
  3. 3. The Future of Finance 3 The Blockchain Panel /p.53 Bill Barhydt, Founder/CEO, Abra; Chairman, Boom Financial. Realizing The Value Of FinTech Panel /p.56 Amelia Dunlop, Principal, Deloitte Doblin. Investing the Uninvested /p.58 Jane Barratt, Founder & CEO, GoldBean. Future of Financial Services /p.60 Jesse McWaters, Project Lead, Disruptive Innovation in Financial Services, World Economic Forum. Becoming an Exponential Financial Services Organization /p.64 Salim Ismail, Global Ambassador, Singularity University Managing Exponential Risk, Rethinking Insurance /p.68 Daniel Schreiber, CEO & Co-Founder, Lemonade
  4. 4. Understanding Exponentials 4 Understanding Exponentials Will Weisman. Executive Director, Conferences, Singularity University. Will Weisman begin his speech by welcoming everyone to the third annual Exponential Finance. He also welcomes everyone to NY city, and states that the city has obviously played an incredibly important role in the history of the country, and in the history of financial services. Willthenproceedstoexpand on the history of Singularity University. The foundation’s mission is to educate, inspire and empower leaders to apply exponentially accelerating technologies to address the world’s largest problems. Will says you can think of them as part think tank, part educator and part new company accelerator. They focus on eight primary accelerating technologies, all areas that have crossed over to be information technologies and are growing exponentially, and obviously, they believe they are going to be the biggest drivers of disruption going forward. Will then states that it’s not just the technology individually, but it’s all about convergence. it’s how do these disparate technologies come together and then cause the creation of new products and services. Continuing on his speech, Will then explains why Singularity University is also about “Impact”, and names what they call global grand challenges, integrated by eleven areas that they have chosen to focus on. These are areas where they see some of the largest problems in the world and where they think technology can really have the biggest impact. ABOUT SU’S FOUNDING HISTORY: founded in 2008 Ray Kurzweil and Peter Diamandis came together at a TED conference, where they both started talking about exponential technologies, the changes that were happening, and that we were about to enter this period of rapid and transformative growth. They
  5. 5. The Future of Finance 5 eventually came together to talk about how they needed to create an organization where people, individuals, companies and governments could come to learn about these technology areas. Peter Diamandis is chairman of SU, and an executive chairman of the XPRIZE, of planetary resources, of human longevity and bold capital partners. Will then talks a little about abundance, and tells the audience that in the next few days of the conference they’ll hear a lot of talk about that theme, a way of looking at the world and thinking about it in terms of going from a scarcity mindset to really abundance mindset. Ray Kurzweil, the other part of the founding equation is a brilliant thinker. He is one of the most accurate Futurists and predictors that this world has ever known. Adventurer, entrepreneur and a director of engineering at Google. Will the proceeds to state several headlines that have been resonating in the last few days: 1. Clean energy jobs for the first- time surpassing oil jobs 2. The UK is thinking about a universal basic income 3. In May of this year Portugal ran their entire country off renewable energy for four years 4. Block chain based distributed autonomous organization that was just launched. Raised a hundred million dollars to invest in early-stage capital To really understand some of these things though you need to understand about Exponentials, and you need to understand about Ray’s laws of accelerating returns, according to Will. What does it mean when something is exponential? All basically means is that something is doubling in a finite period of time. We’ve heard of Moore’s Law is being one of the paradigms.
  6. 6. Understanding Exponentials 6 It’s a difficult concept for us to grasp. If you think about when our brains went through their major evolutionary changes, it was hundreds of thousands of years ago, in a very different world. The world was very much linear and it was very much local. The world was changing very slowly and we focused on just the things that were immediately around us. Fast forward to today this is very much a global and exponential world, so something happens on one side of the globe and we hear about it in minutes or seconds. Computers hear about it in milliseconds. One of the key things from this conference is hopefully to help you think about and understand exponential thinking so that you can start to look at problems and start to think about what the world might look like in the future using this exponential thinking. Will then proceeds to give examples of exponential behavior on current technologies, and talks about Ray’s law of accelerating returns. Will says that there have been examples since as early as 1890’s, and we all know each of these technologies have finite lifespan. What basically happens is in the earliest days things start off very slow, they reach a point where the growth becomes visible through rapid acceleration, and they reach some finite maxim. What’s interesting is that another technology that appears and so it’s a city series of these nested s-curves you can imagine it’s one technology basically sitting on the shoulders of another technology and together create that very smooth curve. Will says that in 20-30 years, he’s going to have a thousand-dollar computer that’s going to be as powerful as the human brain, and by 2050, he may have a thousand-dollar computer that’s going to be as powerful as all human brains for thousand dollars. Will then continues with examples to show how exponential growth has a affected us. Starting in 1956 five megabytes of storage cost you $120.000 dollars; fast forward to 2014 and 28 megabytes of storage costs you $99 dollars and fast forward to today 120 gigabytes now cost you $30 dollars on amazon. That’s a 3000x performance improvement and storage capabilities and 11 years and over 90 million since 1956. Will also mentions GPUs technology, as well as the impact in the advances of the optical camera has made through the years. “If you were lucky enough to be a successful company and make it to the S&P 500 back in the early nineteen twenties, you know you had a 67-year run […] the top of the heap today that’s down to 15 years and that’s shrinking dramatically. If you’re lucky enough to make it to the 500 list, that’s a very short life span. It’s predicted that forty percent of those companies might not even exist after 10 years so that were entering…” states Will, and continues: “One of my hopes from this conference is that you’re going to come out of here with a not being pessimistic not being feeling kind of beat down, but feeling like this is really an exciting time and what could be disrupted stress is really an incredible opportunity so part of that is embracing
  7. 7. The Future of Finance 7 this abundant mindset I mentioned” Will then mentions the framework they use that helps to understand the path of exponential technologies and abundance: 1. First, what happens is something becomes digitized, becomes an information technology. 2. Then it starts growing very slowly, it’s very deceptive, it doesn’t seem like much is happening. 3. Then all the sudden disruptive things start to happen. People are surprised, and all the sudden these new companies, new technologies are coming on that to potentially create stress and challenge them. 4. That’s when we start to see these companies’ products and services start to dematerialize and to monetize things moved to board to becoming almost or 100% free. 5. Then ultimately, we see them get democratize and readily available to everyone. Will completes the idea by showing statistics about how the world is becoming a safer place, and it’s according to him “the best time to be alive”, and adds the fact that we’re going to 3 billion new people coming online in the next few years, so almost a doubling of the number of brains that are out there that are harnessing the internet will be contributing to the solution of world’s problems creating companies. It’s really going to be an extraordinary time. All of a sudden, you’ll start to see lots of new customers for new companies. Will finishes his speech by thanking everyone who has attended, and encouraging everyone to seize the opportunity to be there. Para profundizar, recomendamos: VIDEO CHARLA https://www.youtube.com/ watch?v=2n6JO7KvHvM HERRAMIENTAS http://www.kurzweilai.net/the-law-of- accelerating-returns
  8. 8. What Does Money Want 8 What Does Money Want Bob Pisani, CNBC “On-Air Stocks” Editor. Bob Pisani starts his speech by saying how excited he is for living in times like these, and makes a special remark about Artificial Intelligence. A particularly profound moment occurred during the GO battle with Google’s Deepmind, the GO champion said that the machine made a move that did not make sense to him, that was not in any way comprehensible at all, and only later when the game was at its end did the player realize that and move was very profound that it threw him off, and that it was largely responsible for winning the game. Bob says he wanted to highlight where we are and maybe a little bit about where we’re going right now, commenting on the advances Fintech has had in the last few years. Regarding investment in private FinTech, 1.8 billion dollars in 2010, 19 billion dollars in 2015. Bob then says that what’s driving Fintech is very simple: maintaining control of the customer relationship, making customer experience as smooth and effortless as possible, and cost cutting, critical in a world of low growth, low rates and low profitability. Then Bob goes on talking about where is the Fintech money going: “Mobile money (money transfer, mobile banking), consumer lending (prosper, lending club), Small business lending (cabbage, circle up) and personal finance management (robo-advisors like Betterment or Wealthfront) We are now into this in tech revolution. It’s more difficult than a lot of people thought to build brands, build trust and build relationship with our customers. “The personal finance management area, it’s amazing what the potential is for them; we haven’t even scratched the surface in this…” Bob continues. The global mutual fund business is about 30 trillion dollars the global ETF industry is about 2.6 trillion in the US, and the Robo-advisors business is 20 billion dollars right now, “that under management and this
  9. 9. The Future of Finance 9 is less than one-tenth one percent of the current market, this just gives you an idea”. Peer-to-peer (p2p) lending: it’s small so far 2015. It’s only 7% of the cumulative lendingvolumesin2018.Anotherexampleis Alibaba, the largest e-commerce company, having more users than the population in all of US. Their Gross Merchandise Value is 500 billion dollars, “that’s the GDP of Norway right now”, says Bob, commenting on the characteristics Alipay brings to the Chinese Market. “Where’s the tipping point, where these technologies start to really dominate digital disruption?” We know what digital disruption has done to other businesses, you know what did the music’s sales and video rentals, but could this happen in FinTech where you get these massive disruptions? Well, the answer is yes, and the question is how do we know what’s happening? “There are very different ways of looking at this”, says Bob, “but one thing that I’ve noticed is once a technology starts to get somewhere in the mid-teens in terms of its penetration, when that happens in the digitally it accelerates very quickly because that’s enough for first early adopters, and then you get widespread discussion from people and it starts moving quicker from there. This happened in all these industries. That’s a tipping point.“ So, where’s the Banks “Uber moment”? (A shift for mobile distribution). Bob emphasizes on a specific area in banking industry: “I have been hearing for 20 years that the bank branches are going to go away, this was one of the earliest things you could say in 1996 to sound smart. Once teller machines came in everybody said nobody’s going to bank branches. You
  10. 10. What Does Money Want 10 know what happened actually? We have seen modest declines in bank branches, bank branches actually peaked in 2007. There’s been some modest decline since then. Now the question is will these new technologies, once you get the adoption a little heavier, will the bank branches started coming down? Citigroup estimated that if you started getting massive adoption bank branches could come down anywhere from twenty to fifty percent. Nobody really knows, but my thought is these banks are not going to let those branches go that easy. If they can cost justify them by turning their staff into advisory based roles where you come into the banks and they’re now selling you a whole suite of services that conclude not just mortgages but personal wealth management”. And then reinforces the idea: “For them to remain competitive, banks need to get innovation before the FinTech companies get scale”, quoting Citigroup, but makes clear that the banks are not rolling over. In the last few years the big banks have been working on the digital disruption area, and are not rolling over. The good news, according to Bob, is that disruptors are causing innovation inside the banks. “They’re going to buy a model as well, and you’re going to see some consolidation going on in this area”. BIG DATA: CHANGING THE WAY RISK IS PRICED. There’s now new methods of gathering data on consumers. Loyalty cards, social networks, purchase data or even browsing habits, and this eventually supports faster, more accurate decisions. “This is absolutely invaluable to a bank.” BLOCKCHAINS. How do I know I got something if it’s not in my hand? How do I know I sent that money to Thailand? How do I know that I truly sold that stock to somebody? How do I know I own that piece of real estate? Well we have an elaborate system in the stock market call clearing to tell that you did buy that stock, and we have elaborate system regarding real estate insurance mechanisms that says that guarantees transactions, but the blockchain can bypass all that. It is truly revolutionary. What’s coming according to Bob? 1. P2P, small businesses. 2. B2B will be the next wave. 3. Industrial Fintech, financial transactions incorporated into the IOT. Smart meters at home, that could even negotiate the rates of, for instance, energy. “Cross Fintech with the IOT, and you’ve got a lot of great potential”. Bob continues… “When I talk at CNBC, when we talk to people who are CEOs, who run companies in the United States they say regulation and compliance is a really big headache and increasingly they’re citing cybersecurity what there be some application to take big data and apply it to regulatory issues to find a better way to do regulation and compliance…” Bob then advances in his speech talking about possible negative outcomes (at least temporarily) for some of the disruptive
  11. 11. The Future of Finance 11 tendencies, understanding that there may be things that could go wrong in Fintech. “You are just moving money around, and when money moves around stuff can go wrong, models can collapse, stuff can get stolen”, and continues “remember, the FinTech business outside of the bank’s, is remarkably lightly regulated… and you’re going to see much more press pressure for regulatory scrutiny, and that could change things as well…” Bob then talks about what happened to Lending Club, just a couple months ago, the CEO abruptly resigned. There were debts that were misstated regarding its price, the CEO properly disclosed investment, and the buyers of the loans started to refuse, so Lending Club had funding problems, and the stock dropped almost 50% in a week. “There’s nothing completely revolutionary here, you’ve got people who want loans and then you’ve got people who want to buy the loans, if you don’t have somebody that wants to buy the loans you’ve got a funding problem here, so again nobody’s repealing the laws of gravity here”. Bob ends his speech by talking about the tech-pessimists, focusing on the country’s mood, and discouraging the pessimism that’s being seen around, and encouraging to believe in innovation. “I can’t help but to be excited about the future, people need to have more imagination, and the thought leaders have to do something to counteract the wave of pessimism...” Para profundizar, recomendamos: VIDEO CHARLA https://www.youtube.com/ watch?v=SyGQhzjxg7 HERRAMIENTAS https://deepmind.com/ http://icg.citi.com/icg/citi_research/index. jsp https://www.lendingclub.com/
  12. 12. Machine Learning, AI and Big Data 12 Machine Learning, AI and Big Data Neil Jacobstein, AI & Robotics Co-Chair at SU, Former CEO of Teknowledge Corporation. AI spent the first six decades of its history flying below the radar and now it has suddenly exploded into public consciousness. The MIT press published a seminal work and artificial intelligence applications and manufacturing 14 years ago. Manufacturing is a data and knowledge driven process, it’s all about manipulating molecules and we still can’t do atomically precise manufacturing at scale in spite of that historical trends and materials and manufacturing or clear increasing precision. Decreasingcosts,increasing flexibility, increasing speed, in fact accelerating speed and complexity is now free. Thanks to the advances in hardware, in algorithms, in cheap sensors and then access to data, things have really changed so AI can now contribute to manufacturing faster actions and decisions: 1. Product and material innovations 2. Improved efficiency 3. Higher accuracy 4. Lower costs 5. Increasing scale It’s not just about improving things on the manufacturing floor but improving things throughout the manufacturing enterprise from design to customer service, sales and administration and quality control. General Electric has been using AI in its manufacturing process for three decades. They’ve been using big data to make smarter turbines, to diagnose problems in their train engines for decades. Business Wire just published a report a few weeks ago, on a collaboration between robot manufacturers FANUC, Rockwell Automation, Cisco and Preferred Networks, an AI company. They’re all about creating an advanced analytics platform that improves overall equipment efficiency on the manufacturing floor. Yale University has
  13. 13. The Future of Finance 13 published a series of articles on using machine learning to provide integrated optimization of semiconductor manufacturing. General Electric is all also providing a software fabric to go over traditional manufacturing floors to provide increases in prediction responsiveness and connectivity to take a standard manufacturing floor of old-style equipment and turn it into a software configurable manufacturing engine. IBM has graduated Watson from playing jeopardy games and working in medicine to Watson explorer for manufacturing a single portal for integrating all of the information from the manufacturing enterprise. Search IBM Watson blog just a few weeks ago, looking for the article on how content analytics, text analytics and NLP (natural language processing) has helped auto manufacturers identify potential product liability just by looking at Twitter feeds and customer feedback. There’s been an increasing pace of AI investment and acquisition from 2011 through 2015, over three billion dollars and VC funds were invested in cognitive technology. During the same period over a hundred of AI related companies either merged or were acquired by the typical players: Alphabet, IBM, Facebook, Amazon, Apple People often described AI as a game- changing technology but it’s actually much more than that. AI is disrupting the entire field that we are operating on! The achievement where ALPHA GO won against the World Champion on Go four games to one is a led the Korean government to promise three billion dollars for an AI R&D program aimed at manufacturing. The underlying technology behind
  14. 14. Machine Learning, AI and Big Data 14 that Alpha GO player was a pioneering technology that combined convolutional neural networks (you can think of that as a fancy word for pattern recognition agent) with reinforcement learning that reinforces that agent for a high score in an arbitrary Atari game. These systems were developed by DeepMind Technologies in the UK, demonstrated for the first time in 2013. The system started from zero knowledge of any of these Atari games, says Neil showing images of well-known games in the history of gaming consoles, and they outperformed all previous approaches machine learning approaches and did amazingly well they discovered strategies on their own. After a hundred and twenty minutes of training DeepMind Tech machine learning system begins playing at a kind of mediocre human level. But then after 240 minutes of training the system tunnels up the left-hand side of the screen and plays from the back court where the game has no defenses that is a real breakthrough in AI. Just a month after that 2013 demo, Google acquired Deepmind Technologies for more than 500 million dollars. What is AI? People often want definitions… It’s pattern recognition techniques to solve practical business and technical problems. Software agents that can utilize resources efficiently. Most of the work that goes on in AI and robotics is not going to result in the sort of science fiction scenarios but if anybody tells you that the long-term consequences of the AI will be all good or all bad, they are cherry picking the data… AI comes with trade-offs, yes! Faster, cheaper, better problem solving but also job disruption, human identity change and risk amplification… and sometimes risk reduction. The AI community is taking risks seriously; “I was recently invited to a Conference on the future of AI in Puerto Rico where I joined with 50 AI researchers. We sat around for 3 days and talked about the research agenda needed over the next few decades to keep AI doing beneficial things for us”. Elon Musk worked with people from Y Combinator to create a new organization called Open AI to pursue advanced AI in the open so that everybody has access, not just big companies. They’re investing 1 billion dollars and some great researchers in that endeavor. They’ve already put out their first product: the Open AI Gym to evaluate different reinforcement learning algorithms The human brain evolved under very different circumstances and the ones that we have today it hasn’t had a major upgrade and over 50,000 years. Compare to your laptop or your cell phone upgrade in last five years… We’re going to have to augment our cognition both in everyday life and on the factory floor. We’re going to use statistical and deep machine learning task and domain-specific knowledge engineering marshalling the data and biologically inspired computing architectures like deep
  15. 15. The Future of Finance 15 learning. Deep learning is the champion algorithm in machine learning has been winning all the contests and one of the things it does is hierarchical pattern recognition. It can start with pixels and then go to edges and then it begins to recognize object parts at the next layer of the hierarchy and finally objects and you can add arbitrary numbers of layers, 152 or 300 or 1.000 and get amazing feature discrimination. DARPA (Defense Advanced Research Projects Agency) has a new program called probabilistic programming for advancing machine learning and what that’s about is opening up the black box of machine learning algorithms and getting them to play well with others particularly relevant for the manufacturing floor where we want to be able to use simulation and optimization and get all these algorithms to play together. AI it’s not just better, faster, cheaper… it’s different. AI allows us to expand the range of the possible in the form of practical business and manufacturing problem solving. Create an application oriented AI toolbox! Download the Machine Intelligence Landscape infographic, is just lots of different examples of machine learning companies and techniques, all classified into different bins. There’s a company called Nutonian that you might want to track, they have a machine learning product called Eureqa. A company called Río Tinto was working on powdered metal steel and they were having trouble in their quality control. They used Eureqa to analyze many different variables involved in the powdered metal manufacturing process and it turned out that one of the variables that they just threw in there for kicks turned out to be the really important one causing their quality control problems. If you don’t have the bench strength in your own company, you can extend your bench strength by putting out your data in the public and putting up some prizemoney at Kaggle and the world’s greatest data science teams will compete for the solution to your problem. Another way to increase your bench strength is to use a company called x / 5 that curates a marketplace of qualified data scientists they came out of the Harvard Innovation lab and they allow you to just put out your problem without revealing your data and then pick a qualified data scientist to work with you. Let’s talk about some work implications Oxford Business School had a study in 2013 of the next 10 to 20 years of the American job market and they can be noted that 47% of the most routine jobs in America would be vulnerable to automation over the next few decades. They updated their work over the last few weeks. They put out a new report called Technology at Work where they looked at the entire world and they concluded that developing countries have an even bigger problem, they have more people involved in routine work both in factories and in administrative jobs, their
  16. 16. Machine Learning, AI and Big Data 16 risk is even higher! That suggests we’re going to need to team with AI strength that way we’ll get best-in-class performance at least for some deaths pure biases and decision-making superfast operational velocity will be able to team with a partner that works seven days a week 24 hours a day, no vacation or sick leave required, no healthcare insurance but limited empathy, language understanding and social grace. The winning formula for working with AI and robots for that matter humans plus a is plus good business process that’s more powerful than AI alone. We’re going to be able to combine that power to increase our productivity remarkably. We’re going to build very smart systems. “We’re going to reverse engineer the human neocortex, make vast artificial neocortex and make our factory floor super smart.” How to think outside the box? There is no box, remember that AI is going to change the balance of power between big companies and small startups. Some operational recommendations to transform manufacturing products and services: 1. To team humans plus AI best- in-class business process is a winning formula. 2. Utilize the power of machine and deep learning, try all the free tools that are out there, they’re surprisingly powerful. 3. Leverage AI platforms and your manufacturing operations, not just in your customer facing products and services. 4. Outsourced and increase your bench strength with Kaggle and other crowd services and be proactive about security ethics and product liability. Para profundizar, recomendamos: VIDEO CHARLA https://www.youtube.com/ watch?v=0lH706jQ8GQ ARTÍCULOS Manufacturing Automation Leaders Collaborate: Optimizing Industrial Production Through Analytics http://www.businesswire.com/news/ home/20160418006725/en/Manufacturing- Automation-Leaders-Collaborate- Optimizing-Industrial-Production How content analytics helps manufacturers improve product safety and save lives https://www.ibm.com/blogs/ watson/2016/04/content-analytics-helps- manufacturers-improve-product-safety- save-lives/ The Current State of Machine Intelligence http://www.bloomberg.com/company/ announcements/current-state-machine- intelligence/ HERRAMIENTAS www.kaggle.com https://deepmind.com/ http://www.nutonian.com/products/ eureqa/
  17. 17. The Future of Finance 17 Quantum Computing Marcos López de Prado, Senior Managing Director, Guggenheim Partners. Marcos begins his speech by asking: “How many of you have heard about quantum computing? and how many of you have actually use a quantum computer?” The motivation for why quantum computing is important when you think about the challenges that financial research faces today. Most of the financial research that you’ll find are publishing papers in journals, it’s a research that is not based most ofitonexperiencemeaningthat most academics do not have access to the only laboratory that exists for finance. Think of a physicist who has never been able to drop the ball and experience how gravity works, or physicists who is thinking about particles but has never had the chance to experience in an accelerator, so that is the situation in finance. The second problem, according to Marcos, is models tend to be very simplistic. When you think about it, financial markets are very complex networks, much more complex than for instance climate or weather prediction, because when you’re trying to predict the weather you have to model all these variables, but the variables are not reacting against you, they are not trying to learn what you are learning and acting in a different way to counter to produce a counter effect for countermeasures, and that’s the second problem: typical financial research models are way too simple for the kind of problems that we have at hand. What is the implication? Most research that appears in journals tends to be very simplistic toy models that are over-feed on data, they are not experimental, they are empirical. They measure things but they don’t observe reactions. In the end, the president of the American Finance Association has acknowledged most research findings in financial economics are just false. So, what can we do about it?
  18. 18. Quantum Computing 18 The biggest problem is computational power. The models are simple because people don’t have access to the computational power needed to solve difficult problems. What finance needs to advance and to solve meaningful problems in a reliable way is a kind of machinery that other fields of science used to solve their problems. There is no Large Hadron Collider equivalent in finance. Quantum Computing offers this possibility. What is Quantum Computing? It is a field of research that studies the algorithms and systems to the solution of complex mathematical problems. It was founded in early 1980s by Feynman Benioff, who noted that Deterministic Computers could not simulate efficiently a probabilistic problem. He proposed to develop the new kind of computer device, centering on the probabilistic system usage. It was proven in theory that it was possible to have a computer that could solve an encryption in a matter of seconds, where deterministic computers needed years. The holy grail of Super Computers is Parallelism. You can split the problem in various pieces, and solve them in parallel. In Quantum Computer, this occurs in a circuit level. Quantum Computers don’t work in bits. A bit is a memory item that can have a state of 0 or 1, so 2 bits could be in 00 01 10 or 11, but two qubits (unit in Quantum Computing) hold four units of information; Why? because the four states 00 01 10 and 11 are in a linear superposition, this means that there are four coefficients that characterize the state of the system for variables to represent the information packed into qubits. If you have “n” qubits this means that you can hold two to the
  19. 19. The Future of Finance 19 power of “n” units of information, and there is word “exponential finance”, the exponential power of Quantum Computing. There is a second very important fact about quantum computers and it is the way they solve problems. Marcos proceeds to use a videogame called Angry birds as an example for comparing how a computer works, and show the difference with quantum computing: “You see, when we take a traditional computer let’s say that we are playing a video game like angry birds and you’re going to shoot that bird over those pigs, right? What is the computer doing? Is its solving a partial differential equations system? Is it solving a mathematical problem that represents a physical phenomenon? What quantum computers do is, they work the other way around. They use physics to solve a math problem, it is the anti-angry birds game, is the game where you code a microchip to behave like gravity and then you go and throw the bird and see where it falls…” When you think about it what is essentially powerful bit about this paradigm is that it replicates how the universe solves mathematical problems. There are plenty of very hard mathematical problems that the universe and nature solves all the time, for free, instantaneously. Quantum computer is just a way of changing the problem, it is asking nature to solve this problem for us. “How do they look?” says Marcos, showing a picture of a tiny microchip, basically inside a fridge. That fridge is for isolating the microchip from electromagnetic fields, and cooling it to a temperature of 15 micro Kelvin, which is 180 times colder than interstellar space. Until five years ago, many people in the physics community were very skeptic about the power of computing and even the possibility of one appearing which now is kind of undeniable, says Marcos. In fact, there are multiple commercial quantum computers available. “In the end, you have to think of Quantum computing as a paradigm breaker”, continues Marcos. How can it be used for optimizing a portfolio is trivial, but when you want to compute the optimal portfolio, the optimal trajectory of the portfolio over multiple rebalances, that turns into a very hard problem to solve for traditional computing. Once we get larger supercomputers in a few years we will be able to solve very large scale portfolio optimization problems. A second use case is a scenario analysis, how many times you hear in the board meeting the CIO asking for scenario analysis? How many scenarios can you think of? 10? 15? What if we allowed a quantum computer to use its power to simulate the portfolio under billions of scenarios? The third use case could be Option pricing according to Marcos. Pricing becomes problematic when you end up in path dependent processes, but this sort of path dependency is not a problem to one Quantum Computer because they will evaluate a tremendous number of alternative outcomes and derive the price based on those. Fourth and last, is Clustering. A classic problem where you are
  20. 20. Quantum Computing 20 trying to put together things that are similar, and when you go into the dimensions of one thousand instruments, the correlation matrix is a heat map of the correlation matrix with, which is essentially is going to be garbage, but what if we use a classroom algorithm to reduce the dimension of the problem to a manageable size and take these thousands of instruments and tells: “You have 10 different instruments” after contemplating all the data set. This could have a huge impact on risk management, for example. Why is this relevant? There are many reasons why quantum computing is relevant and is going to change all of our lives: 1. Feynman’s observation: Quantum Computers are better suited than deterministic computers to solve Financial problems. 2. The end of Moore’s Law: The size of transistors is reaching its physical limit. We have been living for the past 30 years an incredible era, where computers became more powerful. In 2012 we experienced the peak for Transistors per dollar. “The Digital computers era is about to end, and we need something to replace it, and the best candidate is Quantum Computing. “Marcos then goes on commenting on Artificial Intelligence and Machine Learning, stating that Quantum Computing could provide the computational power we don’t currently have to boost those technologies. “Nobody really knows how a quantum computer works because this quantum mechanics, right? As soon as you try to look into what is going to happen, what is happening in the system, you are perturbing the system and the system changes its state, so I think it’s going to be very interesting when we recognize that in order to develop artificial intelligence we need this kind of machinery that we don’t truly understand…” Marcos reinforces. PARA PROFUNDIZAR RECOMENDAMOS VIDEO CHARLA https://www.youtube.com/ watch?v=kU7vk9jmQC8 CONTENIDO ADICIONAL DE MARCOS http://www.quantresearch.info/Lectures. htm HERRAMIENTAS www.Quantumforquants.org
  21. 21. The Future of Finance 21 Energy and Smart Networks Ramez Naam, Energy & Environmental Systems Faculty, Singularity University. Ramez spent 13 years at Microsoft, where he led teams developing early versions of Microsoft Outlook, Internet Explorer, and the Bing search engine. His career has focused on bringing advanced collaboration, communication, and information retrieval capabilities to roughly one billion people around the world, and took him to the role of Partner and Director of Program Management within Microsoft, with deep experience leading teams working on cutting edge technologies such as machine learning, search, massive scale services, and artificial intelligence. Ramez starts the speech talking about the disruption of energy, because energy despite being a fairly static industry for decades, it is now an exponential industry with rapid changes in technology. Ramez says a few years ago, he wrote a book about the challenges of Natural Resources and environment and the question: “Can we innovate fast enough to overcome them?”, and what he found in doing the research for that book is that the technology progress in the energy space is incredibly rapid and far faster than most people take for granted, and if we play out those trends and take the math seriously it has staggering consequences. Ramez also says he is a clean tech investor, so he comes at this from a perspective looking at where they’re good deals, where there are opportunities to disrupt markets and also build large new markets and large new companies. Wind power might look like a stagnant 19th century technology but it’s actually one thathaschangedtremendously. Over the last dozen years, the amount of wind power we have deployed to buy a thousand percent (x10). That’s not normal in the energy field, and that happen for a number of reasons: Policy pushing it was a big one, but that policy would not have been effective
  22. 22. Energyand Smart Networks 22 if it were not for an exponential decline in the cost of wind power. Whole power, electricity prices in the US are around seven cents. Let’s say in the nineteen eighties wind power costs nearly 10 times that much per kilowatt hour, now, last year, the average price of a new wind power long- term contract in the US was actually 2.3 cents per kilowatt hour and the cheapest were below 2 cents. That is a staggering drop in the price of wind energy and it’s been driven by a huge amount of innovation in the sector. A basic thing is that we have learned to make these wind turbines bigger. Why does that matter? Well higher up the wind blows more steadily and it blows faster, so that gives you an advantage. And secondly, the amount of power you get from a wind turbine is equal to the area the blade sweeps through, so if you can double the blade length you can quadruple the amount of power you’re capturing. You can also capture lower speed winds. So, as we’re learning more and more about manufacturing techniques, about new materials, we’re able to tap into these, and we can see how the price of wind power has plunged as the scale of these turbines has grown, and this leads not just to more power at a lower cost, it leads to steadier power. Today the wind fleet operates at a thirty percent capacity factor. That means that a wind turbine produces about thirty percent of the max that is expected for, but as we get towards taller and taller turbines the Department of Energy expects that within a few years we’ll be able to get sixty percent up time of these wind turbines, and now it no longer looks like an intermittent platform for energy but more like a steady one. GE is one of the leaders worldwide in the development of
  23. 23. The Future of Finance 23 these new wind turbines and innovating in new ways like the GE space frame to build them taller while transporting them. Big data, machine learning, and so on, that is also vital here because these individual turbines are intermittent. What was found is in cases like Colorado with the excel utility there, using sensors on the wind turbines collecting that data and putting it into algorithms to do predictions of which turbine was going to spin at which speed, a few minutes from now, a few hours from now, on a day from now, allowed excel to triple the amount of wind power they could put on their grid and that saved them billions of dollars, because it is the cheapest power they could buy in their state. As we mentioned before, higher up the wind blows more steadily. Marc Andreessen says software is eating the world, and this is an example of that: A prototype that’s not in production yet about a blimp that has inside of it a small wind turbine, and it is actually a drone, it flies under computer power and it can hover about 500 meters above the ground (three times taller than the tallest wind turbines) and tap into those high-speed winds and then drop down in the case where the wind is too high for it to be safe. Or as another example there’s another drone from a company called Makhani Power in the Bay Area. It tilts back, takes off under computer control, flies up to as high as a kilometer up tapping into those high-speed steady wins; You could never pay the capital cost for a kilometer-tall tower but you can pay the software costs to self-steer this drone and then act as a giant wind turbine in the sky. This company was acquired by google two years ago, who wants to bring it to production. Another point to highlight is Solar energy. There has been an incredible pace of innovation in solar panels. They are made of a chip and if we wanted to plaster thousands of square miles with intel chips, the cost for that would be Quadrillions of dollars, it would be impossible. But, like silicon wafers solar power has had a ferocious and exponential cost decline over the course of the last 30 years (it has plunged by 200 times), that means we’re now seeing solar energy winning deals without subsidies in various parts of the world. It happens especially in places where the 1.3 billion people that don’t have electricity today live and about three- quarters of the world’s growth in energy consumption over the next few decades will be which is a relatively sunny area. Regarding Cross-over, one physical case worth mentioning is a natural gas plant in the US the EIA estimates this cost seven and a half cents per kilowatt hour if you build a new one. In Chile we’ve had about a dozen deals and an average price about six cents per kilowatt hour without subsidies, China (the Gobi Desert) also got six cents, India an Ambar ultra-plant 4 gigawatt plant, an enormous plant the size of four large coal powered plants and capacity at about six cents per kilowatt hour, and in the US six months ago First Solar sold to Berkshire Hathaway a 3.9 cents kw/h central in our
  24. 24. Energyand Smart Networks 24 deal and then last month the city of Palo Alto bought solar from a company in LA at 3.6 cents kw/h. Now this is a subsidized price, but back out all the subsidies about 5 cents per k/h and it’s still about a third lower the price of new natural gas and its producing at peak demand time. And around the world is even better than that, Mexico: the average price in their solar auction last month was 5.1 cents, the lowest price was 3.5 cents unsubsidized. The price in the US in the last eight years has plunged about 80%, just a phenomenal pace of change. In Dubai, one of the oil capitals of the world, this 800 megawatt plant a giant plant being built by Aqua Power (a Saudi firm) and this price did with no subsidies for this plant for the next tranche was 2.99 cents, about half the price of natural gas. In the last three years, we’ve gone from solar being completely uncompetitive to solar in sunny parts of the world, to crushing all other competitors as far as price goes up and that has helped drive an enormous explosion. Wind power scaled by a thousand percent 10x in a dozen years, Solar has left that in the dust a 100 times growth in 13 years. For now, this explosion is unlike anything that we’ve seen in energy. This happens for a lot of reasons. Manufacturing scale, one of the first Exponential’s we ever saw is that the price drops along the learning curve, and this curve is quite ferocious, 20 to 25% reduction in cost per doubling of scale, and that’s going to keep on going for quite some time. That allows the industry to reinvest revenue in R&D to make more and more efficient cells that capture more of the sunlight that hits them, so the prices are going to keep dropping. We are very far from done yet and the prices that you see in Dubai or Mexico will one day be the prices in California, and then after that they’ll be the prices in Middle America and we will have the ability to extend the grid to spread out but, what do you do if the Sun isn’t shining or if the wind isn’t blowing? These are still intermittent resources, no matter how high their capacity factors are. With good integration, you have a far steadier output. Diversity, you can put solar and wind together. We think now that about 80% of electricity meet needs in California can be met with no storage just putting together solar and wind and large-scale grid connections. There’s also another kind of challenge that happens because solar is getting so cheap so fast. For a long time, the power prices that you all a had been paying are highest in the middle of the day, because that’s when peak demand is (Supply and demand: there’s more demand the middle of the day in the late afternoon so prices are higher), but as solar comes online or perhaps a decade away from a point where the middle of the day power prices in much in America are at the lowest prices because it’s a surplus of power right then and there. INTERNET OF THINGS. You hear a lot about smart power, and that’s what this means is being clever about how and
  25. 25. The Future of Finance 25 when to use energy to match the prices you want. Nest company bought by Google. Why does google want a thermostat? Because this is part of the smart grid. This thermostat knows if someone is home and it has a connection to the utility, and if the utility sees that a very expensive peak of power demand is coming late that afternoon because it’s a hot day in Austin, then they can reach out to these nests and say “hey we want to avoid that peak run the air conditioner a little harder a couple hours early and then we won’t have to have such a high peak demand”, and spin up new power plants and the person at home never notices this is happening and they get a reward. They had a kickback from the utility because this is a savings of tens of billions of dollars potentially across the country. In Europe, it’s hot water heaters, so these hot water heaters increasingly are getting smart. They know when the power cost is low; in Europe, it’s when wind power peaks sometimes it might the price drops to zero or negative, utilities will pay you to take energy, and so these connected smart water heaters know that and say we’ll take that will save it up for the morning. Or data centers, the world’s data centers use now about 12% of electricity and growing; all that IOT and cloud stuff it’s not for free, it’s real and it exists in places like this, and they’re becoming increasingly smart being able to absorb load. Another example are electric vehicles; if you have a Tesla you already know that has programming to go for low power prices or during the day they sit at work and whether its own solar panels at the workplace or just the solar utility-scale attention to the grid, when that price drops during the peak hours of the day that car is sitting there and ready to be charged and provide services of the grid by being able to soak up the extra. WATER. In West coast California when there is a massive drought, we can desalinate water. Desalinated acceleration is expensive but about half the cost is energy costs, so this is something you can do when the energy gets the cheapest; a desalination plant in Dubai consumes 12 gigawatts of power and desalination about 500 million barrels of water gallons of water per day. Mapping that the lowest energy prices suddenly allows you the flexibility didn’t have. Ultimately though you need energy storage. We all know who Elon Musk is. He’s announcing the tesla Powerwall battery, and the funny thing is Panasonic makes that battery and it’s got a Tesla casing on the outside; but it’s not some technical breakthrough that got them there it’s a long-term exponential trend. A tripling in the amount of power you can store program and a 10x reduction in the cost of batteries over the course of the last 20 years and that keeps on going. In Germany now it looks like with a small battery, about half the size of the Powerwall, and a small solar panel a German household can provide about seventy percent of its own energy in summer months. So, if your utility and your business model is charging
  26. 26. Energyand Smart Networks 26 by volume, what happens to you in this world? Businesses models are going to have to change and now we start to see utilities wanting to own that solar panel so they can get it on both sides, and the ones that flourish will do that but Tesla got a billion dollars in pre-orders the first week they announced the battery most of them did not go to homes, 90% were for this size battery which went to businesses, commercial spaces, factories and utilities and now every manufacturer in the world that does solar is moving into the same thing. Trina solar battery, the largest solar company in the world, about a 1 megawatt hour battery, and they go after some very simple scenarios, even if you don’t care about solar that’s probably the case that you pay one price for energy at night that’s very cheap and another price during the day; in California that Delta is about 20 cents per kw/h. Guess what? A battery is cheaper than that now, so you can fill it up at night with cheap power and then discharged it during the day instead of using that expensive power. Battery prices are not done coming down. There is a whole range of different forecasts about where battery prices would go and these analysts (including the EIA) said that there would be huge drops over a 10 years’ period. Batteries also follow the exponential learning curve, as they get higher scale they drop in price and they do so it basically the exact same pace as solar. This leads to a crazy idea being that energy going clean might actually be cheaper than dirty energy, we’ve always assumed
  27. 27. The Future of Finance 27 that going clean meant higher prices, but now we’re starting to see even very conservative organizations say that it might actually be cheaper. The IEA says solar will be the dominant form of electricity in midcentury and the cost will be unbeatable for UBS. They said renewables are now deflationary to energy prices. We’ve coupled the cost of energy to the ever-declining cost of technology. It’s like your Kodak: you think these digital cameras will never catch up. The world is now to using more clean energy per year than dirty energy, and we will never look back. The former Saudi oil minister once said: “The stone age didn’t and for a lack of stone, and the oil age will end long before we run out of oil”. He’s warning us that the world is going to produce a technology replacement for oil. Oil fluctuates by a two percent, two million barrels per day difference in supply demand has caused this huge oil fluctuation that nobody predicted it, but we are headed there and electric vehicles (EVs) are going to get us there. The IEA forecasted that we’d be selling 1,000 vehicles a year with a 200-mile range by 2040, so you just can’t trust the experts in this, trust the technology and the innovators. And as the battery prices come down we’ll sell more EVs which will bring down the cost of batteries, which will make EVs cheaper, and we’ll some more EVs as a perfect virtuous cycle. By 2030 they’ll be cheaper than the cheapest car sold in the US. The long- term price of oil is very cheap as our demand drops. PARA PROFUNDIZAR RECOMENDAMOS VIDEO CHARLA https://www.youtube.com/ watch?v=O9FR5-aElWA HERRAMIENTAS https://www.iea.org/ http://www.iea.org/newsroom/ news/2016/november/world-energy- outlook-2016.html https://www.tesla.com/powerwall https://nest.com/
  28. 28. Robotics 28 Robotics Rob Nail, Associate Founder & CEO, Singularity University. Rob begins his speech by doing a quick overview of the robotics space: “Robotics as you can imagine doesn’t have a lot of direct impact on the finance space, but a lot of indirect implications, if you think about insurance or maybe interesting retail opportunities”. Rob then continues by announcing SU opened its first innovation hub. A regional innovation hub in Netherlands, as part university’s strategy to bring awareness about exponential technologies around the world. They’re empowering their alumni base to take some of this thinking to develop their own content and programming, and the first manifestation of that is in the Netherlands because of their alumni base and some interesting partnerships. Rob then tells about an example in the opening celebration involving the archaic regulations that limited the Queen’s (who attended the event) interaction with robots, using said example to highlight how the advances in technology are quickly forcing a lot of work to upgrade our thinking, and our systems in general. After that, Rob mentions three key things that drive the pace of robotics today: Moore’s law, the sensors, and the way we teach robots: “20 years ago, to program a robot to do the simplest of moves you would have to write assembly code in machine language and it would take you weeks and months to program a complicated system. Today we have open source libraries of code, we have drag-and-drop software tools a robotic operating system where eight year old kids can program pretty complicated robots to chase the cat and throw a ball at it when you say a magic word. If you get the Lego’s Mindstorm Kit you can do exactly that this weekend, different paradigm, right?... “Anything that we do physically that it has to be safe, accurate, fast and cheap is perfect for consideration of Robotics”. But leading edge robotics in terms of volume
  29. 29. The Future of Finance 29 and efficiency is not all. Right now, the new face of manufacturing robots is Baxter (rethink robotics), a robot that is aware and interactive with the environment, and allows you to walk it through the steps to perform a task, learning from what you taught it. DARPA ROBOTICS CHALLENGE. The Defense Advanced Research Projects Agency was pretty scared of the what happened with the Fukushima nuclear power plant disaster several years ago. If ever there was a situation where you have to go in and solve the problem but you really don’t want to send humans in its a nuclear fallout situation, right? So they put up a two-million-dollar prize to develop robots that could do a disaster recovery and they had eight discrete tasks to complete, and about 20 teams that competed. Each team had an hour to complete every one of these tasks. Two and a half years ago, no single team completed every task. This year, the challenge gave the teams one hour to complete 10 challenges, and three teams completed the whole challenge. Where it does get interesting mostly for commercial applications is when you simplify it. Rob then talks about Panasonic’s exoskeleton that was just launched last year in inventory management to heighten human’s capabilities, and states that more technologies are coming online every day, for example, concierge or security bots: Relay (Savioke), Navii (Fellow Robots), K5 (Knighscope) or HOPI-R (Panasonic). Imagine if you overlayed this with some other technology around facial expression or verbal analysis. Now robots can understand emotional state and act accordingly, and a whole new line of interesting consumer-level products are out on the market or being introduced this year. Rob says his favorite is Pepper, which is a robot introduced in Japan, marketed specifically for the elderly, functioning as a companion. Some researches has come out over the last couple years (specifically targeting elderly) that suggests if your behavior changes dramatically, it’s a very clear sign of a declination of health or a change in health status. You wouldn’t recognize if that was you, but a robot would be tracking it and noticing patterns. If all the devices around us were information platforms aware of their environment, what kind of new correlations and interesting valuable propositions can they provide to us? Rob then goes on talking about how there’s been a lot of research and concern about the future of Jobs, largely because of robots. There’s a research from Oxford on 2013 that says 47% of US jobs face a “high” risk of being replaced by automation. The rest of the researchers come online are a little bit more conflicted: Millions of jobs are going away, but new jobs are coming online or transforming, because of automation and robotics. If you see how this plays out on an exponential curve, that’s just going to keep happening more and more, what’s the inevitable conclusion? Technology, robotics and automation will provide all the basics for us so that every
  30. 30. Robotics 30 physical task and activity will be provided through them (Rob suggests 20 years in a timeline for this to start happening). Every physical task worldwide will be an opportunity for robot usage. “Are we prepared for that? No, we are not”. We still live in a world where our economic system is very much dependent on everyone having a job. Rob ran some forums where he invited some administrative positions in the government and when this topic was mentioned in the invitation, everyone’s response was that it would be political suicide to show up on an event where they about how “everyone in the future does not have a job”. If our politicians can’t even entertain a different version of the future, how are we going to get there? Rob then comments on the voted and rejected Universal Basic Income experiment in Switzerland, highlighting his interest in that kind of examples, in a future where technology is going to play a much bigger role. Rob says we need to be running thousands and thousands of experiments around the world to figure out a new economic system, but he thinks most importantly is how the mindset is required to change. The future of abundance where technology can provide the basics, and our systems need to adapt fast and radically. PARA PROFUNDIZAR RECOMENDAMOS VIDEO CHARLA https://www.youtube.com/ watch?v=Mnc9F_bF6dM UNIVERSAL BASIC INCOME http://www.bbc.com/news/world- europe-36454060 HERRAMIENTAS http://www.savioke.com/ http://www.darpa.mil/program/darpa- robotics-challenge http://www.fellowrobots.com/ http://knightscope.com/ http://www.panasonic.com/global/ corporate/technology-design/r-and-d.html
  31. 31. The Future of Finance 31 Uber Yourself Before You Get Kodaked Rob Nail, Associate Founder & CEO, Singularity University. Deloitte set up a program called the innovation partnership program with Singularity University XPrize. They established about three years ago, and the reason he brings this up is because over those three years they had 30 of the largest companies in the world, all fortune 500 corporations mostly fortune 200 corporations, get together in a membership model where they bring them up to singularity university or X PRIZE headquarters and spend three or four days with executive teams literally that the senior leaders of these major organizations. There’s no competitors in the same room there, where companies really started to realize that their next 10 years, the level of disruption that could take place as well as a level of opportunity that they could capture was significant, and you could almost see which industries are moving faster than others. More importantly within each industry, you could see certain companies that were moving forward well everybody else wasn’t paying attention, so whether you know it or not there is a level of disruptive advantage that’s starting to take place right now. Disrupt yourself before you get disrupted. Uber yourself before you get Kodak’d. The notion is disruptive advantage instead of competitive advantage, so instead of trying to do 10% improvement go for ten times improvement. If you look at certain organizations like Google with Astro teller who runs the Google X program, he comes and talks at the innovation partnership program and he discusses this notion of legitimately creating a culture where you are trying to go 10 times better not ten percent because to go 10 times better doesn’t take ten times smarter people, it doesn’t take ten times as more people, it doesn’t take ten times the
  32. 32. Uber Yourself Before You Get Kodaked 32 amount of investment, but it’s ten times better so the economics really pay off. The other notion is the pace and magnitude of change, and who can create that change. The fact that we are surrounded by a world of entrepreneurs that are really creating new ecosystems, that are creating a level of innovation we just haven’t seen before. Marcus then says he’s going to talk about “The future of the firm”. Particularly in this time with everyone being connected to the internet, with super computers in the pockets, you have this crowd phenomenon that’s happening. You have a labor force that goes way beyond your four walls as an organization. If you haven’t been paying attention to the crowd movement, you’re not designed as an exponential organization. In terms of industrialized crowdsourcing think about this: what if you could get access to anyone, anywhere in the world, any time a day and at the scale that you need. If any of you are in the HR side and you’re thinking about the labor that your organization needs, how are you going to start to staff up around some of these technologies? Having scale on demand is very important in that model, to be able to scale the expertise when you need it. If it has a long shelf life great, but it has a short shelf life you don’t have to let everybody off, you can scale back and in scale up, and that’s very important from having that adaptable and agile framework. And this is not just simple task, but
  33. 33. The Future of Finance 33 you can crowdsource people around the world to do very complex things and very open ended things, and the reason why we’re seeing this happen now versus we weren’t talking about this even 5 years ago (or 10 years ago) is because it’s this trend that’s happening where you’ve got cloud internet computing, everyone you know in the world is walking around with super computers in their pockets, and then also keep in mind the social aspect people, especially Millennials. “My kids there are more used to collaborating with people that they don’t work in the same four walls with, their growing up this way…” says highlights Marcus. The Millennials are the largest portion of the workforce in the US. Other trend that’s happening which is the delineation between current economic conditions is creating an interesting scenario where you have one group of people worldwide that have too much money and not enough time, and you have another group that has not enough money in too much time. It relates a little bit to the inequality and income discussion. This groups are connecting with each other. The notion of using brains outside of your departments, and the wisdom of the world of the genius of the crowd worldwide. You have got to keep in mind that right now they have a lot of projects that are happening that are underway, like Google Loon, or the Facebook Drone project that Mark Zuckerberg is working on, you have all these efforts that are underway to give everybody on the planet access to the Internet, in many cases for free, so it’s very realistic to think that in the next five to ten years the experts are saying we will have free Wi-Fi for everybody on the planet or everybody will have access. That’s going from 3 billion people of the planet to 7 billion people that have access to the internet; think about all these minds that are now connected. If you don’t have a strategy to tap into that wisdom, to leverage all those minds across the world, you’re going to lose against those that have that strategy. Who are the crowds? It could be external crowds (these could be your consumers, communities of interest, affinity groups, scientific communities) or internal crowds, have hundreds of thousands of people in your own organization. When you hear about these Crowds strategies, which is a way to capture excess capacity, you can use it without going outside your organization, you can just harness the wisdom of your entire crowd within your own organization. And these are one in the same, make no mistake about it that you have people in your organization today that a nights and weekends or perhaps even in during the day when they’re working for you there and on the web starting to play in these crowd models. Especially the younger generation that understands how these models work. Whatever they’re doing they can participate in these models, and start making income outside of your organization.Thesearerathersophisticated groups, sometimes people think that these crowd models are all the people the world that don’t have regular jobs or can’t get jobs,
  34. 34. Uber Yourself Before You Get Kodaked 34 and that’s actually not the case. They’re just competing on these crowd platforms on nights and weekends. The interesting thing is that some of the more prominent crowdsourcing sites where you can crowd source data scientists from around the world, or developers from around the world to make your next commercial. We’re finding out that if you’re really talented, so you graduated top of your class and you’re just the best developer in your class, out of school you can start to play in these crowd models. They don’t go searching for any job, they get into these models and they’re making seven figures out of school because they can just quickly win (a lot of them are competition-based). So, you’re finding that some of the best people in the world are going into these crowd models, which you can take advantage of, and it’s important to understand why this is actually a superior model, the reason being is that the smartest people in the world don’t work in our companies, because there’s seven billion people on the planet, the smartest people world have to be somewhere out there in the crowd. So, if you start to compete against a company that’s using the genius of the crowd or the wisdom of the world, you’re going to put yourself in a competition and you’re going to lose. Breaking down these models you start to see the type of incentive structure in which these crowd platforms work: 1. Compensation. You can pay people and they’ll work for you, regardless of where they are in the world, regardless of what time of day it is, right compensation is
  35. 35. The Future of Finance 35 a big incentive. 2. Convenience. You also can make things very convenient. Gig Walk, for example, an app that when they walk into a grocery store it prompts and offers to pay for information. 3. Gamification. Making a competition in the game out of the exercise to where people actually fulfilled your need because they actually thought they were partaking in a game. 4. Credibility/Ego. A lot of these models are competition based models where the winner gets recognized, or the group of winners get recognized 5. Passion. 6. Competitive spirit. You’ll see a lot of crowd sourcing sites use competition to do it. It’s not always about the money. XPRIZE is now trying to use all of these elements. It’s a non-profit focused on taking on some of the world’s greatest challenges. The world needs it solved, so they basically designed an instrument that they put out to the crowd. Marcus then highlights the Qualcomm Tricorder XPRIZE, a competition that offers 15 million dollars to whoever can create a handheld device that can give you the same diagnostics of 54 health markers, essentially having a board-certified physician in your pocket. According to Marcus, there’s a trifecta that rules the models: Crowdsourcing, sharing economy and excess capacity. 1. Excess capacity is alluding to physical things, but can also be interpreted as intellectual capacity. A couch that you have in your house, a bedroom, the automobile, etc. AirBnb, Uber, Couchsourfing. 2. Sharing economy. Everyone is more inclined to share with each other. 3. Crowdsourcing, as a way to connect supply and demand. If you go out into the ecosystems of entrepreneurs and innovation ecosystems around the world, this is what everybody playbook. Who capitalize on all the excess date of coming off when you’re in traffic? Waze used that. That was their model, excess capacity data that just wasn’t being used, it was considered not even valuable. What you should start asking yourself is where do you have where is your consumer’s product excess capacity, because it’s going to be put into this model It’s absurd idea to think that the spare bedroom in your house is going to be used, and shared in your clothing there is technology that’s going to make it friendly to scan yourself to understand your dimensions, that to be able to use artificial intelligence machine vision to figure out just by taking a picture of your closet to start to inventory your closet, and then get an Uber car to bring it from your house to another house. Someone’s is going to make an app for people to take all the assets they don’t use, or sub-use, and start sharing them in the sharing economy. So, if you manufacture
  36. 36. Uber Yourself Before You Get Kodaked 36 anything or manufacture parts that go into any of these things, you should assume that you’re going to be out of the mix. Intellectual capital is being shared too. Crowds sites using all that intellect to be part of the crowd model, so you see sites like Topcoder to developing and coding, you have Medcast for doctors, you have InCloudCounsel for legal, and even Tongal for crowd commercials. Everything is going to this model. Colgate-palmolive did this in about three years ago. They spent seventeen thousand dollars as the prize money, put it out to 70,000 creative people. They only had to pay if they like the winner, so they picked a winner, gave him $17.000 for the video, and it was so good it became their 2012 Super Bowl ad. PARA PROFUNDIZAR RECOMENDAMOS VIDEO CHARLA https://www.youtube.com/ watch?v=ivZIt7BMnnM HERRAMIENTAS https://tongal.com/ https://www.airbnb.com https://www.incloudcounsel.com/ https://www.couchsurfing.com/ http://www.mdb.gov.my/medcast/login/ https://www.topcoder.com/
  37. 37. The Future of Finance 37 An Interview with Ray Kurzweil Ray Kurzweil, Director of Engineering at Google, Co-founder & Chancellor of SU. Ray Kurzweil is director of engineering at Google and the co-founder and Chancellor of Singularity University. He is one of the world’s leading inventors, thinkers and futurists with a 30-year track record of accurate predictions called the Restless genius by the wall street journal and the ultimate thinking machine by Forbes magazine, and was selected one of the top entrepreneurs by ink magazine which described him as the rightful heir to Thomas Edison. Bob Pisani then continues to introduce him until Ray himself joins the conversation through a Beam, a robot that contains a screen which he can remotely operate. Ray then goes on talking about the law of accelerating returns, mentioning a lot of important events that have been recently happening (such as the GO championship for AI, self-driving cars, image recognition, and comments on how he is currently writing a new book, called “Singularity is nearer”. Ray continues talking about AI: “There’s been tremendous confidence in AI recently, so much that people are now concerned with the downsides. We’ve gone from AI will never work to “oh my god is going to work and what does that mean for Humanity””. Ray then goes on talking about how in the last few years the mathematical advances allowed to create more complex neural networks regarding AI, and computation in general. Ray states that is amazing how the first chart of the law of accelerating returns (dated 1981) can now reflect on how predictable it was, and mentions that they are effectively updating the current chart. “Not only predictable, but exponential”, says Ray, highlighting the fact that exponentials tend to be very seductive in the way that, at first, nothing seems to be happening but half way
  38. 38. An Interview with Ray Kurzweil 38 through the project the growth turns truly visible. On the other hand, Ray mentions that despite all evidence to the contrary, people tend to be pessimistic towards exponentials. Many people even think things are getting worse. According to Ray, what’s happening is that the advances in communication technologies, allow everyone to know everything with little time apart, and no geographical boundaries (For example violence or environmental degradation). This is the most peaceful time in human history, says Ray, your chance of being killed is dramatically less that it was centuries ago when it was dire scarcity of resources. He believes that the rise of democratization has to do with the rise of communication technologies, and so the world is getting “dramatically better”. Life expectancy in 1848 was 37 years, and with the gran transformation in Health and Medical Centers, we are now living that numbers in the dust. Bob and Ray then focus on the subject of AI. They mention the GO Championship withheld during that year, and the breakthrough that’s been impacting public consciousness about said subject. “The machine had made a move that the player did not understand but later described it as beautiful; I don’t know how to describe that but the Machine did something human players did not think was going to happen and later realized there was a beautiful move, something happened there…”, Bob says. Ray then boards the subject:
  39. 39. The Future of Finance 39 “Well it’s interesting, in the early eighties I predicted the computer take the world chess championship by 98, and it happened in 97. That was really a victory for the symbolic school of AI that at as many of you realize it’s been these two competing schools of artificial intelligence being able to think things through logically, the so- called symbolic school and the connection in the school exemplified by neural Nets, where computers basically emulate human abilities at recognizing patterns... […] “In my recent book I talked about how I believe the neocortex works which is a connection/ system that is somewhat different regarding the deep neural Networks, it’s a hierarchy of modules that can recognize a pattern. I estimate we have about 300 million of those modules and recreate the hierarchy that recognizes with our own thinking” Ray then continues talking about the GO championship Bob had mentioned, saying that in GO you would actually have to deal with a sequence of moves that expands radically, having hundreds of moves available at each time, so the levels of pattern recognition have to be really deep to assess the board and know logically if you are winning or losing, and play accordingly. Recent breakthroughs in AI technology give the computers the ability to assess those situations. The Google GO playing program perfected itself by playing with itself to generate the training data and then it could assess the moves based on the outcome of these simulated games. Bob then addresses what he calls “the new wave of the techno pessimists”. People out there, saying “where’s my jetpack”, coming out and arguing that things haven’t changed that much. Ray says that there has always been people that can make arguments in the face of all reason. We’ve seen the rise of internet, computers, AI, robotics, and we are seeing machines do things like driving cars, that would make absurd to say that this have not been transformative changes. “[…] We have always used our machines to extend our own reach and leverage our muscles. Unaided human muscles couldn’t create skyscrapers. We can now access all of human knowledge with a few keystrokes, how many people can do their work without the brain extenders we already have? These will become more and more profound and more and more intimately connected to us, so we’re becoming smarter…” 65% of the jobs today in America didn’t exist 25 years ago, let alone a hundred years ago, and we keep increasing the sophistication of jobs. We enhance our intelligence not only with education, but by merging with intelligent machines. “Ultimately, we will connect our brains to all this technology and extend our physical and mental reach…” Bob then mentions Genomics, the potential to cure long-standing diseases like cancer or diabetes, and continues expressing his feelings about the potential of all new technologies like quantum computing or robotics, and questions Ray about the best way to make people aware
  40. 40. An Interview with Ray Kurzweil 40 of all these positive changes. Ray then goes on talking about the consequences of the readiness that we have of information around the world, as communications get exponentially better, every time we plug into the news you get to know what’s negative or what disaster is happening right now, and that influences our perception vastly. Ray affirms that that’s one of the things that keep the whole pessimistic wave alive. “15 years ago, search engines were just getting started, and know thinking of a world without them sounds like ancient history”, says Ray. “We very quickly get used to the positive things, looking at the future and change is always threatening because we don’t immediately have an answer…” We’re moving up Maslow’s hierarchy, you know people were just involved with basic elements of survival centuries go. Because we are geared towards survival, we tend to be very alert to potential threats, to not just existential threats but even threats to our well-being, so for example it’s very easy for the media to report how many jobs have been lost. Bob mentions that since the 2008 financial crisis, we’ve all become behavioral economists essentially. Not just life expectancy, but there are a lot of good things happening. There are dozens of new jobs that didn’t exist only a couple of years ago, so humans keep going forward, concludes Bob. PARA PROFUNDIZAR RECOMENDAMOS VIDEO CHARLA https://www.youtube.com/watch?v=- lvAxU2PdpA MEDIA ACERCA DE DEEPMIND Y EL CAMPEONATO DE GO https://www.youtube.com/channel/ UCP7jMXSY2xbc3KCAE0MHQ-A HERRAMIENTAS http://www.singularity.com/ http://howtocreateamind.com/
  41. 41. The Future of Finance 41 Exponential Computing Brad Templeton, Director, the EFF & Founder, ClariNet Brad begins his speech saying he wants to talk about how Moore’s law is digitizing everything, and what’s happening in computing right now. Brad start talking about early adopters, which is the first component he states is necessary for innovation. Early adopters are the first consumers a certain new line of technology have, and they become the “fuel” for innovation. Other necessary component for innovation are Open platforms, according to Brad. “No matter what company you are, the smartest people in the world don’t work for you”, and Open platforms come here to break through that wall by allowing people to contribute what they learned back to the world, and even beat out Microsoft spending billions of dollars trying to do the same thing. Brad then goes on talking about how the internet was not an invention but an accident; the internet gives people the illusion that it’s free, but it’s nowhere near that, everyone pays a part, and this allows every idea to lift from the ground and become a reality. In the days of Netscape, they put up a camera on their fish tank, and around the world everyone thought it was very amusing to go and see fish on the other side of the planet. But had that been done on the old ways the network where you paid by the kilobyte for everything you used, they’ve gotten a big bill at the end of the month and those guys would have been called in to their bosses office and say why did I get this big bill so people can look at our fish? “All the intelligence of the internet breaks the idea of having intelligence in things, and give the network the intelligence it needs to be smart.” That smart network then allows anything, for instance smartphones, to innovate, to amplify the needs technology covers. Brad then goes forward stating that “If your business, your city is not software-based you may
  42. 42. Exponential Computing 42 not be a company soon. You now need information of 2023 to make a plan for 2025, because the world is changing fast.” NASA’s probe that have been sent to Pluto arrived last year, and by the time it took to get there Pluto was no longer a planet, but when it arrived, new software was already running in the probe that allowed it for new types of image and signal processing, things that weren’t even conceived by the people who launched the probe into space. That’s the value of software right there. Brad then talks about how bandwidth is widening its range and in the next few years, the 4 billion people that are now “disconnected” will be coming online, and that certainly is a number that can change how things are done. For instance, virtual/augmented reality and robotics may impact and even replace travel, likewise Ray’s speech before Brad’s. Facebook spent 2 billion dollars to acquire the Oculus Rift, company which was only 18 months old and it never ship the product, and so you’ve also may have seen some of the hype now about going beyond this - what’s called augmented or mixed reality where we actually bring things into the world that you’re in as though they’re real, and the most exciting company in this space is one called Magic Leap. Brad then talks about the advances this company is accomplishing, and how soon this technology is coming. Magic Leap raised 1.4 billion dollars to build this technology, the largest
  43. 43. The Future of Finance 43 private investment drowned in history. Microsoft will be shipping to developers their augmented reality glasses called Holo-Lens sometime around 2016. THE INTERNET OF THINGS (IOT). Brad says the “internet” is the wrong metaphor, this is more a convergence of technologies making it happen. The three technologies are sensors, computers and networking, and are getting cheaper and smaller every year. They’re getting to use less power, which is highly important in a world switching to renewable energy as we move forward. If you bought a phone recently, you’ve seen what happened to sensors because every company advertise it. Advances in computers have enable us to prototype cheaply; Raspberry Pi, not only really small, but it’s also $5 dollars. How will the world change when supercomputing shows up in that price tag? Regarding networking, it’s interesting how many formats and standards are out there. Very long distance low power communication, or Bluetooth energy format, which has been in our phones for a couple of years now. There’s a lot of hype around IOT according to Brad, and highlights what are the things that will become important in the next couple of years, and for instance, industrial application will give the ability to gain value with just a really low cost of investment and implementation of sensors and networking. Supply chain companies are another area where we should focus. Brad also talks about wearables, and makes the comparison on how on healthy people, there’s still low value on most of wearables or IOT related stuff, but there’s a lot of potential when you have already a condition, such as pill bottle caps that know when you have taken the pills, and can help someone track their medications, or even wearables designed for their condition. “One thing I think we’re going to be able to do with all these cheap sensors is copy our friends here at Google…” Google came up with a very interesting philosophy of running a big server and instead of buying enterprise-grade hard drives and enterprise-grade everything as everyone else was told to do they bought the cheapest they could find in the marketplace and they expected it to fail, and they designed it so that it just failed and it made a notification, and the drives had to be changes, but costumers didn’t notice, because of how the system was designed. They made the cheap perform better that the best, and allowed them to survive failure. “This is one of the great lessons that Google has taught the world…” says Brad. Brad then goes on his speech to talk about “Frictionless”. Making things so that you don’t observe the user interface anymore. Regarding Moore’s law, there’s certain types of problems. If you have to dig a ditch, and can hire 9 people, the ditch should be faster, but what about when you hire 1000 people? There’s a part where we can’t make the ditch faster, and that’s what happening with computers right now. Brad says that we have to start advancing towards quantum computing
  44. 44. Exponential Computing 44 can solve this type of problems, obeying the laws of quantum mechanics we are all familiar with. Problems like factoring large numbers in a short time can really change how things are viewed and done. For instance, all of our internet security is built around how it’s really hard for us right now to do that, including financial security. The energy industry will change because you’re not going to care about the power in your vehicle anymore and you’re not going to buy a car, you’re going to buy a ride. And when you do that suddenly all the energy equations change. A lot of cars are going to move to being electric and that means that the United States will stop importing oil. The value of real estate is driven by location, and the meaning of distance and location are going to change in a world where self-driving rides are available for twenty cents a kilometer less than a bus ticket, that’s what transportation is going to cost in the future. Moore’s Law is going to come to transportation. Retailers will change, Northern Europe is building delivery robots that will bring you anything in 30 minutes, not just a pizza, for less than a dollar. What if you can get anything in 30 minutes or less than a dollar? Do you even need to own things? What will this mean for the retailers of the world? PARA PROFUNDIZAR RECOMENDAMOS VIDEO CHARLA https://www.youtube.com/ watch?v=G9gfNR0Eiyo HERRAMIENTAS https://www.raspberrypi.org/ https://www.microsoft.com/microsoft- hololens/en-us https://www.oculus.com/
  45. 45. The Future of Finance 45 The Death of Products, When Everything Becomes a Service Marco Annunziata, Chief Economist & Executive Director of Global Market Insight, General Electric Company. Marco begins his speech reinforcing what other speakers haven been talking about the negativity subject, and he says he used to be like that, so he understands why people tend to be in that posture. He joined General Electric and started seeing more of what is happening in technology and that’s what he says he wants to talk about: How exponential change is beginning to permeate in the industrial industry, or what he calls “The next industrial revolution”. “This is going to be as big as the previous industrial revolution”, says Marco, mentioning the impact on the economy and jobs it is going to have. DIGITAL INDUSTRIAL TRANSFORMATION. The convergence of physical and analytical technologies. According to Marco, the most important in defining aspects are industrial assets becoming intelligent inter- connected devices, equipped with electronic sensors, resulting in insights of enormous amounts of data and allowing to understand and operate with greater efficiency. “You can now understand a lot better how a jet engine performs in different flight conditions so is it flying over the desert? Or is it flying over the oceans? What are the implications for taking different flight paths? Different strategies of taking off and landing so as to save fuel but also to improve the maintenance, and here is one thing which really changes: you start understanding these machines a lot better and move from reactive maintenance to preventive maintenance, fixing things before they break because you know what is going to go wrong 80/90% percent probability over the
  46. 46. The Death of Products, When Everything Becomes a Service 46 next two weeks…” This really gives you the sense of how once an industrial asset that becomes an intelligent input connected device, the functionality changes and it becomes something completely different. The smartphone we carry around today is completely different from the old phone, or think of what we’ve seen with a Tesla: you have a car that you drive back one evening from the office to home, you park it in your garage, and the morning after the car drives you to work because at night through software upgrade it’s become self-driving. This is what it means to have machines that through changes in software changing integrated functionality. Marco says his favorite example regarding renewable energy are Wind Turbines. There’s new intelligent and interconnected wind turbines can react to changes in weather. They can change the inclination of its blades so it catches the wind in a better way, but that’s only the first step. The second step is to realize that the way in which the first line of wind turbines intercept the wind impacts not just how much power they can produce, but also how the wind then passes through the second, and third line of turbines. What happens with intelligent wind turbines as the wind changes is that they literally talk to each other, and they react in a way which is coordinated so as to maximize the power output for the wind farm as a whole;
  47. 47. The Future of Finance 47 here you have team playing by machines. According to Marco, there is a reason why economies have been so pessimistic over the last few years even as digital innovation has accelerated. Today industry has been left behind; industrial productivity used to be 4%, over the last five years it’s going down to just 1%, and in the last few quarters it’s been even lower. Until now, the industrial world that has really missed the train of visual innovation because it needed more time for a critical mass of these innovations to find their way into industrial assets are now doing so. They are starting to build digital twins, which are essentially a software module of a generic machine. “Think of what’s happening in the consumer space, where services like Amazon, Netflix or Facebook increasingly know us, so they can recommend to us what we would probably like to read or to watch...” In the machine world that means knowing exactly every specific piece functioning and knowing in advance how it will perform and adapt in different circumstances, which means you can optimize the performance and reduce the risk of failure. “The important implication of this is if you are a company like General Electric, it shifts the focus from assets and products to services in outcomes because suddenly you’re no longer thinking in terms of producing a best-in-class machine and selling it to a customer and then the customer will do whatever they want, you’re focusing on the idea that thanks to these technologies what you’re really selling to your customers is outcomes, services and solutions…” It changes the game to a significant extent and as this concept starts to take hold across the industrial world. In the consumer space, we have companies like Uber and Airbnb that have enormous valuation even though they don’t really own any of the underlying assets which are being used to deliver the services they provide. Similarly, we have a company like Apple which makes a large amount of revenue out of its app services even though it’s just creating a few apps, so you’re moving to a world where even though the physical assets that have always been a vehicle for providing services, but now the focus really shifts to the services themselves. Marco says that it’s going to be interesting how this plays out, as companies will no longer sell the machines to the industry, but keep the ownership and allow the use of the assets to the customers, shifting the balance of risk. What happens when you have a third party that says “I can do this better”, and proceeds to buy the industrial assets and sell the use of them? Marco then reinforces that if the world is changing so much, maybe being big is not enough. “You have to start investing more in software, take digital technologies more seriously… The first question you must ask yourself when evaluating an investment is: How seriously are we taking the digital revolution? Are they investing in software?” Resuming the topic about energy discussed in previous conversation, Marco
  48. 48. The Death of Products, When Everything Becomes a Service 48 highlights how the digital and physical technologies help the consumer role evolve from one that just buys and consumes energy, to someone that not only buys and consumes, but can generate, store and sell back to the grid energy, and this puts in perspective the question: “How do I help different players in the energy game generate more value?” Marco continues by saying technological progress is getting the traditional lighting business out of business, and that they had to start thinking differently and combining years of research and knowledge to transcend said traditional industry. What happens when you can use the lighting system not only to transmit electricity, but also data and information. Lighting becomes the neural network. Intelligent lighting by GE helps each lightbulb become part of an enormous system that can help on numerous tasks across the globe, such as enhancing safety along the streets, monitor weather conditions or even pollution levels. If you are entering this digital industrial revolution where everything becomes his service, what kind of play can you run? 1. Figure out what your set of customers will be 2. Focus on what you are actually selling And how do you monetize this? With a new generation of customer service agreements where the value that you bring to the customer is generated by a combination of hardware and software. Marco also highlights the importance of maintaining the relationship with start- ups, because big companies have to start learning from companies that are nimble and flexible in a rapid changing environment. BRILLIANT FACTORY. Evolving the intelligent factory by applying sensors and interconnect all the factory floor by a smart network. Therefore, the factory floor is connected in smarter ways to the supply chain to distribution channels in a way that allows you to recalculate almost instantaneously, when something happens, how you should we optimize the flow of your supplies but also how you can reorganize the work on your factory floor to do this. It also has implications for the way we work: “We’re seeing that a lot of these technologies actually augmented the ability of workers at different levels of this distribution, so you have a specialized recognition on a factory floor or going out in the field to repair that machine, and this person is now carrying around a portable device (the equivalent of an iPad or a wearable device) that aids in training and day-to-day manual tasks.” The implication of this is that the workers who are not a computer scientist or engineers, will have ever disposal match greater abilities which will make them more productive and greater productivity means the ability to support the higher wages. Marco continues: “I do feel that we are at the point of the elbow of the exponential growth curve were over the next five to ten years you will see a larger number

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