Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Similar to Demystifying AI | Mathias Vercauteren | Keynote at AI 4 Business Summit | Brussels, 2019
Similar to Demystifying AI | Mathias Vercauteren | Keynote at AI 4 Business Summit | Brussels, 2019 (20)
Recently uploaded
Recently uploaded (20)
Demystifying AI | Mathias Vercauteren | Keynote at AI 4 Business Summit | Brussels, 2019
- 1. Demystifying AI A lot of companies aren't ready yet, are you? Mathias Vercauteren @mathiasvercaut
- 2. CHANGE YOUR MINDSET START YESTERDAY PUSH THE BOUNDARIES 3 KEY TAKEAWAYS
- 5. Most extraordinary time in human history
- 8. Every single company here is gonna transform in the next ten years.
- 10. Creative Arts
- 11. Energy
- 12. Financial
- 13. Healthcare
- 14. Manufacturing
- 15. Retail
- 16. Media
- 17. Services
- 18. Social Media
- 24. Demystify AI
- 25. There is a lot of excitement but also a lot of unnecessary hype about AI.
- 26. Artificial Narrow Intelligence Artificial General Intelligence do anything a human can dosmart speaker self-driving car web search AI in farming, factories, …
- 27. AI Bubble
- 28. AI as a black box
- 29. You think You’re ready for AI
- 30. Only 4% of the companies are actively using AI in ‘many processes and to enable advanced tasks’ © Artificial Intelligence in Europe. Belgium & Luxembourg: Outlook for 2019 and Beyond. Report commissioned by Microsoft and conducted by Ey.
- 31. CHANGE YOUR MINDSET START YESTERDAY PUSH THE BOUNDARIES 3 KEY TAKEAWAYS
- 32. What makes a great AI company? Andrew Ng 1. Strategic Data Acquisition 2. Unified Data Warehouses 3. Pervasive Automation 4. New roles and division of labor
- 34. Step 1: Execute pilot projects to gain momentum
- 35. Step 2: Build an in-house AI team
- 36. Step 3: Provide broad AI training
- 37. Step 4: Develop an AI strategy
- 38. Step 5: Develop internal and external communications
- 39. Five-step AI transformation playbook © Andrew Ng 1. Execute pilot projects to gain momentum 2. Build an in-house AI team 3. Provide broad AI training 4. Develop an AI strategy 5. Develop internal and external communications
- 41. Rethink your Strategies and Business Models THINK BIG THINK BIG
- 48. Key Performance Questions © Bernard Marr
- 53. Chatbot Tay
- 59. CHANGE YOUR MINDSET START YESTERDAY PUSH THE BOUNDARIES 3 KEY TAKEAWAYS
- 60. Sixties
- 61. WE CHOOSE TO GO TO THE MOON!
- 70. Buzz Aldrin, Astronaut The biggest benefit of Apollo was the inspiration it gave to a growing generation to get into science and aerospace. “
- 71. Companies fail because they do the wrong things or they aren't ambitious, not because of litigation or competition. Larry Page, Google “
- 75. PROJECT LOONBalloon powered internet for everyone
- 76. PROJECT WINGRapidly deliver products using flying vehicles
- 77. How to apply Moonshot Thinking to your company © Peter Diamandis
- 78. Step 1: Hire some 20-somethings to do some digging
- 79. THE STRIKE FORCE
- 80. Step 2: Question everything and everyone
- 81. Step 3: Generate Ideas. No limitations!
- 82. Step 4: Catalogue, prioritize and select
- 83. Step 5: Fund the best ideas and best teams
- 84. Moonshot Thinking applied 1. Hire Young Team 2. Question Everything 3. Generate Ideas 4. Catalogue & Select 5. Fund Best Ideas © Peter Diamandis
- 85. It’s often easier to make something 10 times better than it is to make it 10 percent better. Astro Teller, Google X “
- 87. WE CHOOSE TO GO TO AN AI DRIVEN WORLD!
- 88. In honor of AI. One giant leap for mankind.
Editor's Notes
- Thank you for having me. Thanks for the warm welcome.
- What I really want to accomplish in this talk today is to establish a change of mindset of how much abundance and opportunity there is right now and how AI plays a crucial role in it. And then, secondly, really get into the tactics and set up a framework of strategies that I think a lot of people here can take with them and push the boundaries of yourself, your team and your company. Let's go.
- Let me take you on a small trip to the future. Year is 2050, so 31 years from now…still in our lifespan.
- We're at a high school, more particular we’re in the history lesson of Mister Rubio. Subject of the lesson is: "Human inventions that changed the world and transformed life on the Earth.". According to Mister Rubio there were 5 main inventions that changed the world. 5. Electricity 4. The Wheel 3. Antibiotics 2. Robots 1. Artificial Intelligence, AI. Mister Rubio says, AI has been around for almost 100 years (remember, it’s 2050). But AI really boomed during the late Twenty Tens and especially during the Twenty Twenties.
- Back in 2019, he said, we were living during the most extraordinary time in human history.
- And it’s true, science fiction became science fact yesterday. I don't think any of us truly realize how powerful we are right now compared to a 20, 30 years ago. How we have access to the world's information, access to more wealth than any time ever in human history.
- Literally, a woman with a smartphone in Mongolia has access to more computational power and information than the heads of Nations had just a decade ago. People have no idea how fast the world is changing.
- Every single company here is gonna transform in the next ten years. And AI will be the main driver, together with exponential breakthrough technology. Artificial Intelligence is currently being used behind the scenes to optimize operations, inform business decisions and more important, to impact our everyday lives. To give you some examples from different industries:
- Starting off with the consumer good industry. Hello Barbie from Mattel uses natural language processing, machine learning and advanced analytics, to listens and responds to your child. Anheuser-Busch InBev is using AI to drive growth and innovation in such diverse tasks as pricing, supply chain, and back office.
- In the creative space. We have a new Chef in town, called Chef Watson from IBM. It’s an AI-enabled chef that helps you develop recipes and advise you on food combinations. Amper is an artificially intelligent music composer, producer, and performer and is the very first AI to compose and produced an entire music album.
- In the Energy sector: BP is using big data and AI, in combination with sensor data to improve operations and usage of resources. GE, General Electric, is also leveraging the same technologies to build an “internet of energy” and they’re working towards a vision of a “digital power plant.”
- In the Financial sector: You might have heard of KBC’s K’Ching, it’s a mobile banking app which uses an artificial intelligence chatbot to answer users’ questions. BNP Paribas launched ‘Smart Chaser’, an AI tool to boost its trade processing services.
- Personally, I’m very fond on the usage of AI within healthcare: Take the Chinese company Infervision for example, who’re using AI and deep learning to save lives. In China, there aren’t enough radiologists to keep up with the demand of reviewing 1.4 billion CT scans each year to look for early signs of lung cancer. Radiologists need to review hundreds of scans each day which is not only tedious, but human fatigue can lead to errors. Infervision uses deep learning to augment the work of radiologists to allow them to diagnose cancer more accurately and efficiently. On the other side of the world you have Atomwise, an American Company, who uses deep learning to shorten the process of discovering new drugs.
- In Manufacturing: You’re certainly familiar with the concept of self-driving cars. These cars, here you see Volvo cars Uber is using, are generating tons of data that can be used for predictive maintenance for example. And the AI tech revolution has hit farming as well. John Deere, famous tractor builder, acquired Blue River Technology who developed a solution that’s using machine learning to decide whether a plant is a pest and should be treated with pesticide or not. So John Deere is getting data-driven analytical tools and automation like AI into the hands of farmers.
- One of the biggest retail chains in the world Walmart, is rolling out the usage of shelf-scanning robots across its stores. And Amazon is working on its Amazon Go store concept, which is an AI-powered grocery store.
- You’re also familiar with Netflix, who’s using Big data analytics to predict what its customers will enjoy watching.
- This is the MagicBand wristband you get as a visitor in Disney. It serves as ID, hotel room key, tickets, FastPasses and payment system. But this wristband also produces of a lot of data that helps Disney anticipate guests’ needs and deliver an amazing, personalized experience.
- And finally, we use AI every single day in that little device in our pockets. Social media apps like Twitter, Facebook and Instagram are all using artificial intelligence behind the scenes to enhance their product. Whether it’s for targeting advertising, fighting cyberbullying or delete offensive comments, all these platforms are using big data and AI to create value.
- Current CEO of Google, Sundar Pichai, said that AI is more fundamental to humanity than fire or electricity and he may well be right. AI has become as self-evident as electricity of transistors and it’s disrupting the world in an exponential way. Moreover, it’s disrupting total industries, reshuffling the cards of the leading companies.
- You might recall the days of the local video store where you could go in and rent VHS tape or a DVD. A very know chain in Belgium was Videoland. In the US you had Blockbuster. Both share a similar track record. For them all was going well a decade ago, but as you can see that red line is creeping up, that’s Netflix. The same Netflix that’s using AI and who did jump onto the train of exponentially growing technology. The blue line, Blockbuster, dived into bankruptcy, it literally fell off a cliff.
- Similar story here: Kodak versus Instagram. Kodak, by 1996 was at the top of his game. But because Kodak ignored their initial business vision, which is preserving people’s memories, they experienced the same faith as Blockbuster. A decade later they filed for bankruptcy. The same moment that Instagram, another AI using company, disrupted the photo industry.
- This is what it looks like when a linear technology falls off a cliff and exponential technology thrives.
- And we see similar examples in other industries as well. The AI revolution we’re experiencing now together with the current evolutions in breakthrough technology and advancing techniques in the field of Machine Learning and Deep Learning is enabling existing companies to become the new leaders within their industry. But also awakens exponential entrepreneurs in their garages to disrupt the world. Exposing and threatening other, established companies to sudden drop and fall off the cliff.
- AI might be very powerful but let me take a step back and demystify it all.
- Because there is a lot of excitement but also a lot of unnecessary hype about AI.
- Because almost all the progress we are seeing in the AI today is Artificial Narrow Intelligence. These types of AI are basically one trick ponies but when you find the appropriate trick, this can be incredibly valuable. Artificial General Intelligence is the big deal, but we’re not there yet.
- Many companies today are getting disappointed that their investments in algorithms are not paying off. Does this mean AI is a bubble ready to burst? I don’t know. But there’re some voices within the data community that state so. Because first of all, amongst a lot of managers, there’s quite some confusion about what AI really means and covers. A lot of AI-related projects are done “because they are cool”, because it’s a novel technology which will enhance the visibility of their companies. They often start off with the expectation that the technology is needed to solve the problem. Furthermore, in many organizations, managers and data scientists do not speak the same language. There’s the business world and the data world alongside the IT world, and often these worlds are lacking a constructive dialogue needed to make progress.
- And more importantly, many organizations have leaders who blindly believe in the value of algorithms. A lot of people should be aware of these black box algorithms that they accept to make important business decisions. Especially if you’re in the insurance, legal or healthcare industry, you need to know what’s under the hood of the AI.
- So…all then boils down to this one question: are you ready for AI? You might think you’re ready. I think that a lot of companies aren't ready yet for AI.
- A recent study within Belgium & Luxembourg, showed that only 4% of the companies are actively using AI…so… still a long way to go.
- One year within AI technology, feels like a second. As exponential technology developments, like AI, are moving faster and becoming cheaper than ever before, it’s time for you to hop on the bandwagon and start yesterday. But how can you start yesterday? Starting to use a few neural networks or deep learning algorithms does not turn your company into an AI company. A shopping mall with a website, isn't the same thing as a first-class internet company like Amazon. So, what turns you into a great AI company? What are the prerequisites?
- According to Andrew Ng, who’s co-founder of Google Brain, was VP at Baidu AI group and adjunct prof at Stanford, 4 prerequisites characterize a great AI company. AI companies are very good at strategic data acquisition. Thinking through how to get data is a key part of the great AI companies. AI companies tend to have a unified data warehouses. If you have 50 different data warehouses under the control of 50 different Vice-Presidents, then it will be impossible for an engineer to get the data into one place so that they can connect the dots and spot the patterns. AI companies are very good at spotting automation opportunities. We're very good at saying, Oh! Let's insert the supervised learning algorithm here so we can automate this task. AI companies also have many new roles such as the Machine Learning Engineer for example, and new ways of dividing up tasks among different members of a team. So, according to Andrew characterize a great AI company. But how to turn into one? Becoming a good AI driven company requires a systematic process.
- Andrew Ng has created a five-step AI transformation playbook to become effective at using AI.
- Step one is to execute pilot projects to gain momentum. Just do a few small projects to get a better sense of what AI can or cannot do and get a better sense of what doing an AI project feels like. This you could do in house or you can also do with an outsource team.
- But eventually, you then need to do step two which is building an in house AI team and
- provide broad AI training, not just to the engineers but also to the managers, division leaders and executives.
- After doing this or as you're doing this, you have a better sense of what AI is and then it’s important for many companies to develop an AI strategy.
- Finally, align internal and external communications so that all your stakeholders from employees, customers and investors are aligned with how your company is navigating the rise of AI.
- It’s that easy. Right. Will your company become an AI leader in your industry if you follow the AI Transformation Playbook by the rules? According to me, not … It are very solid rules that indeed will help you get along, but I think you still lack something critical to make it a complete success. In wanting to become an AI-driven company (or even a data-driven company for that matter), you need to
- Think Big, Act Small Think Big, what do I mean by that. 3 things, the first:
- Rethink your strategies and business models Let me explain through an example.
- This is a picture of a late 19th century American Factory. We see people working on their benches and all the power in that factory is coming from a steam engine outside the building. The power comes in the factory and workers draw power from the drive shaft on the ceiling. This steam engine technology is determining the logic of the factory. Typical image for the first industrial revolution. By 1900 electric motors breakthrough, a new exponential and revolutionary technology which was part of the second industrial revolution, also known as the technological revolution. So entrepreneurs needed to rethink their factory and redesign their strategy and business model before somebody else did. So out was the big steam engine, in were hundred small electric motors powering machines through wires. And this evolution kept on going.
- Then robotics and automation came in the picture and we’re now even talking about the Fourth Industrial Revolution. Same is happing in other fields like customer service with the rise of chatbots and virtual assistants.
- So, the point is change. I see a lot of companies who keep putting the past on a pedestal and are afraid of the current and the future. You need to change, you own it to yourself and your company. Without the change, without adjusting, rethinking and adapting your strategies and business models you don't get the progress that you want and that change can hurt. But when you change everything then the technology will work for you.
- Second Think Big action is you need to start by asking the right questions. That's also what they teach you at school, right, when you need to write a paper or a thesis. The first thing you need to do is to determine your research question. If you don't have a targeted question, you don't have a research paper.
- Voltaire once advised to ‘judge of a man by his questions rather than by his answers’ Instead of asking questions first, we already provide answer, solutions, approaches. Shouldn't we do this...why don't we do that...Use this technology, or I use this technology which will solve all our problems. But which problems? That's not the right thing to do. In business, we often focus too much time on finding answers without asking the right questions.
- Nobel Prize winner Paul A. Samuelson makes this point when says ""Good questions outrank easy answers."
- You need to develop something what Bernard Marr calls, KPQ's or Key Performance Questions.
- Google for example is really using the power of Questions. Google’s ex-CEO Eric Schmidt once said: “We run the company by questions, not by answers.” So, as of tomorrow, start asking questions. What are your biggest problems? How can somebody put you out of business?
- Third and final Think Big action, answer your question by using Moonshot Thinking. In a nutshell this means you need to aim for a 10x improvement, instead of a 10% improvement. I'll elaborate on that just in while.
- Act Small. Act Small means you need to get your fundamentals right! AI systems are powered by machine learning, some by deep learning and others are rule based. All of them require a significant amount of clean data.
- Because garbage in, also means garbage out. If your data is bad or corrupted, really messy or biased, especially for labeled data, your machine learning tools (hence your AI system) is useless. All your investments down the drain.
- A nice example of this is chatbot Tay that Microsoft launched in 2016. Tay was a Twitter chatbot specialized in "conversational understanding." It was a chatbot that tweets like a teen, and the more you chat with Tay, the smarter it got, learning to engage people through "casual and playful conversation." It took less than 24 hours for Twitter to corrupt an innocent AI chatbot and turn it into a full blown racist. So data for me is one fundamental.
- A second one for me is people and culture.
- It's like Biz Stone, cofounder of Twitter, once told: "People First, Technology Second." Science and technology can uncover big solutions and unlock mind-blowing opportunities. But they take teams of bright and dedicated people chipping away at the problem day and night. So what drives someone to take on such a difficult, uncertain process and stick with it? It’s purpose.
- In 2014, Salim Ismail published a book called “Exponential Organizations”. In his book, Salim's team analyzed the 100 fastest growing organizations and looked for their key traits. They discovered every single company on the list had a MTP or a massive transformative purpose. MASSIVE, stands for being audaciously big and aspirational. TRANSFORMATIVE, can cause significant transformation to an industry, community, or to the planet. PURPOSE means there's a clear ""why"" behind the work being done. Something that unites and inspires action.
- Also remember that people are individuals, who change at different speeds. You have runners, joggers, walkers and people who just won’t run. You need to handle them all.
- So, people first, technology second. Let me give you one last metaphor on this. Everybody is familiar with the Belgian roads and the way the government is repairing them. If there's a hole or a crack in the road, you fill it up with stones and asphalt and problem solved. Hup to the next hole. What happens after a while, the fixed hole is becoming an even bigger hole than it was before it was fixed. So what's the best solution to fix a road surface. Scrap it, redesign it and rebuild it. More traffic will pass over a new smooth piece of road surface. What I mean with this metaphor is that you don't need to do AI for the purpose of doing AI. Don't use exponential technology as a band aid solution for your underlying bigger problems or to achieve quick wins.
- So think big, act small and use the five-step AI transformation playbook to get going.
- Who of you remembers the sixties? It was a period of possibilities, freedom, … A period of Big Ideas!
- You might also recall the speech of JFK in which he cites: "We choose to go to the moon, not because it's easy, but because it's hard."
- Those were radical ideas.
- And we dare to do it.
- We prepared
- Launched
- Took off
- Made it
- This technological endeavor
- launched a whole new era.
- Buzz Aldrin, the astronaut, once said that: "The biggest benefit of Apollo was the inspiration it gave to a growing generation to get into science and aerospace." But afterwards, we became less ambitious in space. NASA’s budgets dropped because the space race was won. Also in business big ideas were put aside, focus only on small ideas. Low risk, incremental. Everybody was trying hard to improve their business by 10 percent. But a 10 percent improvement means that you're doing the same thing as everybody else.
- According to Larry Page, companies fail because they do the wrong things or they aren't ambitious, not because of litigation or competition.
- What's the solution: Moonshot Thinking! Moonshot thinking is shooting for the moon. Moonshots live in the gray area between audacious projects and pure science fiction; they are 10X improvement, not 10%. Google X, the Moonshot Factory, is leading the 10X movement.
- How does Moonshot Thinking work at Google X? They take on global-scale problems, define radical solutions to those problems, and involve some form of breakthrough technology that could actually make them happen. They look for 10X improvements and solutions that will help one billion people. Here are some Moonshot example Google X is working on:
- Project Waymo - Technology for driverless cars
- Project Loon - Balloon powered internet for everyone
- Project Wing - Rapidly deliver products using flying vehicles
- You might think these are nice and cool examples…but you're not Google X, right. You probably own a company or not, do business as usual and are already very satisfied if you can make this year 10 percent better than last year. But this is about mindset! Whether you’re a local butcher or a corporate enterprise, Moonshot Thinking will help you win. So, how can you apply Moonshot Thinking to your company? I'll give you 5 steps.
- Step 1: Hire some 20-somethings to do some digging
- Create a Strike Force of young people. Why young people? They are smart, hard working, and naive. All the qualities you want in someone who’s trying to reinvent a system. Where do you find your strike force? They may already work for you, or they might be graduates, or a group of local entrepreneurs. Look for passion and curiosity. Form teams of three to five people.
- Step 2: Question everything and everyone Give the Strike Force 4-6 weeks to walk around your company and examine everything. Let them to talk to all employees, clients, suppliers, and so on. Everybody. And have them document the major challenges your company is having.
- Step 3: Generate Ideas. No limitations! Larry Page once said: "Good ideas are always crazy until they’re not.” So challenge your Strike Force to think about how the biggest challenges could be solved. Having no limitations is critical.
- Step 4: Catalogue, prioritize and select
- Finally, Step 5: Fund the best ideas and best teams Now you need to show your skin in the game. Fund the best ideas and the best teams to develop the solution either internal to your business, or as outside entrepreneurial endeavors. Either way, you win.
- These are 5 simple steps to start your Moonshot Thinking process and shoot for 10x.
- Astro Teller, who’s Captain of Moonshots at Google X, that’s his real job title by the way, once stated: It’s often easier to make something 10 times better than it is to make it 10 percent better.
- So, from climate change to transportation, from to protecting our oceans and forests to improving access to food and water, there’s no shortage of problems in the world, nor do we lack technologies. AI is here stay and to help us: what we need are more moonshots. Now take off, enjoy the ride and celebrate the win.
- To end with an adapted JFK quote: "We choose to go to an AI-driven world in this decade. Not because it's easy, but because it's hard."
- In honor of AI. One giant leap for mankind.