“The platform we have uses big data analytics and machine learning in the cloud to process and find all of the unknown malware, make it known and be able to block it,” says Scott Stevens, SVP, Global Systems Engineering at Palo Alto Networks. “We find 20-30 thousand brand new pieces of malware every day. We’re analyzing millions and millions of files every day to figure out which ones are malicious. Once we know, within five minutes we’re updating the security posture for all of our connected security devices globally.”
Scott Stevens, SVP, Global Systems Engineering at Palo Alto Networks, discusses how the company uses AI, machine learning, and big data to find and block malware for its customers in an interview with Jeff Frick of theCUBE which is covering RSA Conference 2019 in San Francisco:
We Find 20-30 Thousand New Pieces of Malware Every Day
There are two ways to think about artificial intelligence, machine learning, and big data analytics. The first is if we’re looking at how are we dealing with malware and finding unknown malware and blocking it, we’ve been doing that for years. The platform we have uses big data analytics and machine learning in the cloud to process and find all of the unknown malware, make it known and be able to block it.
We find 20-30 thousand brand new pieces of malware every day. We’re analyzing millions and millions of files every day to figure out which ones are malicious. Once we know, within five minutes we’re updating the security posture for all of our connected security devices globally.
Whether it’s endpoint software or it’s our inline next gen firewalls we’re updating all of our signatures so that the unknown is now known and the known can be blocked. That’s whether we’re watching to block the malware coming in or the command-and-control that’s using via DNS and URL to communicate and start whatever it’s going to do. You mentioned crypto lockers and there are all kinds of things that can happen. That’s one vector of using AI NML to prevent the ability for these attacks to succeed.
Machine Learning Uses Data Lake to Discover Malware
The other side of it is how do we then take some of the knowledge and the lessons we’ve learned for what we’ve been doing now for many years in discovering malware and apply that same AI NML locally to that customer so that they can detect very creative attacks very and evasive attacks or that insider threat that employee who’s behaving inappropriately but quietly.
We’ve announced over the last week what we call the cortex XDR set of offerings. That involves allowing the customer to build an aggregated data lake which uses the Zero Trust framework which tells us how to segment and also puts sensors in all the places of the network. This includes both network sensors an endpoint as we look at security the endpoint as well as the network links. Using those together we’re able to stitch those logs together in a data lake that machine learning can now be applied to on a customer by customer basis.
Maybe somebody was able to evade because they’re very creative or that insider threat again who isn’t breaking security rules but they’re being evasive. We can now find them through machine learning. The cool thing about Zero Trust is the prevention architecture that we needed for Zero Trust becomes the sensor architecture for this machine learning engine. You get dual purpose use out of the architecture of Zero Trust to solve both the in-line prevention and the response architecture that you need.
How Palo Alto Networks Blocks 30,000 New Pieces of Malware Daily
We’ve been talking about 5G for a very long time and now the opportunity is really here, says Kathrin Buvac, President and CSO of Nokia Enterprise. “We’ve said for a number of years that 5G will enable the Industrial Revolution.” Buvac added. “It’s clear that 5G has to be a lot more than mobility services. When I talk with enterprise customers I really do believe that these productivity gains that are spoken about are real. Operational efficiencies, process automation, all the way to dark factory operations to full autonomy, that is really what’s coming.”
We’ve been talking about 5G for a very long time and now the opportunity is really here. We’ve said for a number of years that 5G will enable the Industrial Revolution. It’s clear that 5G has to be a lot more than mobility services. When I talk with enterprise customers I really do believe that these productivity gains that are spoken about are real. Operational efficiencies, process automation, all the way to dark factory operations to full autonomy, that is really what’s coming.
Before we go to the deep depths of 5g technology I think they’re really two things. One is the convergence of IT and OT technologies. Enterprises need to bring their enterprise IT services and the operations technology together. That is not so easily done. The other thing is digital. Think about Amazon and Netflix and what they’ve done transforming physical goods, books into eBooks, and DVDs into streaming. That will not be possible unfortunately with Industry 4.0, meaning we cannot digitize a crane or a truck in a mine. That’s just not possible.
Industrial Digital Twins Powered Via 5G
What we will do is create digital copies of the big machines or robots. That is what we call the digital twins. What that has to do with 5G technology is that it all starts in connecting these sensors, these machines, these robots, these devices, the co-workers in the factories, in the minds, and in the energy networks. That is where ultimately we will need 5G technology because of the big promise of lower latencies or higher bandwidth capacity, etc.
I think there are a few geographies that are leading the industrial automation. I would say from our standpoint it’s clearly the US. It is clearly Germany where car manufacturing and many manufacturing opportunities are coming. It’s Japan and it’s a few other geographies across the globe that are really leading the pack right now in terms of the Fourth Industrial Revolution that we have to look into.
The Industrial Opportunity is Striking
One thing that is striking me is the industrial opportunity. Over 15 million industrial sites will be deployed in the next decade. We have today 6.5 to 7 million base stations deployed in LTE worldwide. So it’s more than double the number of industrial sites that we somehow all together need to deploy to enable IoT. How are we going to do that?
There is the issue of spectrum availability. We have to be super creative, whether that is shared license, CBRS, 3.5, large scale carrier subleasing spectrum, and making money through that. It’s so critical and that also determines which country, which geography, which enterprise customer will go first. Industrial devices will just not be as quickly available as the smartphone’s which will be made available this year. There is still a lag.
5G Is a Complete Redefinition of the Network
5G is a complete redefinition of the network. We have all discussed AI, edge, and cloud. But we have to bridge now for a couple of years for enterprise customers as we take them to 5G. The question is really because enterprise customers want to leverage productivity gains now, not tomorrow, like yesterday. The question is really how do we do that? Can we potentially provide private wireless networks, with the help of our telco customers, to enterprises that can then just be a software upgrade to 5G? We would do this while we deploy industrial sites today based on LTE technology.
Enterprise customers are wired a little bit differently than us consumers. think about uplink video. We’re just so used to down-linking from tablets as consumers. We need a lot of uplink capacity if we use email or if we browse. If for a millisecond the network doesn’t work it bothers us, but it’s not the end of the world. But we need six nines reliability in the network in order to make sure we have the unmanned vehicles in the mines or the robots and the factories running precisely with that accuracy. A lot of work is needed still to get the 5G networks where they need to be, but it’s really exciting times to build that infrastructure.
Smart managers are the backbone of any business – but when leadership is running on empty, things can start falling through the cracks. When tasks begin piling up and managers’ attention is pulled in every direction, AI tools can step in to help.
Leadership roles in departments from payroll to administration services face up to 96% chance for computerization in the near future. But automation overhaul isn’t exactly a new concept; retail workers, service industry staff and everything in between has fallen risk to AI-replacement. Why should managerial work be any different? Machines can gather information, analyze the data, learn from past events, and most importantly, recommend solutions in the same way a human manager could, albeit much faster. But reliance on such programs doesn’t necessarily mean we are without responsibility; too much pressure on automation can lead to disastrous outcomes.
For Amazon, this took form in their “state of the art” hiring AI that was built to help fast-track the hiring process. With already over 600,000 employees on payroll, hiring is a big job for Amazon and this AI algorithm was expected to change the game. Until it didn’t. In order to teach the algorithm, it was fed ten years worth of resumes to identify successful hiring patterns. The previously male-dominated industry was evident in these successful hires and as development continued, the algorithm began to pick up on the pattern of gender discrimination. By 2018, the program was scrapped as the AI began penalizing resumes including the word “women” and filtering out listings of all-female colleges.
Hiring is perhaps one of the most personal and one of the most difficult of all business operations, especially for small business. Today, over half of small businesses use some form of tech to help move along recruiting, but smart leaders know there’s no substitute for a meaningful, in-person interview. The takeaway for automated management and its imitations is along a similar vein to AI in any other position – it simply lacks the human touch. So when office managers and project managers are spending their creative energies on mundane and repeatable tasks, they cannot away lead their team effectively. Here’s the AI that changes everything.
AI gives us a great opportunity to truly “work smarter, not harder.” Products specifically designed to reshape office management, like Managed By Q, turn regular tasks into a localized and cohesive platform. In this program, managing scheduling from maintenance to interviews is a snap, employees may submit requests with minimal workflow interruptions, and booking, communication, and billing are handled on a single place. Project management standards get a new look as well with AI tools that help break up even the most complicated projects into simple, easily achievable tasks. iCEO is one such platform that not only helps keep traditional employees on task and in communication but also communicated with freelancers and gig workers to manage progress that keeps everyone on the same page.
More than four in five businesses believe they could benefit from bringing in better tech, but that’s only half the battle. In spite of this, one in five businesses thinks it’s just too much of a hassle to buy and implement new tech. Here’s where to start. This infographic details the powerful new tools of the trade for managers, how they are helping us lead our teams better, refocusing daily operations, and finally giving us the time to concentrate on what matters. Will AI replace your manager? Let us know in the comments.
We believe the Edge is the next frontier, says HPE CEO Antonio Neri. “When we talk about the enterprise of the future, we see an edge-centric, cloud-enabled, data-driven, enterprise,” notes Neri. “What that means is the cloud is moving closer to where the data is created. That’s driven by the use cases we see around us.”
Neri adds: “Whether it is healthcare, manufacturing, or transportation, everything is being connected. It started with connectivity and then soon after that is the security aspect. One thing is connecting devices and apps and one thing is connecting things to the network. That’s why our Aruba platform is such a unique asset because it provides connectivity and security with AI built-in at the core.”
Driving the Acceleration of the Digital Transformation
I would like to characterize that we had another strong quarter for the company. That’s further evidence that our strategy is working to accelerate the Intelligent Edge and to drive profitable growth in the core segment of the market called Hybrid IT. Because we are continuing to build our portfolio and we see the demand steady, we’re actually very confident to raise our guidance that we obviously beat in Q1. We see the rest of fiscal year 2019 as strong for us and give us the confidence to raise the guidance driven by the portfolio and the innovation we have and in the feedback we get from customers.
We see the demand steady. We have not seen any evidence of a downturn (due to tariffs, shutdown, etc.). Obviously, we are continuing to monitor the uncertainties around the globe, but the reality is that customers are making critical investment to drive that acceleration of the digital transformation. That’s all driven by the fact that the data around us has continued to grow. They need to extract the value of that data much faster than ever before. That’s why we see growth in segments like high performance compute, which for us grew 50 percent. Software around infrastructure grew 70 percent. Also, the connectivity in the Edge grew 20 percent in the wireless business. We see that as a continued trend.
When people ask me what’s going on around the globe with Brexit, for example, our UK business actually grew double digits. When you think about the government shutdown, actually one of the key products we sell in the government is high-performance compute, and it actually grew triple digits. So it has not had the impact, but obviously, we continue to monitor what’s going on around the globe.
Next Frontier: Edge Centric, Cloud-Enabled, Data-Driven
We believe the Edge is the next frontier. When we talk about the enterprise of the future, we see an Edge centric cloud-enabled data-driven enterprise. What that means is the cloud is moving closer to where the data is created. That’s driven by the use cases we see around us. Whether it is healthcare, manufacturing, or transportation, everything is being connected. It started with connectivity and then soon after that is the security aspect. One thing is connecting devices and apps and one thing is connecting things to the network. That’s why our Aruba platform is such a unique asset because it provides connectivity and security with AI built-in at the core.
3 Cs of the Intelligent Edge
Ultimately, it brings that cloud computing closer to actually where the data is created. We think about it as an integrated solution. Obviously, we need to provide customers the tools to be able to protect themselves and be compliant with the new regulatory policies being put in place, like for example, GPI in Europe. We are really focused on that and we actually believe we have one of the best solutions at the Edge today. The data continues to outpace the compute capacity and actually, 75 percent of that data is created at the Edge. That’s very exciting and that’s why I’m bullish about these Edge compute capabilities that the customers need going forward. It’s just physics.
AI is a Big Opportunity for Us
Two years from now we’re going to create twice the amount of data that we created in our entire human history. That data needs to be stored, it needs to be managed, it needs to be compliant, and most importantly, business outcome has to be derived. That’s why we see the need to bring that cloud compute closer to where the data is in a different form factor. We see AI as a big opportunity for us and all integrated with connectivity and security.
Customers are telling us that they are accelerating the digital transformation. We have a saying that the future belongs to the fast. People who can extract insights from the data faster are going to continue to win. We are very bullish about it because we have one of the best portfolios we ever had and our innovation is second to none.
The US is Ahead with 5G
5G is going to be an exciting opportunity for us. The US is ahead and is going to be one of the first countries, if not the first country together with Japan and others, to roll out 5G. We already see evidence of that. Our opportunity with 5G is to provide customers an integrated experience. 5G is a type of connectivity, but it is not the only type of connectivity. You are talking about 5G, talking about wire connectivity, you talk about wired network connectivity or wireless connectivity.
What customers are asking us is give me one integrated experience with one security control play. That’s where Aruba fits perfectly in that we’re going to provide a cloud-based solution that integrates 5G into that experience.
AI, machine learning, and robotics are fundamentally changing healthcare, says Johnson & Johnson CEO Alex Gorsky. “One of the most exciting parts of my job right now is to see the technology that’s usually equated with California and the West Coast,” said Gorsky. “Whether it’s AI, machine learning or robotics, you’re seeing it more and more being integrated into healthcare.”
AI, Machine Learning, Robotics Integrated Into Healthcare
One of the most exciting parts of my job right now is to see the technology that’s usually equated with California and the West Coast. Whether it’s AI, machine learning or robotics, you’re seeing it more and more being integrated into healthcare. With this remarkable partnership that we have now with Apple where we’re taking this technology built into the iWatch to help detect things like atrial fibrillation or when you get a heart fluttering earlier. We know that there are over 35 million people around the world that suffer from this condition.
If we can detect that earlier we can get them to write medication and we can help them be compliant on these medications over a longer period of time. Ultimately we’re going to save lives. I think it really shows how some of this new technology is coming to healthcare in new, innovative, and unique ways. We couldn’t have even imagined this just a few years ago. We’re talking about algorithms that are built into the watch that are monitoring health in real-time. It can detect these anomalies far before something really manifests itself that the patient’s going to recognize in the terms of symptoms.
Auris (recently acquired) is another great example of how this technology is fundamentally changing the way we’re thinking about healthcare. Today, less than five percent of surgeries are done with a robot or digitally. In the future, we think that’s going to be significantly greater. What we’re so excited about is just as technology has changed the way that we drive a car, where you pull up your map system or you see that light go on if you start to change lanes, think about that in surgery.
Robotics Technology via Auris is Fundamentally Changing Healthcare
Suddenly, a surgeon can go in preoperatively, utilized imaging to help him or her really navigate their way specifically to the lesion, and they can actually get guidance. We know that’s going to lead to better precision, better outcomes for the patient, and better value overall for the healthcare system.
Healthcare Being Reinvented by Technology
Think of it, for example, with our Auris Monarch Platform which is used for something called bronchoscopy. Now, if you happen to have a lesion or a tumor at a very far out section in your lung, they, of course, would have to go in through minimally invasive surgery to do a biopsy to better diagnose what you have. Imagine we take a tree and turn it upside down and that tree is your lung. We can run this wire down through the system, way out to the outer ends of the leaf. Think of it almost like the acorn.
Once we get there we can do a biopsy or we can use imaging in the future to actually determine what kind of a cancer it is, or we could deliver a therapeutic, perhaps a new kind of immuno-oncology agent to that specific lesion, or we could go ahead and cut it out. Those are the kinds of things are being made possible by this new technology at a company like Auris.
AI, Machine Learning, and Robotics Are Fundamentally Changing Healthcare
The CEO of Geek+ Robotics Robotics, a China-based company, says they don’t see any strong competition outside of China and this includes the United States. “We’ve already entered Japan, Europe, Australia, and the United States and we are seeing a big demand for robotics and automation,” said Zheng Yong. “We almost cannot see any strong competitor outside of China.”
We think the market potential is quite high. We hope in the next four years we can deliver 20,000 to 50,000 robots per year. Our customers come from two directions. One is the retail companies including ecommerce. The second direction is the manufacturing companies.
There is very strong competition in China with lots of strong robotics companies that are growing very fast. We are not only starting automation solutions with robots to our customers, but we also provide logistic service to our customers. We own a lot of operational experiences and we combine those experiences inside our system. We have a lot of data and that will be a long-term advantage.
No Strong Competitor Outside of China
We haven’t got any money from the Chinese government directly. But because the government is promoting this concept in their Made in China Industrial Plan it can help us in the market. Overseas expansion will be our first priority next year. We’ve already entered Japan, Europe, Australia, and the United States and we are seeing a big demand for robotics and automation. We almost cannot see any strong competitor outside of China.
Our business is being impacted by the trade sanctions, taxes are higher. Our plan to grow our business in the United States is a little bit slowed down. We want to see the results of the trade conference between China and the US.
About Geek+ Robotic
Focusing on Logistics and Warehousing, Geek+ leads the technology revolution, by applying advanced robotics and AI technologies to realize high-flexibility and intelligent logistics automation solution. Geek+ provides leading, reliable, one-stop enterprise-level service with strong technological strength, precise customer understanding, thorough after-sales service, and ISO 9001: 2008 quality system.
Geek+ R&D team consists of Ph.D. and master graduates from Tsinghua, PKU, CAS, BEIHANG, USTB, etc., with much solid research and practice experience in the fields of robotics, embedded development, software engineering, artificial intelligence, most of them have joined domestic/international robotic contests and won the championship. All products are developed independently and possess the core patents, with a world-class level performance.
Domino’s software engineers and digital ad team have created a unique AI-powered ‘Piedentifier’ to launch it’s Super Bowl week marketing blitz. Domino’s is encouraging people to send in a photo of any pizza, even if you made it yourself, and it’s system will determine what type of pizza it is and give you ten points toward a free pizza in their rewards program.
‘Piedentifier’ launching for Super Bowl week marketing blitz
We’re going to give Piece of the Pie Rewards points for any pizza. Our customers are going to be able to use our great technology to take a picture of any pizza, send it up to us, and earn ten points toward a free Domino’s Pizza. The great thing about this is our team got together and created something called the ‘Piedentifier.’ What it does is it uses your phone to look for what they have referred to as the open-faced expression of crust sauce and cheese. Anything that looks like a pizza and you’re getting ten points.
Today we’ve got more than 20 million active members of our Piece of the Pie Rewards program. We don’t know the exact number of how many customers will come on board with us, but as the leader in the pizza category, we see this as a great opportunity not only to grow the overall pizza category, but also to invite new customers in to download our app and to try our product. We feel that when customers try our product we’ve got the opportunity to bring them back again and again.
This Sunday is a huge day for us. On Super Bowl Sunday, we’re typically up about 40 percent over a normal Sunday. We’ll sell about 2 million pizzas and about four million chicken wings. Each year, it’s the biggest day of the year for us. It tends to not matter which teams are in the game. Certainly in individual cities maybe it does, but broadly across the US it’s a huge day no matter who’s playing.
Average Franchise Makes $140K Per Year EBITDA
Opening up a Domino’s Pizza store is still a terrific return for our franchisees. Across the globe cash on cash returns are better than three years in our business. Just a few weeks ago at our Investor Day, we released again our unit level average for our franchisees in the US. Once again it went up. We’re expecting it to be somewhere between $137,000 and $140,000 a unit in the US on EBITDA on a Domino’s Pizza store that you can open for $350,000.
Driving is Still a Great Opportunity
Driving for Domino’s is a great opportunity because of the volume that we do out of our stores. In a lot of cases, drivers are able to come in and earn a lot more than they can driving for some of these other businesses. As we continue to tighten down our territories through our fortressing program, it’s giving our drivers the opportunity to get more runs per hour. That means more tips per hour and in turn, higher wages.
In addition to a job that earns a decent wage driving at Domino’s is also an opportunity potentially to be a franchisee in the long term. Over 90 percent of our franchisees today started as drivers or started in as CSRs answering our phones in our stores.
Self-Driving Cars Will be Here Someday
Self-driving cars will be here someday. We don’t exactly know what day but we’re working hard to really try to understand how our customer interface with that car when it pulls up to their curb. They’re used to having a uniformed Domino’s pizza delivery expert bring that pizza to the door. So we’re learning. As the technology evolves we’re going to learn how the customer wants to interact with us and we’ll be ready when it does get here.
Aurora CEO Chris Urmson says that there is this amazing opportunity to go and take the next step in democratizing transportation. Aurora, an independent autonomous vehicle technology startup, has secured over $530 million in funding led by Sequoia, Amazon, and T. Rowe Price. The inclusion of Amazon in this round raises the prospect that Aurora will help power Amazon’s well-known ambitions to provide autonomous delivery.
“This is a company that is a technology giant and they’re a massive logistics company,” says Aurora co-founder and CEO Chris Urmson. “We’re just excited to have them as a partner and we’ll see if we can make them a customer at some point.”
Chris Urmson, Co-founder & CEO of autonomous vehicle technology startup Aurora, discussed the most recent investment in the company and the future of driverless technology in an interview with Bloomberg Technology:
It’s Amazing to Have a Great Partner in Amazon
It’s amazing to have a great partner in Amazon. This is a company that is a technology giant and they’re a massive logistics company. We’re just excited to have them as a partner and we’ll see if we can make them a customer at some point. I can’t really speak to Amazon but let me tell you how we think about it. At Aurora we’re building a driver and that driver can move people and ultimately it will move goods as well. We look at Amazon and see this incredible logistics company and we look at an opportunity to help them with that over time.
We’re really excited about the investment in Aurora. That’s an incredible vote of confidence for us as a young company. The folks we have around the table with Sequoia and Amazon and T. Rowe Price is great. We’re going to spend it on hiring great people and bringing it in. This is a big problem and we need lots of people and that’ll be a big part of it.
We’re Building a Driver
We’re building a driver and the idea is you should be able to get in your car and sit back read a book or have a nap and get from A to B. We’ve been at it for about two years now and we’ve got this great group of people who’ve joined us, so we’re about 200 people now. It’s just exciting to see the progress we’re making on the software. We’re still developing it so we don’t have a product yet that we ship to customers, but our test team is out on the roads. We’ve got vehicles on the roads in California and Pennsylvania as well.
I think our approach is probably similar to the way that Google is approaching it. They’re building a driver and they’re integrating that. They’re buying vehicles from people and then doing what they’re going to do with it. Our model was to do the thing that we can be the best in the world at, and we think that is building that driving capability. Then we go and work with companies like Volkswagen and Hyundai and ultimately with other companies in the transportation sector. What we’re really excited about though is that we’re actually an independent player. So people that are working with us have confidence that we’re going to be supporting them and their interests.
Aurora is Democratizing Transportation
What we’re seeing is this technology that has an incredible opportunity to save lives and make the roads more efficient and make it less expensive and more accessible to get around. Like anything that’s going to be transformational, it takes a while. It’s a new technology and it’s bridging between two industries, between the technology industry and the automotive industry. Anytime you have that level of complexity it takes a while to figure it out.
We look at it and we see this incredible green field. There’s this amazing opportunity to go and take the next step in democratizing transportation. We’re going to be there with our partners and we think there’s lots of room for others to play too.
Heart of the Technology is Anticipation
I think the heart of the technology is really anticipating how others are going to drive on the road. Our vehicles today do a good job of seeing other people, whether it’s a pedestrian or cyclist or another car, and then it’s anticipating what they are about to do next. Are they about to step in the road? Is that vehicle about to make a lane change in front of us? If you can do that well then you become what we talk about as a defensive driver and you avoid these kinds of catch-22 situations.
There are subtle cues. As a car’s driving along, even if it doesn’t turn on the turn signal, if it starts to drift in the lane it might be about to make a lane change. If you’re approaching an intersection it might be that some car wants to make a move over. Part of the magic of this technology is getting to the point where we’re picking up those subtle cues in the software and then reacting to them safely.
Car makers are recognizing that this is an important technology. They see this as part of their future. For many of them, they’re going to move from being car makers to companies that provide mobility. The key ingredient to that is having a driver in their system and that’s what Aurora brings to them.
Aurora is Democratizing Transportation, Says Aurora CEO Chris Urmson
The future of fintech is cloud, AI, blockchain, IoT, 6G and quantum computing, says Anton Ruddenklau, Global Co‐leader of FinTech at KPMG. Those are the technologies that are fueling the digital transformation and will be central to financial services in the UK and the world going forward.
Anton Ruddenklau, Global Co‐leader of FinTech at KPMG discusses the future of fintech in an interview by Charlie Barrett, who is the FinTech Lead at AWS:
By 2027 Large UK Banks Will Go Cloud Native
The first tipping point is 2027. That is the date that IDC predicted when large UK corporate banks go cloud-native. They base it on spend analysis they get from CIOs across the industry. They say that 75 percent of the industry would have gone cloud native, the other 25 percent would have gone bust. There is an interesting thing.
Just as a sidebar, we’ve seen one CEO who has already been fired in the last couple of weeks because they didn’t actually adhere to their cloud strategy, and that’s Sage. So it’s starting. People are getting serious about cloud.
If you move back from those dates, what do the CIOs say? By 2020 they will spend more money on cloud services and data than they will on legacy technology. That’s a big tipping point for us and the cloud providers in the industry full stop. By 2022 the analysis shows that people will spend more money and resources on digital propositions and products supported by data and cloud than they will on legacy. We are moving to really a digital economy on financial services.
Blockchain, IoT, 6G, and Quantum Computing
The other one is blockchain which we think which is roughly between 2022 and 2024. That will be predicated on a number of things. Our tipping point analysis shows that ten percent of consumers and SMEs will have adopted distributed ledger cryptocurrency and that whole gamut of tokenization.
Then the internet of things (IoT). The new 6G is coming down from the mobile operators which is specifically for sensor technology and location based services. That’s sort of early 2020s. That will really fuel up the connection of machine to machine and all the things we want to see as consumers coming through.
Quantum computing is also a big one that is a big question mark for people. It’s super nascent right now. If we believe what people are saying to us, by 2024 or 2025 the quantum will arrive and that will just change the bandwidth for everything including the distributed ledger which really needs a lot of power to really make it work at scale.
Machine Learning Baked Into Cloud Services
More nearterm, I think for us is machine learning being baked into cloud services and cloud data warehouses? We see the likes of Amazon really moving hard on that and bringing machine learning to the masses. You don’t need to be a data scientist to do it. I think that is a fundamental change that’s coming. The small and medium sized fintech firms can adopt that a lot quicker.
However, they don’t have the distribution in scale. The opportunity for us is to get the large banks to understand that. It comes back to new types of skills and moving IT from the back office to the front office.
Starbucks has dramatically increased the use of AI-powered customer insights to drive growth, says Starbucks CEO Kevin Johnson. During the most recent holiday season, Starbucks made data-driven decisions on a variety of items from the type of holiday cups they were offering to how they promoted gift cards, all designed to increase sales. Johnson credits these new customer insights for improving gift card sales by four percent over last years holiday period.
Kevin Johnson, CEO of Starbucks, discussed in an interview on CNBC how analytics, artificial intelligence, personalization, and technology are now driving marketing, sales, and business decisions:
AI is Making Us a Better Company
We have dramatically stepped up the focus on customer insight. We are using technology to help inform us of what customers want, what they need, and what they think of Starbucks. That informed our entire holiday plan this year, and we had a fantastic holiday.
We are driving much more use of analytics, artificial intelligence, personalization, and technology to help us be more informed and more connected to our customers. That is making us a better company.
Customer Insights Driving Starbucks Growth
I’ll frame it around customer insights. Coming out of last year’s holiday we used a number of tools and research to give us customer insights on what customers really appreciated and loved about Starbucks at the holiday. That informed everything from the design of our cups to utilizing the reusable red cup promotion that we launched. We saw gift card sales grow four percent year-on-year in the quarter.
That was a function of customer insight and research that we did. This holiday, in many ways, was informed by that insight. That’s just an example of what we’re doing. We’re using all kinds of data, customer focus groups, and things to help us be more informed and more front-footed on the trends and the things that customers really want to see from Starbucks.
Toyota has introduced the hybrid P4 concept car that includes increased accident protection that is much “smarter” than its predecessor. Toyota says that with greater computing power, its systems can operate more machine learning algorithms in parallel for faster learning. They say it can process sensor inputs faster and react more quickly to the surrounding environment.
The technology was created by the Toyota Research Institute (TRI) as part of their autonomous vehicle R&D. P4 adds two additional cameras to improve situational awareness on the sides and two new imaging sensors – one facing forward and one pointed to the rear – specifically designed for autonomous vehicles.
Toyota Research Institute Rolls Out P4 Automated Driving Test Vehicle at CES.
Additionally, the imaging sensors feature new chip technology with high dynamic range. The radar system has been optimized to improve the field of view, especially for close range detection around the vehicle perimeter. The LIDAR sensing system with eight scanning heads carries over from the previous test model, Platform 3.0, and morphs into the new vehicle design.
“If we are able to reduce technology that theoretically can reduce fatalities by ten-fold or perhaps even a hundred-fold we can make consumers and society safer,” says Bob Carter, Toyota North America Executive Vice President.
Bob Carter, North America Executive Vice President of Toyota, discussed the new Guardian technology at length on Fox Business:
Toyota P4 Concept Car With Guardian Technology
This is I believe our fourth or fifth year where we’re introducing our newest technology, particularly in the autonomous driving area, here at the Consumer Electronics Show. The vehicle we are introducing today is a concept car called P4. It’s our fourth platform. We are introducing what we call our Guardian technology. Guardian is considered the co-pilot sitting in the passenger seat for you.
We are going to demonstrate to the media today where we actually experience an accident on Interstate 80. What the Guardian technology does, it’s an offshoot of development for fully autonomous, is it monitors all the conditions around the car all the time. In the example of this one unfortunate accident that nobody was hurt in one car drifted into its lane into another car and then pushed it into the guardrail. This is a very typical situation.
Guardian Technology Takes Control Prior to Accidents
Our Guardian technology senses that and then momentarily takes the controls from the driver. This includes acceleration, braking, and steering. It can navigate the car out of the area of the accident and then immediately hand back the controls to the driver. The end result is that the driver is still in control of the car. He has the enjoyment of driving, yet in in unforeseen circumstance, technology can take over to avoid the accident.
It was developed by the Toyota Research Institute that we have in the Silicon Valley. They’re working on a number of different technologies for the future that we believe are really going to enhance the safety of society in the future. Unfortunately, it’s are something that does happen. In North America last year there were 40,000 fatalities on our roads.
Guardian Technology May Reduce Fatalities by Ten-Fold
If we are able to reduce technology that theoretically can reduce fatalities by ten-fold or perhaps even a hundred-fold we can make consumers and society safer. In fact, we are so convinced that this technology is the correct path for the future that we are opening up to other auto manufacturers. We would love to see every vehicle on the road today have this sort of technology available for consumers.
Last year, there were 17.2 million vehicles sold. Approximately one percent of those were full battery electric vehicles. We have a very robust system we use with hybrids which is a combination of our gasoline engines and electric. These have been on the market since 1997. We think it is going to take some time for the market to advance but later on next decade we believe electrification will become mainstream in the North American market.
“We’re massively going for the expansion into this multi-cloud world,” says Björn Goerke, SAP CTO & President of the SAP Cloud Platform. “We strongly believe that the world will remain hybrid for a number of years and we’re going in that same direction with the SAP Cloud Platform.”
Massively Going for Expansion Into Multi-Cloud World
We’re massively going for the expansion into this multi-cloud world. We strongly believe that hybrid clouds will play a major role in the coming years. If you also follow what the hyper scalars are doing, Amazon was the last one to announce an on-premises hybrid support model. We strongly believe that the world will remain hybrid for a number of years and we’re going in that same direction with the SAP Cloud Platform.
We announced partnerships with IBM and ANSYS already and there will be more coming. We’re totally committed to the multi-cloud strategy driving the kind of choice for customers that they demand. But then what we’re more and more focusing on is business services and business capabilities. It’s about micro services as well. It’s really about business functionality that customers expect from SAP. We are an enterprise solutions company.
It’s Really About No Code and Low Code Environments
With our broad spectrum of 25 industries we support all the lines of business within a corporation from core finance to HR to procurement, you name it. We are focused on a high level of functionality that we can expose via APIs and micro services on a cloud platform to allow customers to quickly reassemble and orchestrate customer specific differentiating solutions.
There is no other company out there in the market that has the opportunity to really deliver that on a broad scale worldwide to our corporate customers.
That’s where we’re heading and that’s where we’re investing. We’re working on simplifying the consumption of all of this. It’s really about no code and low code environments. You need to be able to plug and play and not always force people to really go down into the trenches and start heavy coding.
SAP Embedding Machine Learning Into Applications
Beyond that machine learning is all over and on everybody’s mind. What we’re doing is making sure that we can embed machine learning capabilities deep into the application solutions. It can’t be that every customer needs to hire dozens and even hundreds of data scientists to figure these things out.
The very unique opportunity that SAP has is to take our knowledge in business processes, take the large data sets we have with our customers, and bring machine learning right into the application for customers to consume out of the box.
RPA is a big topic as well of course. We believe that 50 percent of ERP processes you can potentially automate to the largest part within the next few years. We are heavily investing in those areas as well.
Focused on Security, Data Protection, and Privacy
Especially if you think about the level of connectivity and companies opening up their corporate environments more and more, clouds being on everybody’s mind, and the whole idea to make access to information processes available to everybody in the company and in the larger ecosystem at any point in time from anywhere, of course, that raises the bar that security has to deliver. So it’s a top of mind topic for everybody.
There are a lot of new challenges also from an architectural perspective with how these things are built and how you communicate, We have a long-standing history as an enterprise solution provider to know exactly what’s going on there. There’s security, there are data protection and privacy that companies have to comply with these days. I think we’re well positioned to serve our customers needs there.
Pandora is considered the world’s most powerful music discovery platform, using its proprietory algorithm to determine which music to play to a subscriber at any given time. The question is how do they do it so successfully?
Pandora’s Data Science Manager says that it’s not about AI and machine learning replacing humans. He says it’s about those two working together.
Using Data to Teach Computers How to Listen to Music
Music is an art form and behind it are certain objective properties, what instruments went into making it, the overall sound style, and artistic expressions of intent. It’s not just about objectively understanding music itself. We’re using that data to teach computers how to listen to music.
There are about 450 traits that we’re looking at for every song. Is it a breathy voice like Bjork or perhaps a smooth vocal like Shaday? Is there a swing or a shuffle feel to the beat or is there a lot of syncopation? There’s always this talk about AI and machine learning replacing humans when in reality it’s a loop. I think really a lot of the future is those two working together.
Challenge is Determining When to Introduce a New Song
The machine can tell you pretty well that someone’s singing in a piece of music. A machine might have a little harder time telling you what language that person is singing. The type of music we listen to and how we behave when we listen to it can really tell us a lot about ourselves. What do you do the first time you’ve ever heard a song? Are you open to it do you follow the mainstream or do you have very niche interest? Underlying all of those core behaviors are some really fundamental personality traits.
The challenge with music discovery is when is the right moment to hear a new song. That’s where you have to start learning about people. If you’re working and very concentrated you want to be listening to something familiar and hearing something you’ve never heard before is oftentimes a bit jarring.
Biggest Misconception About Music Streaming and Data
The biggest misconception about music streaming and data is that everything behind it is an algorithm. When we fundamentally think about how the algorithms work we have to think back to how we used to discover music before we had streaming services. We would listen to the radio or we would learn from our friends.
What’s at the heart of a lot of these algorithms is actually connecting you to all of the other people out there that you’re never ever going to meet. The trick then becomes how do you combine all of those sources of recommendations with your past listening behavior and with your current circumstance to pick the best song for you right now?
Working with the Google Developers Launchpad, BrainQ has developed a unique AI-powered brain-computer medical device, says their CEO, Yotam Drechsler. “It takes patients’ brainwaves as an input with a set of metadata and runs machine learning algorithms in the cloud and translates them into a tailored electromagnetic treatment aimed at facilitating their central nerve system recovery process,” says Drechsler.
BrainQ is developing an AI-based medical device aimed at getting powerless people following neural disorders, like stroke or spinal cord injury, back on their feet. Every single year, hundreds of millions of people around the world suffer from neural disorders. Stroke alone accounts for 15 million people every single year. And the entire neural disorders cost to the US economy is $1.5 trillion every single year.
My grandfather had a stroke several years ago. From being the center of the family, all of a sudden, he became paralyzed in half of his body. That means he can longer do simple things like grabbing a glass of water or dressing alone. That’s the reality for many people out there.
Using AI to Model Physical Therapy
The common treatment is what’s called physical therapy. It’s essentially exercising the hand or the leg back and forth. What BrainQ essentially does is modeling physical therapy and applying it directly to the brain. In a sense, we ask what happens for a patient or for a healthy person when he does a hand movement, like reaching his hand to grab a glass of water.
We are getting a lot of people to do these kinds of movements and then we learn the patterns. We take these patterns that we have learned and identified and reapply it back to him as a personalized treatment.
Developed Unique Brain-Computer Medical Device
We have developed a unique brain-computer interface-based medical device. It takes patients’ brainwaves as an input with a set of metadata and runs machine learning algorithms in the cloud and translates them into a tailored electromagnetic treatment aimed at facilitating their central nerve system recovery process.
We were very fortunate to have Google share this vision with us. We worked very closely with the GCP team on making this vision come true. We were fortunate to be on this program, and it really puts us on a fast track. And in all four fronts, we have developed the next generation of technology with precision medicine base, with the studio team, Peter Norvig, and the rest of the Googlers that were very, very keen in helping us.
We had a large funding round in the past couple of months and we have several collaborations in the pipeline. We are hoping to continue on this promising track and really bring cure to millions of people around the world. And we are fortunate to have Google with us on this journey.
Dr. Rand Hindi says that without emotional intelligence machines will never be able to obtain human-like artificial intelligence. Reminiscent of Data on Star Trek Next Generation, Hindi says that despite the impressive ability of machines to learn from other machines and to solve logic problems better than humans, most decisions humans make are actually emotionally driven and machines simply don’t have an emotional IQ.
I want to talk to you about the reason why I believe that human-like artificial intelligence is never going to exist and what that means for the future of work. Artificial intelligence is the ability to reproduce human behavior in a machine. That’s it. Take what a human can do intelligently, put it in a machine and you’ve got artificial intelligence.
Within AI you’ve got one type of way to achieve this which is called machine learning. The idea of machine learning is that you’re effectively teaching machines to reproduce the behavior by giving it examples. It’s a little bit like a kids book where you have pictures of animals and the name of the animal is written and then after seeing a few pictures of horses your kids know how to recognize horses. It’s exactly the same thing in machines.
Machine Learning is a Very Big Deal
Machine learning is a very big deal because up until now when you wanted to automate something a human had to first understand what was going on, then sit down and program a machine to do that. Automation was limited to what humans were able to understand. With machine learning all you need is data collected from what you’re trying to automate and the machine does everything else. You no longer need a human expert in the loop.
Within machine learning there is one type of algorithm that’s called deep learning. Deep learning is a branch of machine learning which is a branch of artificial intelligence and you could consider all three to be interchangeable today, but that’s going to change in the future. I don’t believe that word artificial intelligence is actually going to be used in marketing in the next few years.
Deep Learning Has Been a Huge Revolution
How have we been using deep learning? Deep learning has been a huge revolution. We see it happening for self-driving cars. We see it happening for medicine. Medicine is a very important use case for artificial intelligence because we have today AI that can diagnose x-rays or MRIs better than humans can.
You’ve probably heard about Alexa, the voice assistant from Amazon. This is one of the fastest growing consumer products ever. Rumors are that one in six Americans uses that. This was not possible before because deep learning was not enabling us to talk to machines as naturally speaking.
Is AI Getting Out of Control?
Let me tell you about the world champion playing against Google’s artificial intelligence at the game of Go. The game of Go was considered to be extremely complicated for an AI to beat because the number of different combinations meant that the only way for a machine to beat a human is to actually learn how to play the game. We thought this was still ten years in the future. The way that they made this work was really interesting.
They took one artificial intelligence and they made it play against another one. So one was playing the white side, one was playing the black side, but the trick is that every time one of the AI played a move the other one gave it feedback on that move. By mutually reinforcing each other by playing millions and millions of games, eventually they learned how to play the game better than any human.
At the time, when they played against a world champion the world champion won one out of five games so this was amazing. But people felt a little bit reassured, they were like a 20 percent chance of surviving AI that’s still not bad! However, the same AI kept on learning. Today, not a single human can beat that AI at a single game. But there is more, there is a new version of this AI that beats that AI that beats every human at every game.
When I saw that I was like, oh my god, this is just getting out of control, this is getting out of our hands. But what you need to understand is that everything I just talked about, however impressive it is, is still something that is called narrow artificial intelligence. Effectively, those machines are able to do one thing, perhaps do it better than a human, but they’re only doing this one specific thing. The AI that played the game of Go that was a breakthrough, but it doesn’t know how to do anything but play the game of Go.
Machines Will Never Have Emotional Intelligence
Now people are working on something that’s called general artificial intelligence. This idea that a machine could solve any logical task, that it could reason, that it could transfer the learning it had from something to something else. This is major because if you can have a general form of intelligence and reasoning then potentially machines could do anything that seems like intelligence.
But this is still not what you see in movies. What you see in movies is a very human-like artificial intelligence. It’s not just reasoning and logic, it also includes the ability to emotionally connect with humans. So artificial human intelligence is really this combination of logical intelligence and emotional intelligence. It’s IQ plus EQ. If you only take IQ into the equation you don’t end up having human intelligence.
Why is emotional intelligence important? It’s a way that as humans we can solve paradoxes. A paradox is a mathematical problem for which there is no logical solution. If a machine is not able to have emotional intelligence it will never be able to solve logical traps, which means as humans we can use our EQ to find traps for machines that have very high IQ.
You might be thinking that machines are building emotional intelligence as well. We see all those amazing robots, people develop feelings for those robots as well. However, I believe that you will never have true emotional intelligence in machines.
EQ First Requires Artificial Consciousness.
Emotional intelligence first requires artificial consciousness. They will also need to feel emotions. This is very different than pretending to have emotions. It’s very easy for me to learn that when someone is smiling that person is probably happy and it’s very easy for me to smile back. But hey, I can be smiling but it doesn’t mean I feel happy right now. There’s a big difference between perception of emotion, between display of emotion and feeling emotions.
We know that humans who don’t feel emotions are incapable of making decisions on a daily basis. They can do math, they can solve mathematical puzzles, so they have very high IQ potentially. But if you ask them what they would like for lunch they cannot answer because there is no algorithm to answer that question. Given that as humans most of our decisions are emotionally driven. Let’s be honest, we use the data to back it up but we make emotional decisions mostly. A machine that doesn’t have an emotional intelligence will never be seen as a human-like type of intelligence.
What I’m trying to get to here is that yes, you will have an AI that has an IQ of five billion and yes every logical task is potentially doable by a machine, but humans will have the monopoly on emotional intelligence. Humans alone will be able to do emotionally driven tasks and so rather than think about machines replacing humans we really have to start thinking about humans and machines working together.
How can we leverage the horizontal emotional intelligence of humans with the powerful mechanical logical intelligence of machines? Rather than try to build an AI that replaces humans completely, why don’t we start building an AI that actually works with a human in a very natural and very intuitive way.
One of the more interesting reveals that Dan Francis, Senior Product Manager for LinkedIn Talent Insights, provided in a recent talk about the Talent Insights tool is how LinkedIn is using machine learning to determine skills of people. He says that there are now over 575 million members in the LinkedIn database and there are 35,000 standardized skills in LinkedIn’s skills taxonomy. The way LinkedIn is figuring out what skills a member has is via machine learning technology.
LinkedIn Using Machine Learning to Determine Skills
The skills data in Talent Insights comes from a variety of sources, mainly from a member’s profile. There are over 35,000 standardized skills that we have in LinkedIn’s skills taxonomy, and the way we’re figuring out what skills a member has is using machine learning. We can identify skills that a member has that’s based on things that they explicitly added to their profile.
The other thing that we’ll do is look at the text of the profile. There’s a field of machine learning called natural language processing and we’re basically using that. It’s scanning through all the words that are on a member’s profile, and when we can determine that it’s pertaining to the member, as oppose the company or another subject, we’ll say okay, we think that this member has this skill. We also look at other attributes, like their title or the company, to make sure they actually are very likely to have that skill.
The last thing that we’ll do is look at the skills a member has and figure out what are skill relationships. So as an example, let’s say that a member has Ember, which is a type of JavaScript framework, since we know that they know Ember, they also know JavaScript. So if somebody’s running a search like that, we’ll surface them in the results. I think that the most important reason why this is helpful and the real benefit to users of the platform is when you’re searching, you want to get as accurate a view of the population as possible. What we’re trying to do is look at all the different signals that we possibly have to represent that view.
575 Million People on LinkedIn Globally and Adding 2 Per Second
Today, LinkedIn has over 575 million members that are on the platform globally. This is actually growing at a pretty rapid clip, so we’re adding about two members per second. One of the great things about LinkedIn is that we’re actually very well represented in terms of the professional workforce globally. If you look at the top 30 economies around the world, we actually have the majority of professionals in all of those economies.
LinkedIn is the World’s Largest Aggregator of Jobs
I think there’s often a perception that most of the data’s directly from LinkedIn, stuff that’s posted on LinkedIn and job status is one notable exception to that. Plenty of companies and people will post jobs on LinkedIn, and that’s information that does get surfaced. However, we’re also the world’s largest aggregator of jobs. At this point there are over 20 million jobs that are on LinkedIn.
The way that we’re getting that information is we’re working with over 40,000 partners. These are job boards, ATS’s, and direct customer relationships. We’re collecting all of those jobs, standardizing them, and showing them on our platform. The benefit is not just for displaying the data in Talent Insights, the benefit is also when members are searching on LinkedIn.com, we’re giving them as representative a view of the job market as possible.
What could change us from having to wrestle with physical devices? That was the question posed by Microsoft AI CTO Joseph Sirosh at the 2018 AI Summit in San Francisco. He was specifically referring to a prosthetic, but that is only an example of how Cloud AI Services could impact the usefulness of all devices.
Joseph Sirosh, AI CTO at Microsoft, talks about how a Cloud AI Service will eventually be driving every device:
Top Macro Trend: A Cloud AI Service Behind Every Device
The most important macro trend is a cloud AI service behind every device. It might be a prosthetic, it might be any device that you use in your house. Of course, your apps on your phone have AI services behind them eventually, some of them already have AI, but others well. Everything in the world that is connected with Wi-Fi or Internet connectivity can now be backed up by an AI service. That’s very powerful and profound when you think about it.
Now, think about this one, the grip classification (on a prosthetic). How it works is there’s a muscle sensor that I’ve attached to my arm here, there’s a camera in the hand. So, through the electronics, it goes to an Azure Custom Vision Service, where our classification model has been set up, a deep-learned model that recognizes objects and classifies it to the right action and then that triggers the appropriate grip classification in the Servo motors connected to an Arduino board in the arm.
The Magic Provided by a Cloud AI Service
Two undergraduates built this. Hamayal Choudhry from the University of Ontario Institute of Technology and Samin Khan from the University of Toronto. They did this for the Microsoft Imagine Cup. They were the winners in 2018. Building this took them a few weeks. Of course, then the magic was provided by a cloud AI service to be able to make this device intelligent. That’s a power. Even an undergraduate can build something as powerful as this today.
Why is this Revolutionary?
So, why is this revolutionary? Step back and think about this device. Look, there are over a million amputations per year. That’s an amputation every 30 seconds. WHO estimates that 30-100 million people in the world live with limb loss. Only 5 to 15 percent of these have access to prosthetics, even though prosthetic devices have been around since the Egyptian times. Even though these devices have been there, they have been purely physical devices and very severely limited. Limited by cost.
The bionic arms that you have heard about today, they cost tens of thousands of dollars and it takes a lot of effort to fit them on you. They’re limited by availability, very few people have access to it, and they’re limited by the interface you can attach to the body.
Breaking Physical Limits via Cloud AI Service
Above all, they’re limited by the nervous system that we have because we’ve got to train ourselves to use that device. In fact, literally, we had to force our will into these devices to be able to use them effectively. How could we change all of that? What could change us from having to wrestle with physical devices? How could we break these limits? The answer is an AI or a cloud AI service backing it up.
Think about this, what if you had low-cost electronics to build with it? What if we could change the game of availability with 3D printing? So, you can print these things anywhere in the world. What if you had a Cloud AI service behind it that provided the ability to recognize things and make the movements? What if it could be personalized? What if it could be adapted? What if other people, your friends could train your arm to make the right kind of movements, in the right kind of environments? How could you have customizability of all types? What if you could tap into the knowledge of the world beyond our senses through the cloud service so that you can keep improving it? What if all of these things came together for a very low cost like the $100 it took for this arm to be built?
That would be revolutionary, right? Imagine, now every prosthetic in the world or orthosis in the world which is, let’s say you break your arm and [inaudible] sling and you need assistance? What if you could get something very cheap that you could move around but it’s controlled by a Cloud AI service and all you have to do is express your intent to that Cloud AI service somehow and it does the more complex task of actually doing the grasp?
Affordable, Intelligent, Cloud-Powered and Personalized
See, this is the difference that the services can make. What you do is you express your intents and your constraints, and the service generates the behavior you need. So, it’s a generative service. The behavior is generated but from high-level intention that you communicate. So, the future is affordable, intelligent, cloud-powered, personalized, prosthetic devices and really devices of every type. That’s hugely revolutionary.
The world’s leading automotive alliance, Renault-Nissan-Mitsubishi, is spending a billion dollars over the next five years investing in technology-focused mobility startups. François Dossa, Head of Alliance Ventures, a strategic venture capital fund of the company, says that they want to invest money in the new technologies that will make the mobility of the future and the car of the future.
Our Sector is Suffering Not an Evolution, But a Revolution
We want to invest money in the new technologies that will make the mobility of the future and the car of the future. We take this very seriously because our sector is suffering not an evolution, but a revolution. We’ve been for years using a car always the same way, your two hands on the wheel and your view on the road, and this is going to change. Many new technologies that we will not develop internally because it would be too long and too expensive and this is why we have to rely on startups.
We are excited with everything related to mobility. In mobility, I can also think of my legs that will be a part of the mobility, so it will be multimodal, not only a car. If I want to go from A to B, I have to be able to use my legs, a bike, a scooter, a car, a train, a van, a bus, and all this together is going to be the new journey that our customer will have. Customers in the future will consider that we are a service company and this is the big change that we have to do. We are good at manufacturing cars and we have to be good at offering a service to our customers.
Should we have our own platform or should we use someone else’s platform? We decided to have our platform, so we’re going to build our platform and I’m in charge of that. On a platform are all the tech bricks that you need to have to offer, ride-hailing, ride pooling, ride sharing, and goods delivery to your customers.
My activity is not to acquire companies, it is to acquire shares in companies. I don’t want to be the owner. If I think of a start-up, if I acquire the startup I kill the startup. We are a company of 475,000 people, that’s a very big company, very kind of heavy company, and we need to keep the fact that in the startup they grow very fast. All these technologies they’re moving very fast. This is why I don’t want to acquire but I want to be part of the shareholder of the company.
What’s Happening in China is Just Amazing
China is the most amazing area in terms of innovation. Number one in the world. What’s happening in China is just amazing. We have been investing in a company called WeRide, it’s a level 4 autonomous startup in China. With level 4 I can tell you, I had a demo with their car in normal traffic conditions and the car goes on the highway and nobody is driving the car. My first reaction I was really dying. I was oh my god and we had 30 minutes and it worked extremely well.
That’s very clear and it’s something that I’d like to say. About 40 years ago the Japanese companies went to the States and to Europe, they copied what we were doing. Then ten years ago, the Chinese did this also. Now I think it’s our time to go to China to look at what they are doing and to copy, because if not they’re going to kill us. We have to be very cautious about China and there are a lot of opportunities especially in deep tech new technologies. With AI, the Chinese know exactly where they are going. They tell you well we have a plan, it’s the central government plan where they want to be in 5, 10, and 15 years.
AI is everywhere, so we have four main activities for investment. First one is the new mobility and this is the decision that we made about the platform. Then we have all related to autonomy, autonomous cars connectivity, and services. and EV, electric vehicles. We are the leader in EV and we want to keep this position, and we need to make a lot of investment and startups are very good at this.
The Key Driver is Really the Technology
Even though I’m not American, I think that money is very important. For me, money is important and it’s also a way to be sure that we invested in the right startups because they will grow and then we’ll make money out of this investment. But this is not the key driver. The key driver is really the technology. We are a strategic fund and so we are here to bring into the Alliance companies and the new technologies that will make this new mobility and this car of the future. That’s really really clear in our mind but we’ll make money also out of it.
About Alliance Ventures:
Alliance Ventures is a strategic venture capital fund of up to $1 billion over the next five years, operated by Renault-Nissan-Mitsubishi, the world’s leading automotive alliance.
The fund, launched in 2018, with a $200 million initial investment is co-located in Amsterdam, Silicon-Valley, Paris, Yokohama, Beijing and Tel Aviv from where it targets technology and business model innovation in New Mobility, Autonomous Driving, Connected Services, EV & Energy and Enterprise 2.0.
Alliance Ventures is the main interface with the Alliance and its member companies for start-ups, incubators, accelerators, investors and the venture capital eco-system. By drawing on expertise and business opportunities from across the world’s leading automotive alliance, we pursue strategic investments at all maturity stages in startups developing disruptive technologies or businesses, focusing mainly on Series A and B, plus follow-on investments to support the start-up’s growth.
Cloud adoption is just in the very early days says Salesforce co-CEO Keith Block. He says that over the last few years we’ve been in a perfect storm of cloud and mobile and data science and artificial intelligence coming together that have given companies the opportunity to reinvent themselves and reinvent their business models. Block says that this has been an incredible wave and a global phenomenon of digital transformation.
Keith Block, Salesforce co-CEO, discussed the global phenomenon of digital transformation in an interview on CNBC:
Cloud Adoption is Still in the Very Early Days
I believe we’re in early days. Salesforce will be celebrating its 20th anniversary very quickly and we’ve had a meteoric rise. We’ve been the fastest enterprise software company and in the top five software companies in terms of growth to $10 billion. We just gave our guidance to $13 billion and we’ll do $16 billion for next year. But cloud adoption is just in the very early days.
Incredible Wave, Global Phenomenon of Digital Transformation
What we’re really seeing right now is this incredible wave, this global phenomenon of digital transformation. Over the last few years, when you think about this conversion, this perfect storm of cloud and mobile and data science and artificial intelligence, these amazing technologies that have come together, it’s given companies the opportunity to reinvent themselves and reinvent their business models. I think classically of a company that is a B2B company that now wants to become a B2C company and that’s where Salesforce really plays beautifully in terms of getting closer to that customer.
MuleSoft Completes the Wave of Digital Transformation for our Customers
Specifically on MuleSoft. A great example is really having the holy grail of the 360-degree view of the customer, where you have information about the customer, where you can personalize the experience for the customer, where the customer feels like they are personally engaged with the companies that they do business with. MuleSoft is an amazing integration technology and we’re very lucky to have it. It really completes the wave of digital transformation for our customers in the sense that it’s allowing you to unlock data from any source.
Cloud Brings the Ability to be Agile, Nimble and Flexible
Think about decades of legacy data that have been built up and built up and built up and CEOs want to know how do we access that legacy data in a very agile and in a very quick fashion so we can serve it up to our systems of engagement? That’s why the marriage of Salesforce and MuleSoft has really become very compelling for CEOs all over the world. At the end of the day what the cloud brings you and what we bring at Salesforce is the ability to be agile, to be nimble, to be flexible, and actually bring something we refer to as a beginner’s mind. Completely taking a step back and saying, how do we reinvent, how do we innovate, how do we go quickly?
You can move, because of the technology that’s available today, far more quickly than you could in the age of the legacy system. It starts with that, bringing a point of view, speaking the language of the industry, understanding that talking to a bank is different than a telecommunications company. These technologies apply in different ways. Those are very fundamental than what you see with some of the legacy technology companies that are still using the same motion.
CEOs Must Commit to Digital Transformation
The second is it’s all about trust and making sure that you have a trust-based relationship with your customers. The third thing that I would tell you and I think is very very important is that we live in a world today where because of that convergence, that perfect storm of technology, we now have this global phenomenon called digital transformation. The most important aspect of that is the commitment from the CEO. The CEO has become and must be become the Chief Transformation Officer.
Microsoft wants people to know that that they consider it their civic responsibility to provide the very best technology possible to the United States military. Microsoft President Brad Smith says that we want this country, especially the people who serve this country to know that we at Microsoft have their back.
Brad Smith, Microsoft President, recently discussed Microsoft selling technology and services to the US military on Fox Business:
Will Provide the Best Technology to the United States Military
This country as has always relied on having the best access to technology, certainly the best technology that American companies make. We want this country, especially the people who serve this country to know that we at Microsoft have their back. We will provide the best technology to the United States military.
We’ll Be Engaged But We’ll Be Engaged As a Civic Participant
We have also said that we recognize the questions and at times the issues and concerns that people are asking about the future. We see artificial intelligence entering the world of the militaries around the world where people are asking questions about things like autonomous weapons. We’ll be engaged but we’ll be engaged as a civic participant.
We Just Need To Move Forward Into This New Age
We’ll use our voice, we’ll work with people, we’ll work with the military to address these issues in a way that will show the public that we live in a country where the US military has always honored the importance of a strong code of ethics. We just need to move that forward into this new age.
AWS CEO Andy Jassy announced Amazon Textract at the AWS re:Invent 2018 conference. Textract allows AWS customers to automatically extract formatted data from documents without losing the structure of the data. Best of all, there are no machine learning skills required to use Textract. It’s something that many data-intensive enterprises have been requesting for many years.
Amazon Launches Textract to Easily Extract Usable Data
Our customers are frustrated that they can’t get more of all those text and data that are in documents into the cloud, so they can actually do machine learning on top of it. So we worked with our customers, we thought about what might solve these problems and I’m excited to announce the launch of Amazon Textract. This is an OCR plus plus service to easily extract text and data from virtually any document and there is no machine learning experience required.
This is important, you don’t need to have any machine learning experience to be able to use Textract. Here’s how it generally works. Below is a pretty typical document, it’s got a couple of columns and it’s got a table in the middle of the left column.
When you use OCR it just basically captures all that information in a row and so what you end up with is the gobbledygook you see in the box below which is completely useless. That’s typically what happens.
Let’s go through what Textract does. Textract is intelligent. Textract is able to tell that there are two columns here so actually when you get the data and the language it reads like it’s supposed to be read. Textract is able to identify that there’s a table there and is able to lay out for you what that table should look like so you can actually read and use that data in whatever you’re trying to do on the analytics and machine learning side. That’s a very different equation.
Textract Works Great with Forms
What happens with most of these forms is that the OCR can’t really read the forms or actually make them coherent at all. Sometimes these templates will kind of effectively memorize in this box is this piece of data. Textract is going to work across legal forms and financial forms and tax forms and healthcare forms, and we will keep adding more and more of these.
But also these forms will change every few years and when they do something that you thought was a Social Security number in this box turns out now not to be a date of birth. What we have built Textract to do is to recognize what certain data items or objects are so it’s able to tell this set of characters is a Social Security number, this set of characters is a date of birth, this set of characters is an address.
Not only can we apply it to many more forms but also if those forms change Textract doesn’t miss a beat. That is a pretty significant change in your capability in being able to extract and digitally use data that are in documents.
Why is this Revolutionary?
When you use OCR it just basically captures all that information in a row and so what you end up with is the gobbledygook you see in the box below which is completely useless. 
Textract Works Great with Forms