Let's do our data analytics. Let's do our machine learning project. But just two weeks ago I met with five customers over the course of the week and three of them said hey, I want to do a full lift and shift. I just want to move everything to the cloud. And it was only last September that we actually started calling ourselves Google Cloud, all that we do from the infrastructure to the workplace collaboration, productivity, and even the mobile devices in the enterprise. It's been a remarkable year. I mean, our engineers have done over five hundred releases. These are releases to get functionality to our customers. These are new innovations. These are inventions and just ongoing improvement in all that we do. Security, reliability, efficiencies. Cloud is just an incredible cool place to be working right now. It's basically revolutionizing – it's sort of where a lot of the revolution, the digital revolution for every industry is going on. In financial services, you know, tremendous efficiencies on how data is processed or how the banks can talk directly to their customers.
In health, we're seeing a revolution in diagnosis and predicting patient outcomes. In retail, particularly exciting area, taking billions of dollars out as we revolutionize the store of the future. Media, something Google is particularly well situated to do, and energy, manufacturing, optimizing, reducing the energy usage, making the factories, the manufacturing more efficient. It's incredibly exciting to be part of this. We have such interesting customers. We have a customer Planet Labs that is taking pictures of the entire earth every three hours and that is going on Google Cloud. I think the cloud, you know, it is no longer sort of a utility for surplus, peak capacity. It is no longer a place just to store things. You know, startups, it's where they start, but it's not solely for a startup to figure out what – what demand they are going to have before they spend any money. Workplace productivity has really moved beyond sending files around via email. And the cloud is really what gives – what's giving – increasingly giving customers their competitive advantage.
And what is important there, paramount is security, from the board level on down. Nobody – you know, everybody really cares about security and I will say a little more about security at scale in a little bit. It's about cost, performance effectivity, the flexible costs, the lock-in, and it's about reliability. And I am just, because of all of the interest in reliability recently, I am just going to say a few words. You know, you take Google Search. It was designed. It runs as you see when you do a search. It runs at five-nines of availability. That is 99.999% uptime. And we're – our cloud, that is how we designed our cloud and we're making it really easy for our customers to design and deploy for that kind of reliability, distributed, no single point of failure. And I'm really proud. I just learned yesterday that we were recognized as being – having the highest availability of any cloud over the course of 2016. Thank you. I think 2017 will be promising too. We're putting a lot of effort across the board, across our entire systems with the unbelievably excellent engineers we have to keep giving you more nines.
What else? Well the world customers are getting increasingly focused on data. You want the world's best data analytics, the world's best machine learning. This is definitely a Google strength. And then finally workplace culture. You know, really it's about real-time collaboration. It's about finding ways to get the bureaucracy out of a company because everybody has got to move fast now and we have the technology tools to do that. So over the next three days, you're going to hear from our engineers. They're going to tell you about our products. They're going to give you our roadmaps. You're going to see lots of demos. Our customer facing people will help you navigate Google Cloud. And you're also, in this keynote, going to hear from our customers. Everybody at Google Cloud is so incredibly proud of the customers that we have here today that we've been working with over the course of the year. Six customers and a major partner. So now I just want to pause.
I am wearing my red ribbon. I want to acknowledge that it is International Women's Day today. Wow. I have to say that response is pretty exciting. You know, this industry – I think I have been incredibly fortunate but it was sort of an industry where I – you know, I was lucky and I kind of was – chose to be kind of oblivious to what was going on, and now we're in an environment where women are just increasingly having a huge impact and adding a lot of value to our industry. And women are celebrated. If they raise their hand, they say hey, you're missing my value; you're not recognizing what I'm doing. And at Google, we strive at Google Cloud to have an environment where no one needs to raise their hand, but no matter what it's completely safe to do that, okay? You know, I really look forward to the day when this audience is maybe 50% women. It's more fun to have diversity. So shifting gears, now I want to bring out our next keynote speaker. It is my phenomenal privilege to introduce our incredibly smart, compassionate, and just great leader, Sundar Pichai.
>> SUNDAR PICHAI: Thank you. This is a big crowd. I have done many I/O presentations here and it feels like a bigger crowd than Google I/O. So thank you all for joining today. It's great to be here. Google was founded on a mission to organize the world's information and make it universally accessible and useful. Over many years, we've had the privilege to create products that have served billions of consumers across the world. To do that, we've had to engage pretty much every branch of computer science and we have had breakthroughs along the way. It had led us to breakthroughs in cloud computing technology, collaboration software, analytics, things which are now transforming businesses everywhere. So with Google Cloud, now we offer businesses Google quality computing, security, and business tools, and it is an extraordinary big bet for us both as a platform internally for our own innovation but also as a way of bringing our infrastructure to serve the needs of businesses across the world.
Our customers and partners will see many ways to leverage all of Google, be it Google Maps, Android, YouTube, our devices ecosystem, and will deliver it over the most efficient, high performing, and secure core computing resources. For over fifteen years, we have also been investing in machine learning and AI and as businesses increasingly shift online and create more information, they can leverage these AI and machine learning tools to understand the information and build better products that delight more customers. Above all, we are excited to see what you all will create with our products and services. When we shift things on the consumer side, we always get surprised in how they use our technology in a thousand unexpected ways. It makes us better as a company. With Google Cloud, we hope to have the same journey. We hope to grow and learn alongside you. Partners already have pushed us to add more ways to collaborate beyond video conferencing. They have exposed us to more real-world scaling needs, for example the demand that retailers like Home Depot get on Black Friday.
They have shown us exciting new use cases for Google products. You will see what EBay has done with Google Home as an example. In many ways to me, Google Cloud is a natural extension of our mission to make information accessible and useful. We're just doing it for businesses. It means increasing the availability and lowering the cost of data storage and computing resources. It means making it easier for businesses to understand and act on critical information. That is what G Suite does. G Suite enhances information sharing and collaboration. Machine learning finds previously hidden patterns in data, new information which helps businesses improve their products and better serve their customers. So I am really excited by the progress here and I can't wait to see what you all build next. So without further delay, I am going to invite Diane back onto the stage. She joined us in late 2015 and the business has grown dramatically for us under her leadership. And given that it's International Women's Day, it is also a pleasure to welcome back onstage, a trailblazer for women in technology.
So let's have Diane back to share more about how Google Cloud is helping all of you. Thank you. >> DIANE GREENE: Thank you. That was really great. Thank you so much, Sundar. We really are one Google. And at Cloud, you know, one of the reasons I joined; we're leveraging almost two decades of innovation and technology really built for the kind of enterprises we have today or we're starting to have. I want to just kind of underscore or say a few words about our infrastructure. We don't really normally give out many numbers and I'm not going to necessarily break that policy but I am going to tell you some interesting nuggets, okay? We have possibility the world's biggest, most powerful secured network, okay? Tomorrow, Urs Hölzle, who really is behind – employee number eight behind our data centers and infrastructure is going to go into this more and tell you about what we're doing and where we're going. But today what I am going to tell you about is just the kind of the scale of our infrastructure.
You know, if you took not even our largest data center and stacked all of the servers one after another, it would be higher than more than five thousand feet above Mount Everest, okay? I was just going to say above Mount Everest but the person that calculated this said no, no, add the five thousand feet. So – just one building in our South Carolina campus is bigger than Stanford's Arrillaga Football Stadium. We have a new complex in the Netherlands. It's got over ten thousand miles of cable. That is enough to go from here to Tokyo and back. And then one of the things we're all just very proud of at Google is we've been focused on being carbon neutral from the beginning. You know, compute takes a lot of power. Someday we'll be as efficient as our brains but it does take a lot of power. Google is the largest purchaser of renewable energy. That's wind farms. That's solar. In fact, our purchases are larger than the next three or four purchasers combined. So why did I tell you about that scale?
Well I want to give you some examples of why it matters, just to customers. You couldn't have failed to notice that Niantic Labs launched Pokémon Go earlier this year and just six days after they released, they kind of eclipsed their most optimistic three month predictions. Their queries increased fifty fold. So they were running on Google Cloud and our site reliability engineers were with them twenty-four hours a day, seven days a week making this thing go flawlessly. They were there around the clock. In fact, it's when we realized we needed the same kind of functionality for our customers. Pokémon Go – last week at the World Congress, they announced – Niantic announced that they have had 88 billion Pokémon caught. Painless scaling on Google Cloud. The other example is an enterprise customer, very innovative retailer, Home Depot. They are now running on Google Cloud and we got them through Black Friday. It was the most painless Black Friday ever and they will be here later today to talk about it.
Also with that scale comes the need for phenomenal security and I am just going to go into that a little. This shows sort of the layers of security and you can see there are many gaps in between the networks, the servers, and the software. So we built our own chips in the network, in the computing devices. We have to look at every single end point. We actually have over seven hundred people just fulltime worrying about security, watching the network, securing Google Cloud. And if you add a Chromebook which this list Chrome, you know, doesn't store, you get an added layer of security end point. I personally only use a Chromebook. By the way, Chromebooks last year outsold Mac OS in the – Macs in the United States. And something we're really proud of is what we're doing for education. Over 20 million Chromebooks used by students in schools worldwide and growing. Yeah. Thank you. So cloud is just a transformational technology. You know, it's changing how people architect their information, use their data.
It's changing how they work with their customers, how they work together, you know. In effect, our companies are becoming virtualized. We're operating both in the physical world and the virtual and there are many things you can do in the virtual world more powerfully than you can in the physical, particularly as we all start taking advantage of machine learning. You know, I really believe that the cloud with the best technology is the best cloud. It gives you a competitive edge. And you want to be on a cloud that is going to keep you on the edge of, you know – technology is moving so fast and you want to maintain that competitive advantage. But all of this technology needs phenomenal customer focus. We've really doubled down on our customer facing part of Google and I am super – as I said, super proud today to give you those proof points to have our customers here to tell you about that, customers and partners. Just to give you a preview, we've got Disney here. We've got our partner SAP.
We've got Colgate-Palmolive, we've got Verizon. We've got Home Depot and we've got HSBC, one of the world's largest banks, and then we'll close out with EBay with a pretty wonderful demo. So I'm going to begin by bringing out one of the most loved brands in the industry. Disney was here last year and they were just dabbling in the cloud, just starting to do some things, and they actually got more done than they expected. They are ahead of schedule. They are all in. Life and shift. And then they have aspirations for even bolder things we will do together. So I thought it would be very interesting to start out with the CTO and SVP of Disney, Consumer Products and Media – Interactive Media. Mike White. Please welcome him to the stage. Thanks so much. Okay. Yeah, we have chairs. I was worried. I was wondering where they were. >> MIKE WHITE: Yeah. >> DIANE GREENE: It's so great to have you back, Mike. Thanks so much. >> MIKE WHITE: Thank you.
>> DIANE GREENE: You know, we just started talking about moving Disney Interactive Consumer Products to the cloud and now you're taking a cloud first approach. Can we get an update? >> MIKE WHITE: Yeah, for sure. First off, we really looked at moving to the cloud as a way to transform the way we developed software. I can tell you it's been truly transformative for us from software development perspective. Currently, we have about five hundred projects in the cloud. That includes everything from customer facing or guest facing products and production we call it, to dev, to QA, to our R&D environments, and also all of our data suites are running on a big query. We've started with a cloud first approach for all new applications since the last time we talked and we've been – had the luxury actually of being able to re-architect a lot of our legacy systems for the cloud and as you mentioned, we're ahead of schedule. That's really a testament to – you said the word partnership earlier.
It truly is a partnership that we have developed with Google that has been, you know, really helpful for us. So thank you for that. >> DIANE GREENE: Oh, you're welcome. I think our teams just really clicked and really just collaborated phenomenally to bring your vision to life. >> MIKE WHITE: Yeah, for sure. I mean, I think – you know, it was really great talking developers to developers and making developers come in first for this. But what was really interesting was within our division, we have different application characteristics. So we have some really top ranking games. We have kids chat app. We have several Disney sites that are all running out of Google Cloud and that is both internationally and domestically. But what that's really done for us, and I talked a little bit about being transformative from the software development side, is it has really been able to free up our developers and our resources. The way we look at our developers is they're, you know, technologists that are storytellers.
For us, we use technology in service of the story. That's what we do at Disney. It's been our legacy since Walt. So we've really been able to focus on telling great stories and with that, we've been really taking a machine learning mindset as we're on our road to AI. So if you think about character development, extension of characters, and really getting closer to the characters, that is where we want to play. And really with this first lens of machine learning I think in the short-term, we're really looking at how that will impact retail which we're really excited about. >> DIANE GREENE: It sounds like magic helping magic. Do you mean just for your operations you're doing this or is it really touching the customer? >> MIKE WHITE: It is both. So for sure, we're leveraging things like image recognition technology for some backend services, but we also have 8,000 characters within Marvel and you can imagine all of the images that come with that.
We're also looking at ways to really strengthen the connection of our consumers through optimization, personalization, and really enhanced experiences. So those are customer facing and backend as well. We look at that as kind of a symbiotic relationship. >> DIANE GREENE: You know, I just love your mission at Disney to bring this magic, you know, to the daily lives of people and – and your fans around the world. It is so great to support that. >> MIKE WHITE: Yeah, I mean, that's what gets us up in the morning, right? I mean, our company's stories and characters mean so much to so many people. I mean, for everyone in the audience I can imagine that you have a favorite character that is Disney or Pixar or Marvel or Star Wars and with that, maybe you have multiple which is great. So that's really what we do. We use technology to empower and really create the magic and we're really excited with the potential of machine learning and AI, what that can do for us.
So thank you. >> DIANE GREENE: Thank you, Mike. You know, I can't wait to see where we are next year. Thanks so much. >> MIKE WHITE: Thanks so much. >> DIANE GREENE: Great having you here. >> MIKE WHITE: Thank you. >> DIANE GREENE: You know, it's pretty exciting for us to see this full lift and shift happening from just sort of an initial fairly small engagement, sort of what I was describing earlier, and then next year doing even cooler things with our commitment to really just all out partnering with our customers. Now you know – what actually – I just want to mention that in 1955, the average age of a company was about seventy-five years. Now in this year, the average age of a company is only about seventeen years. But all of our customers and partners that are here today have been around much longer than that and are beating the odds, even EBay, you know, at twenty-two years. I don't mean even EBay. I mean even our youngest has been longer.
I love to partner. I love to work with a community of technology companies. And you know, we can build on their offerings. They can build on ours and it is just terrific for the customers. Customers first always, then our partners. We've been working with SAP for over, you know, over the course of the last year and the more we have been working together, the more we see what we can do. As recently in Germany it was very exciting to be, you know, at this, you know, the world's biggest ERP firm, a company that when I started working in the IT industry at SciBase pre-public, they were already, you know, such an impressive company. So today I am really thrilled to welcome to the stage Google Cloud's latest major strategic partner Bernd Leukert, Head of Technology and Innovation and Member of the Executive Board at SAP. Hi, Bernd. >> BERND LEUKERT: Thank you, Diane. >> DIANE GREENE: Oh, thank you. >> BERND LEUKERT: And a warm welcome to the Google Cloud Attendees as well from my side.
>> DIANE GREENE: Yeah. >> BERND LEUKERT: I mean, you said it already. Representing here SAP as a company which now for almost forty-five years is enabling companies to succeed across twenty-five industries, across eleven lines of business with our cloud and in historical times as well, our on premise products. >> DIANE GREENE: Yes. >> BERND LEUKERT: And I mean, you refer to the former times. I still remember joining SAP when mainframe computing was the flagship. We had R2 at that point in time. And since that time, we have led many technology waves and helped our customers to succeed going forward. And as you saw, that technology passion – I liked what you said – and our focus on customers has rewarded us, that we are able to serve now more than 345,000 customers. I have to say enterprise customers. Creating products and used by millions of people and decision makers day in and day out. And one of our most important innovations just recently is of course a growth engine for us.
The last couple of days. This is our flagship product, SAP HANA. SAP HANA is our in memory data and analytics platform and in the meantime as well, used by more than 14,000 customers. And these customers implement scenarios that leverage HANA's advanced analytical processing. They use spatial crafts, streaming data, text analytics, as well as predictive capabilities. And to turn machine learning and insight into real intelligence and then follow it into action. Of course as well, use the platform for our traditional transaction business. >> DIANE GREENE: You know, it's just such an impressive story. Hasso Plattner and you and how you've been so agile and keep reinventing SAP and you know, I first was aware of Hasso because of my sailboat racing. He has very good taste in boats but he's also been great for design thinking you've led in the mainframe, in the client server, and now making a core part of your business the cloud. >> BERND LEUKERT: And I mean, Hasso is basically one of our founders and still the technology advisor and we have now as SAP, the goal these days to become the cloud company powered by HANA.
But now we are ready to take things a step further. And today we are delighted to announce here in San Francisco, the general availability of SAP HANA on Google Cloud platform. >> DIANE GREENE: Yes. >> BERND LEUKERT: Of course – of course if anybody questions, with full support from our SAP's existing support contracts. No doubt about that. And we will offer enterprises the world's leading best network, the fastest service, and the best enterprise data platform for mission critical applications, analytics in one stop. And for the developers and the engineers in the audience, I am also pleased to announce that the developer edition for SAP HANA – we call it HANA Express – is also being offered in Google Cloud Launcher which is Google's marketplace for enterprise-grade partner applications. And with just a laptop, it is going to be easy to build SAP software application capable of instantly working with the largest possible suite of products, accessing data primarily in the cloud world.
And obviously, this is great news for our corporate software developers, and I mean our joint corporate software developers, looking to build new products on existing data and applications. >> DIANE GREENE: Thank you. >> BERND LEUKERT: Our cloud partnership story with you, with Google, does not stop here. This is just the starting point. >> DIANE GREENE: That's right. >> BERND LEUKERT: We are working on running the SAP Cloud Platform, and specifically our cloud foundry based platform as a service framework with a host of business and integration services as well on the Google Cloud Platform. And we recognize Google definitely is a frontrunner, is a frontrunner in technologies and specifically in topics like containerization, in scalable data processing which are featured prominently here at the Google Next Conference. And our SAP Cloud Platform and big data teams will work very closely on with your teams – >> DIANE GREENE: Yes. >> BERND LEUKERT: On making technology such as Kubernetes, such as spanner workforce scaling and enterprise workloads.
And I see a tremendous opportunity moving forward from that point for our customers to build these scalable enterprise applications. Using these endless combinations of services, of APIs exposed on the Google Cloud Platform but as well on the SAP Cloud Platform, and we will have that offered together for you, for our customers. >> DIANE GREENE: Yes. >> BERND LEUKERT: And lastly, our joint memorandum of understanding on machine learning co-development is just the starting point. It's just the starting point and you can expect to hear more from the two of us, from our companies, and from our next big milestone is the SAP Sapphire Event which is SAP's Google Next in May in Orlando. >> DIANE GREENE: You know, this is just a tremendously important partnership to us here at Google and – and our commitment really is to SAP and your thousands of customers. As another – yet another but a really big deal element of our partnership with SAP and Google – between SAP and Google Cloud, we're collaborating to develop leading industry governance, risk, and compliance.
We want a solution for the public cloud. And what that means is it's going to enable SAP to be a data custodian of the customer's data that is stored in GCP. It is increasingly important for enterprises, you know, customers moving from on prem to the cloud to retain their insight, their control while still benefitting, you know, from the agility, the scale, from the presence of a public cloud. And we see this joint solution as the basis for a new way to approach compliance and governance in public cloud environments. >> BERND LEUKERT: I completely agree, Diane, and being with Google Cloud ensures from my perspective, deployment to the greatest number of markets and enterprise and visions. And our strategic intent is to work on extending GCP's robust set of existing capabilities through jointly developed solutions that bring global visibility, access control which our customers ask for – >> DIANE GREENE: That's right. >> BERND LEUKERT: To our customers.
>> DIANE GREENE: Yes. >> BERND LEUKERT: For improved risk and compliance management. And to serve as a data custodian, we feel honored. And this is a first step. We analyze GCP's audit logs to assure appropriate visibility and control, but again not for us, again for our customers and ultimately work towards improving access control requests and even – you mentioned security before – encryption key management on service provider access to the customer's data. >> DIANE GREENE: You know, I really think that this partnership is going to improve compliance and risk and you know, really ease the hassle that thousands of companies – millions of customers are facing. You know, we really see opportunities also for more of the machine learning on SAP's data and applications, getting our – you know, the enterprise is just more value and insight from the data they already have, you know, building these new applications. Yeah. This is – and that's why we're announcing these plans to work jointly on our new machine learning.
We're also really interested in tighter integrations with G Suite. Is this your part? >> BERND LEUKERT: No. >> DIANE GREENE: Okay. With G Suite's collaborative tools – anyhow. G Suite I will just say is a platform also with open APIs and so we are integrating G Suite with the SAP applications. I think that is going to be super exciting for people, you know, really increase customer satisfaction. And just to underscore that we have a joint customer, just wonderful person, and – and from a company that is actually 211 years old, I am really pleased to welcome Mike Crowe, the Chief Information Officer from Colgate-Palmolive if he can join us on stage. >> BERND LEUKERT: By the way, a long-lasting friend of mine. >> DIANE GREENE: Hi, Mike. >> MIKE CROWE: Good morning. >> DIANE GREENE: Thank you. >> BERND LEUKERT: Mike, great to see you again. >> DIANE GREENE: Great to have you here, Mike. Please, why don't you just tell us a little bit about your Colgate-Palmolive and your partnerships with both of us?
>> MIKE CROWE: Sure. So first of all, thanks for having me. I'm happy to be here. Colgate is a leading global consumer products company selling our products in 223 countries around the world. Our 38,000 Colgate people focus on four core categories, oral care, personal care, home care, and pet nutrition. Likewise, we have a very focused IT strategy which at its core relies on a small number of strategic partnerships. We chose SAP twenty-three years ago and Google Cloud just last year for very much the same reasons. You're both highly innovative and you both have a willingness to partner with us. And we see tremendous value from implementing your technology. We have of course been innovating with SAP for years on business processes and we're already starting to see the benefit of Google's collaboration suite of applications. >> DIANE GREENE: So Mike, I mean, you were one of the first potential customers I met when I joined Google and now you've implemented G Suite.
Can you tell us a little bit about it? >> MIKE CROWE: Sure. So when we started our project in May of last year and we were very encouraged by the positive email responses we received from our employees as we announced that we were going Google. Still, we knew that it would be a major change management effort to go to a new collaboration platform. So Diane, we worked with your team as well as our implementation partner, SADA Systems to lay out a phased approach for implementation. And in just three months, we were able to launch for our global IT organization all around the world. We learned from that and then we leveraged that excitement that our employees had shown to recruit a few thousand volunteers to be early adopters. And within that set, we had about nine hundred Google Guides who were to be the champions on the ground as we implemented and to be the trainers as we rolled out. And all of that set us up very nicely for our final implementation which was in one weekend in November we took more than 20,000 users live.
So all told, more than 28,000 users in six months. >> DIANE GREENE: Yeah, Mike. I mean, it's just phenomenal to successfully move 23,000 people over the weekend and I can't tell you how much I enjoyed the little video you sent me to educate your company where you're sitting there talking to Mr. C, a cartoon character. What have you seen since you launched? >> MIKE CROWE: Well in just a little over three months, we see that people are working differently. Sure everybody is using mail and calendar, but the usage of the other tools is quite impressive. Ninety percent of our users are active on Google Drive and in February alone, we had more than 57,000 hours of video hangouts. You know, allowing our user base to connect more easily both while in the office as well as on mobile devices while outside the office. And this is critically important for us as our Colgate teams around the world work more and more together from different locations. And then finally, seeing a faster uptake in the productivity suites in Docs and Sheets and Slides as well, faster than I had expected.
>> BERND LEUKERT: So Mike, I still remember when you asked me last summer how is your relationship to Google? And I was thinking, okay. We have a conversation. Now he is asking me. He knows me now from more than two decades but now we are here together and it's pretty amazing. But I have to ask you; now we have made the first step. What excites you going forward? What should the two of us deliver to you going forward? >> MIKE CROWE: First, I am very excited about the Google SAP partnership, about the announcements that have been made here today, and about the possibilities that the combined strengths of these two great companies bring out. I think it makes perfect sense. It's a perfect fit to combine SAP's business – enterprise business application expertise with Google's expertise on infrastructure as a service, running in the Google Cloud Platform. Bernd, you and I have been talking about incorporating machine learning into a broad array of the SAP business processes for some time – >> BERND LEUKERT: Yes.
>> MIKE CROWE: So I am excited about that as well. And then one more example. As you know, we are users of SAP's digital boardroom, a co-innovation project between us and SAP which allows us to review the state of the business at any time using the latest data, and we are already working on incorporating Google Slides into that application as well. So in summary, I think the possibilities are going to be numerous for us. >> DIANE GREENE: This has been really terrific for us. We really enjoyed working with both of you. It's great for Google Cloud. It's great for you guys. And we're really looking forward to see what we're all going to do next. Thank you so much both of you. >> BERND LEUKERT: Thanks for having us here, Diane. >> DIANE GREENE: Yeah, alright. >> BERND LEUKERT: Thanks a lot. >> DIANE GREENE: Thanks guys. That was great. >> MIKE CROWE: Thanks a lot. >> DIANE GREENE: So as Mike was saying, G Suite is this fantastic collaboration suite.
It is really transforming the culture and the productivity at Colgate. One thing also that I will just add about G Suite that we hear in every customer that deploys is the young people so rejoice when G Suite gets rolled out. And one of our bigger customers, PWC, actually did a poll of their employee base and what the number one valued thing from particularly their young employees was their collaboration and productivity tool. It is so important to them. Okay. So for our next guest, I am really excited to bring out you know, premier technology company Verizon. They've got 114 million retail customers. We've been working closely with Verizon for a year now, not simply – and we've been working with them on workplace productivity. It's been a long project. It's been a challenging project. And that's – you know, I really wanted to talk about that here. It's gone really well. Great outcome. And here to talk about it, coming on stage, let me welcome Alin D'Silva who is the Vice President for Digital Workplace at Verizon.
Hi, Alin. Thanks so much for coming. Great to see you. >> ALIN D'SILVA: Good morning everyone. At Verizon we believe deeply in our brand statement which says better matters and we believe better matters not just for our customers but our employees as well. We are keenly aware of the need to move faster, collaborate more effectively, have flexibility in how they work when and where, and it's really a commitment we've made to a much more modern and progressive work environment. And we're delighted that G Suite is going to be a big part of that transformation. >> DIANE GREENE: So are we. We're delighted too, Alin. You know, starting in just a few weeks, I understand you're going to start moving 150,000 Verizon workers over to the G Suite platform. >> ALIN D'SILVA: Right. >> DIANE GREENE: But we both know it didn't happen that quickly, that you started down this path more than a year ago, and I'd just like to know what were you looking for?
>> ALIN D'SILVA: Yeah, so a little over a year ago we formed a group that was really focused on raising the bar on productivity through collaboration and employee engagement and we've done a lot in that short period of time. We fostered collaboration by rolling out activity based workplaces. We rolled out unified communications globally. And we made improvements to our mobile options. We realized that we were really missing some key features, things like real-time collaboration, and other modern features that you see in these productivity suites. So we did a comprehensive trial of G Suite and our employees really loved it. They loved the simplicity and intuitiveness of the product, the ease of use. The real-time collaboration really blew them away. You know, it worked well on desktops. They were really surprised by how – was how well it worked on mobile devices. And you know, the simplicity of the solution actually helped us secure the platform in a much more straightforward way.
And then I'd say the last thing is that we realized that actually a number of our employees at Verizon, specifically at companies like AOL and Telogis were already on G Suite. So for us, that is how we came about making the decision. I would say one more thing. Like, you know, we also realized that we had to skate to where the puck is going because in terms of talent, we knew that you know, as the years passed, the talent that comes into the company is going to expect a product like this. And so we had that in mind as we made our decision. >> DIANE GREENE: Thank you. You know, Alin, a lot of the time change can be pretty hard no matter how good the technology is. Did you have resistance in going to the cloud and what did you do about that if you did have that resistance? >> ALIN D'SILVA: Oh, sure. We had a fair amount of resistance but it really is a matter of addressing the fundamental perceptions of what it takes to go to the cloud. So what we did is we cracked open the door, we asked everyone to sort of keep an open mind, and then over several months, you know, we got really deep on a number of topics like security, operations, user experience, regulation and compliance matters, and we also looked closely at ROI of course.
And in going through the trial, in talking to you, in talking to your partners, in talking to your customers, we realized that really it was the right decision for us. The Google team was really fantastic to work with. Eric Geitner, if you're out there, kudos to you. But they answered all of our questions. You know, they got us really comfortable with the decision that we needed to make. >> DIANE GREENE: Thanks for that shout out to Eric. Alin, do you have any advice for anyone in the audience that is looking at making a similar transformation that you have gone through at Verizon? >> ALIN D'SILVA: Absolutely. So first of all, you've got to bring along all of the stakeholders that are going to be key in the decision-making that you're going to make. So bring along your CSO and legal teams for starters for sure because they need to kind of go on this journey with everyone. You know, they've got to understand what it's going to take and get comfortable with it.
The other thing we found is that we learned a lot from customers, from Google and G Suite, and from partners, so I would say definitely take advantage of that. Remember that this is like partly – I mean, it's a technology transformation but it's really about change and driving change in the organization, so you've got to give thought to how you're going to drive change management around this. I would say, like, you know, if your mission is to go transform the company, then you really have to have meaningful change, otherwise, like, where is the transformation? >> DIANE GREENE: Right. So what has the reception been like since you announced this move to G Suite? >> ALIN D'SILVA: The reception has been pretty interesting. So we put out an article on our intranet site in the middle of January and within a couple of days, it got like the most reads for the whole month. We had hundreds of comments and questions that were posted. And you know, people saw it as a really meaningful step in the right direction.
These were folks who had experienced G Suite at other jobs or had used it in their personal lives and they were really comfortable and excited about the idea that we would go forward in this direction. And then there were a number of employees who you know, naturally were concerned about how it was going to change the job. They were used to doing things a certain way. And they posted a lot of questions online and we went through and we answered each and every one of them. And that really helped the broader community understand where we were going and that was really important. We also identified all of the early enthusiasts, the ones we, you know, we call them Google Guide just as Mike said earlier. We're going to rope them into the early adoption phases of this so that they can get on board and get ready to support our colleagues when we bring them overall. So you know, it was a great validation. It was a great early validation that we made the right choice and we're really looking forward to starting the migrations in a few weeks.
>> DIANE GREENE: You know, it's a big step, Alin, and I really admire you know, the commitment you've brought to bear on this. We've been working pretty closely. I know I'll be hearing more from you and I really look forward to the updates and supporting you. >> ALIN D'SILVA: Great. Thanks, Diane, for having me. >> DIANE GREENE: Thank you. Thanks so much. Bye bye. Yeah. Yeah. G Suite, you know, is built for the cloud, integrated, works seamlessly. It's really proving its value. Going back to Google Cloud, once someone decides to move to Google Cloud, you know, we really have an incredible commitment to deliver top quality customer support. We don't want any of our customers going down. You know, we use site reliability engineers, you know, to keep our seven apps that have over a billion active users available and we realized, as I said before with the Niantic Pokémon Go launch, that our customers need the same. We established a new organization called Customer Reliability Engineering where those people work with our customers to make sure that your services are architected and monitored and keep full availability.
Now Google can't scale to do enough Customer Reliability Engineers for all of our customers and so what we've done is we've reached out to partners and I am really excited today to announce two of our early partners. We have Pivotal Labs, premier consulting development company leading in agile development. Our first certified CRE partner. They offer CRE services to our customer. And then another customer, really a pioneer in the cloud – they understand the cloud inside out. That is Rackspace and they are our first managed service provider and we look forward to doing more and more with them. Now somebody that has already taken advantage of our CRE, Home Depot. I am really excited to welcome to the stage Paul Gaffney, Senior Vice President at Home Depot. Hi. Hi, Paul. Thanks so much. >> PAUL GAFFNEY: Hi, Diane. It's great to see you. >> DIANE GREENE: Yeah. Okay. So you've got an impressive history, quite an innovative retailer doing extremely well. How do you think about technology?
>> PAUL GAFFNEY: Technology is a really important thing to us, particularly in this landscape as consumers' expectations are increasingly being shaped by the software that they use. We've got over two thousand stores in North America, 400,000 real live human beings who take care of our customers and that is our heritage, that excellent experience that you get when you're talking to someone wearing an orange apron. And increasingly consumers are expecting that we do exactly that same thing in software. So we think about software as an extension of our overall culture. >> DIANE GREENE: It's sort of your virtual company running isn't it? >> PAUL GAFFNEY: It is. >> DIANE GREENE: And – and what have been the proof points in using the cloud for you? >> PAUL GAFFNEY: The important thing about cloud for us as we started to get better as a software engineering organization – we paid attention to a lot of different things. One of those things was building cloud native apps.
There were a variety of reasons why we focused on building cloud native apps but we also said well we also should probably run them on the cloud if we're going to build them cloud native. And cloud plays an important role for us economically. Cloud economics are a substantial improvement to our on premises economics. But also thinking differently about resiliency and availability, moving from I think what is a classical big company, IT orientation which is make the infrastructure robust, to a more modern view that says just assume that everything is going to fail. That was a big catalyst for us to engineer our software differently and partner with you guys on learning what does it mean to live in a world where you make your stuff resilient to failure. >> DIANE GREENE: You know, I've come to love all of these days when you have these spike loads and you guys recently you know, of course every year you have Black Friday. I was just wondering; how did it go for you guys this year?
>> PAUL GAFFNEY: I'm glad that you love these spike loads and – and as shareholders – >> DIANE GREENE: I do bite my fingernails though. >> PAUL GAFFNEY: So do we. >> DIANE GREENE: Not really. >> PAUL GAFFNEY: As everyone in here is a consumer, I think you guys all know that there are times during the year when all of us in retail attempt to conspire to get you to do more shopping than is normal. And – but those of you who are in the room who know that that ends up somewhere, that has to be processed, one of the fantastic things about an elastic environment is you don't have to attempt to provision in advance and pay for in advance all of that spike. And if you architect your stuff correctly, you can scale that out instead of having to scale it up. And we were really nervous, not because we weren't prepared. The team that worked on this does fantastic prep and you guys were a great partner. >> DIANE GREENE: You have great technologists, yeah.
>> PAUL GAFFNEY: Outstanding prep, but everyone is kind of nervous. Thankfully our 400,000 folks do such a nice job each year that more folks do business with us each year. So this last Black Friday was an all-time high for us and we were running meaningful portions of our e-commerce infrastructure on Google Cloud for the first time and it was our smoothest performance ever. >> DIANE GREENE: Just tremendous to see and it's great to see you using Kubernetes and containers. How about your work with big data? >> PAUL GAFFNEY: I think as you know, a very interesting offshoot of our partnership on cloud was thinking about okay, we're going to be moving some mainline, line of business workload from on premises to the cloud. Should we be doing the same thing with data? And as the audience might imagine, we've got a lot of data and we replenish those 2,000 stores continuously. And we have started to move quite a bit of our data analytics environment from proprietary on premises infrastructure onto big query and other parts.
I think, you know, I'm excited by the technology, but frankly I'm more excited by the investments you guys are making in talent and I'm looking forward to the work we're going to do on exploring some really interesting problems where we think that the machines can help us understand some things perhaps that the humans find difficult to understand. >> DIANE GREENE: Yeah. We're really looking forward to this ongoing work and I can tell you that Fei-Fei Li and her cloud machine learning group are really excited about what they're going to be able to do with Home Depot. Thanks so much, Paul, for being here. >> PAUL GAFFNEY: Great pleasure, Diane. Thank you. >> DIANE GREENE: Yeah. Okay. Bye bye. Thanks. So now we're going to turn and we're going to talk about security, privacy, data analytics at scale with a big bank and here to lead that discussion and tell you about it, I'm delighted to welcome Tariq Shaukat, Google Cloud's President for all customer facing operations.
>> TARIQ SHAUKAT: Thank you, Diane. Morning everybody. So you've heard a lot today from our customers and you've heard a lot today from Diane and from Sundar about what our mission is here at Google Cloud. But to put it in the terms of what we're looking to do for customers, we very much view our mission at Google Cloud and on our customer team as generating real – a real step change in business value for our customers. That business value happens in a number of different ways and increasingly in mission critical applications. It happens first of all at the cost savings level of how do you actually move to a more flexible environment? How do you move to a more agile environment? How do you move to a lower cost environment? So that is absolutely one of the major conversations that we have with our customers. As you heard Paul talk about and you heard Mike from Disney talk about, we also are increasingly seeing the cloud being used as a platform to drive real, tangible revenue growth for companies for them to both create new applications but also critically importantly, to understand their customers better, to get into their data better, and to really understand how to become closer to their customers, how to become more efficient in their operations, and how to engage their employees better.
So you have the cost savings piece and you have the revenue generation piece. But the third part that really has been a thrilling evolution of the market is how many companies are really coming to Google Cloud now and saying we need a partnership and we need a partnership to help transform our business, to really help us think about what is the business model of the future and how do we take our existing operations and how do we move that in a both gradual way and in a step change way into the future? One of the most thrilling partnerships that we have in this regard is with HSBC. HSBC challenges us in each and every one of these areas, in the cost savings, in the revenue growth, and on the transformation levels every day. You may know them as one of the largest financial institutions in the world. They have over 150 year history, 4,000 offices in 70 countries, and over 2 trillion dollars of assets on their balance sheet. Now to tell you more about this, I am truly delighted to welcome to the Google Cloud stage, Darryl West who is the Global Chief Information Officer at HSBC, and he is going to share his thinking about the role of cloud and cloud scale data analytics and machine learning for the financial services world. Darryl.
>> ANNOUNCER: We are living in a time of rapid digital change, where the only limits are the scale of our ideas and degree of our dedication. The technology ideas of today will be the intuitive habits of tomorrow. Never before has innovation promised so much, touching so many in so many different ways. Our frontier is financial technology. It's changing the way we work, make money, and the way we trust each other. To succeed, we need to adopt the mindset of the silicon hubs of the world and create an incubator of free thinkers, thought leaders, innovators born of collaborative spirit, all fueled by a belief that technology will enhance our customer's financial lives, to imagine a future beyond what we already know, creating a team with the power to transform the world's leading financial enterprise. We are technology. >> DARRYL WEST: Thank you, Tariq. Good morning everybody. It gives me immense pleasure to be able to be here with you today, particularly on International Women's Day.
I've been at HSBC now for a couple of years and I have the honor and privilege of leading an awesome IT team that is at the center of an amazing transformation happening in our organization. I'm going to talk about our commitment to cloud and I'm going to talk about how we're collaborating and partnering with Google to make HSBC a simpler, better, and faster organization, an organization focused on amazing customer experiences through digital channels, and a company committed to using the latest technology and data analytics and machine learning to transform the way we run our business. Now I'm sure many of you in the audience are travelers and I'm sure many of you have stood in airport walkways and seen the HSBC advertisements and they are quite distinctive. And you've probably asked a question. How are these people? Well, who are we? We're the world's largest international bank. As Tariq said, we've been around for one hundred and fifty years. We're present in seventy countries.
We have 37 million customers, customers ranging from individuals to small businesses, mid-sized corporates, large global companies, as well as governments as well. So we have a huge business, a huge global business. We're the number one bank in the world for trade finance and cross border financing and we're a significant player in the global foreign exchange markets. So given our central position in global finance, as you can imagine, we are a systemically important financial institution, heavily regulated. In the banking business, clearly trust and confidence is a central part of our business. We have to make sure that our customers feel confident and trust in us to be the custodians of their assets. So you know, information security, reliability, and resilience in how we deliver our services are fundamental to our business. Now apart from having the 2.4 trillion dollars of assets on the balance sheet, we also have at the core of the company, a massive asset in our data and you know, what's been happening in the last two or three years is a massive growth in the size of our data assets.
So as you can see here, 56 petabytes of data in 2014. That is actually doubled. As of now sitting here, in 2017 over 100 petabytes of data. And what is happening is our customers are adopting digital channels more aggressively. We're collecting much more data about how our customers are interacting with us. And obviously embedded in this data is massive insight and what we need to do as a bank is work with partners to enable us to understand what is happening with this data, draw out the insights so we can run a better business and create some amazing customer experiences. Now our journey in data is very similar to other companies. This is no different to many enterprise companies. The history here. We have lots of good old fashioned databases, all of our core systems are running on products systems that have been around for twenty, thirty, even forty years. The systems are robust and scalable and they do a great job, but they don't have the database structures that actually allow us to really do the data analytics, the machine learning that we need to do.
So the history of enterprises like mine is that we typically did extracts into traditional data warehousing platforms which worked well for many years but of recent times, they have become expensive to run and difficult to use. So we took the plunge about three years ago to really embed ourselves into the evolving Hadoop ecosystem. And for an organizing like mine that has this traditional history of what we call legacy platforms, it's been a tough – it's been a tough road for us. All of this is being done on prem. We've had to provision, large infrastructure, physical infrastructure, build out data centers, and hire talented new people that have understanding of these new technologies. So we thought about this very carefully in the last year and we said to ourselves, we're really – we're a bank. At the core of our business, we're a bank, but we also have a significant technology company embedded within the organization and the question that I was asking the management team is you know, do we really want to compete with the cloud providers and people like Google?
Are we really going to try and do what they do as well as they do it? I think our conclusion was that it was better for our business if we adopt a cloud first strategy. So we started working with Google about six months ago now. So it's still early in our relationship. But we had been working with them on some of the most important and critical business problems that we have to solve in our business. To give you an idea of what these types of problems are – so the initial use cases here are typically characterized by business problems that have very large data sets and require very intense computing capability in short bursts. Now the first one on this list is all about anti-money laundering so as one of our obligations of being a bank, we worked with the governments and the crime agencies to identify nefarious activity and money laundering and criminal activity. Now we have a set of applications that monitor a huge time series of data, so a massive dataset, billions of transactions for all of our customers.
Running analytics over this huge data set with great compute capability to identify patterns in the data and to bring out what looks like nefarious activity within our customer base. Those patterns that we identify are then escalated into the agency, so we work with them to track down the bad guys. So this is an application that clearly requires massive data sets, great computing capability, but also a machine learning capability to be able to identify the patterns in this huge data set. The other applications that are mentioned here in terms of finance and risk, we have billions of transactions. Those transactions need to be aggregated so we can manage our finances and our risk at a global level. Evaluation services and our trading business, as I said, were a major player in global financial markets. We need to be able to run complex multicolor simulations on a regular basis to be able to better understand our trading positions and our risk. So this requires a significant compute capability.
So we were faced with the question of do we build that new data center and put thousands of servers and thousands of cores out there to do this activity, or should we actually work with somebody who does it as their core business? Our solution was rather than build that out ourselves, we should be working with you know, world-class leaders in this space, and hence our work with Google. Now all of this doesn't happen by accident and there are some critical enablers that have to all be in place to make this work for organizations like us. The first couple of boxes here talk about risk and compliance and information security. You know, we are a heavily regulated business. We have to provide a very resilient, very safe, and very performant services to our customers and also very agile because the requirements of our customers are changing tremendously quickly. We also have to respect the data protection and data residency rules that we have in our seventy countries. There are lots of rules about what data can sit where and what data can be shared.
So we have to respect all of that. Working closely with our partner at Google on this – on this construct. Information security as you heard this morning, it's a massive issue for everyone, particularly a bank. We have to keep our data safe from cyber criminals and we are working very well with Google on solutions in the security space. Probably the biggest impact though or the biggest enabler for this journey is the other two boxes in the middle here. You have to drive a cultural shift in your business to make this really work. You have to adopt an agile methodology. You have to adopt a dev ops mindset. And you need to be able to recruit and retain talented people that understand how to use these new technologies and working this way. So just a point of note; we are recruiting. Okay. And we're a great company, just like Google. So the other issue here on the second box is of integration. I mentioned the legacy platforms we have. All of our core data is sitting in these systems of record.
We have to make sure that we can integrate all of this technology complexity to work with the Google platform, the Google Cloud platform. So this integration layer is very, very important. You've got to get that culture in place. You have to get the people that understand how to do it and you have to build the integration layer to be able to make it all work in that rapid cycle. And lastly of course, data preparation. You know, we have, like most big enterprises, a data sprawl as I said and a massive growth of data, but also you need to invest your time and effort in your data architecture and making sure you understand where your crown jewels are, where the copies are, and get a really good understanding of the preparation of getting the data ready to be able to interface effectively into the cloud partner. And obviously agreements of legal and commercial are obviously very important as well. So in summary, these enablers are fundamental to us achieving our goals at HSBC and we are working in very collaborative and partnership mode with Google to get these enablers in place to run a better business.
>> TARIQ SHAUKAT: Thank you, Darryl. That is a fascinating journey that you guys are on there at HSBC. Just a couple of questions for you. You mentioned that you did a pretty thorough investigation of the technologies, in particular as you were looking at us around data flow and big query. What aspects convinced you to move forward with GCP? >> DARRYL WEST: Yeah, we've – we spent a good amount of time working with all of the big cloud providers and evaluating their products. I think if you look at the scarce talent we have on data analysts and data scientists, they need tools that allow them to do their work in a very productive way. So we found as we worked with your team and your subject matter experts, working with our data scientists, that your suite of products have been very performance – very easy to use. You know, there is always a challenge of getting data scientists to shift from their favorite platform to a new one and I think the way that your products are actually being configured and presented to our scientists, they've really enjoyed that experience.
So you know, it's early in our relationship. We're still in pilot mode and we hope to get these use cases to production in the coming weeks and months, but I think our experience so far has been very positive. >> TARIQ SHAUKAT: Terrific. Just looking forward the next three to five years, how do you see the cloud really playing out and all of these technologies impacting your business? >> DARRYL WEST: Yeah, look, it's very difficult to be able to predict the future, even three years ahead. It's a long way away, right? So the world is going to change. I think what is definitely going to be consistent is that our data is going to continue to grow. Massive data sets need to be managed. I know also we're going to be pushed to go faster. I mean, our customer base is dragging us into a new world and consuming services on new digital channels which will require us to be agile and fast to market. I know we're going to have the need to use data analytics and particularly machine learning to run a better business.
So it's going to get bigger. It's going to get more complex. And we're going to need to partner with people like Google and others to be able to use the best technology in the world to solve these problems for our business. >> TARIQ SHAUKAT: Great. Well finally, I think everyone in the audience I'm sure could use a little advice. You guys are leaning very forward into the cloud and cloud technology. What advice would you give everyone here for how to really start their journey? >> DARRYL WEST: Yeah. Well I think the first thing you need to do is you have to make the jump in thinking to make yourself a cloud first company. It requires you know, getting everybody on board in the technology team, but also the business. You've got to get the business to think about things in a very different way and I mentioned the criticality of new ways of working with agile methods, dev-ops methods as really important. So that first thing is make that jump and be bold and have courage to go and do the innovative things.
The second thing is pick a partner that has the same type of culture as you. I think you need to. If you're going to be innovative, you're going to be bold and take on big challenges, you need a partner that is going to think the same way and work in the same ways of working. And just I think basically the conclusion I've come to is have a good look out there. Meet, you know, the people in the market because they are all very different. And certainly from my perspective, the chemistry between the people and the teams is actually the number one thing because what we're doing is complex. What we're doing is difficult in many cases and the chemistry and the culture of the organization is very important. >> TARIQ SHAUKAT: And it's a multi-year journey. >> DARRYL WEST: And it's a multi-year journey. So you have to like who you're hanging out with for the years ahead. >> TARIQ SHAUKAT: Exactly. Well again, on behalf of all of Google Cloud, we're really thrilled that you're here today so thank you very much.
>> DARRYL WEST: Thank you. >> TARIQ SHAUKAT: And I'd like to welcome Diane Greene back onto the stage. >> DIANE GREENE: Thank you, Tariq and Darryl. That was fantastic. And now we're going to have a look at how an iconic e-commerce company, EBay, is thinking about the cloud. I think we have a video first and then I want to welcome on stage RJ Pittman who is head of products, CTO. >> ANNOUNCER 2: We transfer about thirty gigs a second, search through one billion active listings in our quest to find your perfect. Through cutting edge technology and the performance and scale of cloud, we strive to meet our customers where they are and transform the future of commerce to help find your version of perfect. The future of commerce from EBay. >> DIANE GREENE: Cool. RJ. Thank you for coming. Great to have you here. >> RJ PITTMAN: Great to see you. >> DIANE GREENE: So, RJ, you've had a phenomenal amount of experience working in online environments.
Why don't you start talking about how your view of the cloud has changed? >> RJ PITTMAN: Well the biggest thing is it's moving and it's moving fast. In the last four years, it's, from my perspective, gone from a very powerful and compelling proposition for outsourcing your IT infrastructure and shifting some things so that you can focus on your core business, to now we see it as a strategic growth engine and a strategic growth engine that accelerates innovation. This is a very different position that the cloud has taken and it is playing a very important role for us in that matter at EBay. >> DIANE GREENE: And what do you think that means for EBay? >> RJ PITTMAN: Well you know, in the videos you can see. I mean, we've been around for a long time. The business is continuing to grow. We have over one billion live listings at any given moment in two hundred countries around the world. >> DIANE GREENE: Yeah. >> RJ PITTMAN: One hundred and sixty-seven million shoppers.
And so you can imagine that if we start moving the capabilities of the cloud to EBay, we're not just changing our infrastructure and changing our business; we're changing the experience for all of those shoppers and all of our buyers and sellers around the world. And that is the really important connective tissue here. This is not just a technology exercise for us. It is absolutely a customer-centric effort. >> DIANE GREENE: Yep. Absolutely and you know, with that kind of phenomenal growth, I can see that you really are paying attention to technology to help you through it. Yeah? >> RJ PITTMAN: Yeah, it's – you know, for us the e-commerce space is competitive and it's moving fast and the demands of customers and shoppers today is changing so quickly and as new generations of buyers come into the world, first millennials and now gen-zers, they have very different shopping habits, very different expectations, and they are much higher expectations. So we EBay, at our scale, if we're, you know, intent on setting ourselves up to meet the demands and exceed the demands of this next generation of online shoppers, we have to move quickly and the cloud has become a very strategic partner for us in that way.
>> DIANE GREENE: So RJ, before we get into our cold demo, can you just tell me a little bit about what you're doing on Google Cloud? >> RJ PITTMAN: Sure. So this was an undertaking for us that we've been thinking about for a few years, but we really got serious about it a year ago and we knew that there was a lot of untapped potential inside the EBay marketplace and we wanted to get at it. And as a marketplace, let's also remember that first and foremost, we're a tech company and we utilize technology to differentiate, to compete to innovate, and to create these amazing customer experiences for all of our customers around the world. And so for us, we went out on a mission and said if we could bring the EBay marketplace to a modern stack environment, if we could bring our customers to a place where we can be innovating almost every day and bringing great new features and capabilities to them, you know, that would give us a tremendous advantage and a ton of momentum.
So literally in the space of about five months, we took a great team of engineers and set off to do exactly that. And in five months we went from nothing to the entire one billion live listings of EBay running in GCP. It was not a test. It was not a prototype. It quickly moved to a production grade environment for us that we ended up launching and bringing in to market six months ahead of our plan and mind you that, in total start to finish, was about seven months. So it can be done. >> DIANE GREENE: Yes. >> RJ PITTMAN: Do not fear the cloud. It can be done. And look, in our business this is super important. You can't – you have to be careful when you're serving live customers in a live marketplace like that. And now the way we've approached it, we were smart about this and we didn't just flip the switch and you know, move the entire 85 billion dollar marketplace business at the throw of switch. We're actually running a parallel swim lane and that gives us lots of latitude to play with.
They're both live systems and this is very difficult to do in – in most environments because we're transacting as you saw, thousands of orders a second. And we now have two hot, hot systems running. Our core system on prem and then we have the new Google platform both serving customers and we've had to build a system that ensured that we didn't create two separate marketplaces, meaning no two buyers could buy the same one item that is for sale because that would create obviously a lot of problems for us. And it was actually one of the most important decision factors for us in really leaning in on the Google platform is the services and the capability that Google offers that nobody else did, that allowed us to build a true replication – replicated system that runs in real-time side by side to help companies of our size and scale and complexity make that transition much more seamlessly to the cloud. Now mind you, the other cool thing about it is it didn't just allow us to go to a cloud instance here in North America, but using the global footprint of GCP, we took the show on the road and we were able to test our theory and look at lighting up the Google Cloud in multiple countries around the world so that we could be serving where our customers are and providing a great high speed performance as if that data center was sitting in their backyard.
We've not been able to offer that kind of experience and that kind of performance in the twenty-two years that we've been around. So this is really breakthrough for us and it's our customers that are the ones that really stand to gain. >> DIANE GREENE: That is just a great story about what you've done and I think also in another area, you're kind of leveraging AI and – >> RJ PITTMAN: Yeah. >> DIANE GREENE: For your catalog. And what about that? >> RJ PITTMAN: So this is – this is a really cool part of the story where you have a billion live listings and we have twenty-two years of historical transaction data. We have more economic data on the supply and demand information on virtually any product that has been made and sold in the last twenty years. We know what it sold for, what the demand was, what countries, you know, are most interested in what products and when, and you can imagine if we could then start to encapsulate and capture all of that knowledge and bring it forward for our shoppers.
You could build arguably one of the smartest shopping experiences and smartest catalogs on the planet. And the challenge there too has been getting to a place where we had truly the computing capacity and performance to get our arms around literally billions and billions of records that go back in time but also the new ones that are created every day that there are transactions on EBay. And going to GCP, we have the scale and the performance that allowed us to lay down some really great AI technology, going well beyond machine learning and going very seriously into deep learning, natural language understanding, and computer vision to create something that we called EBay ShopBot. This thing is pretty great and it is the largest marketplace in social where we took our billion item catalog and merged it with a billion people in the social graph and brought them a highly personalized shopping assistant that gets to know you, that understands natural language, and can start to make really, really great recommendations across our entire inventory of a billion items to give you – help you find the best item for you at the right time, at the right place, at the right price.
And so when technology can start doing the heavy lifting and provide you with almost a concierge-like personalized service, I think that's when we've really, really made great strides, and that's something that we brought together with the innovation at EBay and the great work going on in Google. >> DIANE GREENE: I have to say that sounds like a perfect match for Google Home and we actually have a Google Home sitting over there. Could you show us all what you're talking about? >> RJ PITTMAN: In the spirit of going to where our customers are, we've taken it to Google Home because we want to get inside the home. Let's do it. >> DIANE GREENE: Now you know, we're doing this live. There is like ten thousand people on the network. We really hope this works. >> RJ PITTMAN: Hey Google. Let me talk to EBay. >> GOOGLE HOME: Sure. Here's EBay. Hi. I'm EBay. I'm the world's price guide. You can ask me what something is worth.
>> RJ PITTMAN: What is my camera worth? >> GOOGLE HOME: Is it new or used? >> RJ PITTMAN: New. >> GOOGLE HOME: What is the brand of your camera? >> RJ PITTMAN: Canon. >> GOOGLE HOME: Tell me the model of your new Canon camera? >> RJ PITTMAN: Five D. >> GOOGLE HOME: What else do you want to tell me about your Canon camera? >> RJ PITTMAN: Nothing. >> GOOGLE HOME: Your camera is worth 2,548 dollars. >> RJ PITTMAN: Not bad. So this is maybe an unexpected use case, but one that is really interesting and close to the hearts of EBay because we support not only our shoppers but also our tens of millions of sellers all around the world. And what this allows us to do is start to bring more sellers into the marketplace. You may have lots of really cool things sitting around your house that you didn't know had really great market value. Now you'll be able to ask Google and ask EBay through the Google Home partnership to get you started and bring you a little bit closer to EBay.
And there is so much more to come with this technology. >> DIANE GREENE: Absolutely. >> RJ PITTMAN: And let me tell you this. It was five months for us to go from where we were to in the Google Cloud and it took us five days to get into Google Home. So you know, with that kind of power there is great, great potential. >> DIANE GREENE: RJ, thank you so much. >> RJ PITTMAN: Thank you. Thank you. >> DIANE GREENE: That was fantastic. >> RJ PITTMAN: It was really fun being here. Thanks everyone. >> DIANE GREENE: You know, I just love the fact that here is a chat bot running on Google Cloud, talking to Google Home. We have one Google partnering with EBay. And now you're all in for a treat. We're going to bring Fei-Fei Li on stage. I first met Fei-Fei when she came to Stanford back in 2012. She is a neighbor of mine. And for those of you who don't know, Fei-Fei was really instrumental in the explosion of machine learning. She built image net which is the largest database of labeled images and what that facilitated was all of the research – all of the academic researchers, industry researchers now had something to benchmark against and we started seeing this explosive improvement and adoption of machine learning.
So let me just welcome to the stage Fei-Fei Li. She is the – she is in charge of Google's cloud machine learning. She is head of the AI Lab at Stanford and here now to lead us in our AI efforts at Google. Please welcome. >> FEI-FEI LI: Good morning everyone. My name is Fei-Fei Li. I'm the Chief Scientist of Google Cloud AI and Machine Learning. So in Google's code word, I am still a New-gler, and it is quite an honor and privilege to be on this stage to share with you some of my thoughts about AI, machine learning, and Google Cloud. So the world is changing incredibly fast. Some say that we're living in the fourth industrial revolution, and much of it is propelled by the phenomenal force of computing. As an AI technologist for nearly twenty years working on machine learning, computer vision, I have witnessed my field growing from a lofty but academic pursuit to the biggest driver of this change. But change happens at many scales and it takes imagination to see them all.
Let's take a familiar example, the self-driving car. It is easy to understand the appeal. With the help of sensor and algorithms, a self-driving car reduces accident risks and gives us more time to work, socialize, and just relax while commuting. This is great for a single driver. But what happens when thousands of people have self-driving cars? Suddenly through the coordination of vehicles, traffic congestion is reduced and parking is dramatically simplified. What about millions of people having them? Entire cities will be reshaped by – to reflect the fundamental shift in the use of its infrastructure. So the difference between each scale is participation. As a technology reaches more people, its impact becomes more profound. This is why the next step for AI must be democratization, lowering the barriers to entry and making it available to the largest possible community of developers, users, and enterprises. Speaking of democratization and reaching many people; Google's Cloud Platform already delivers our customers' applications to over a billion users every day.
That is a lot of participation. Now if you can only imagine combining the massive reach of this platform with the power of AI, making it available to everyone. Then we stand to witness a greater improvement in quality of life that any other time in history from finance to education, from manufacturing to healthcare, from retail to agriculture, you name it. This is why delivering AI and machine learning through Google Cloud excites me. It means finally sharing the technology and insights I have been involved in for years as an AI researcher at Stanford. That is also where, by the way, I began a collaboration and partnership in AI with Dr. Jia Li who was one of my first PhD students many years ago. I am very excited that she has joined Google with me as the Head of R&D in AI and Machine Learning at Cloud. And speaking of International Women's Day today, this is another badass woman in STEM, CS, and AI. There is no shortage of examples of AI Solving real world problems such as the demo we just saw that EBay – talking to the EBay ShopBot through Google Home.
As impressive as these achievements are, they are just the beginning of the transformation of the entire enterprise. More and more problems are being addressed by AI and the tools we use to build AI solutions are becoming more and more sophisticated in their functions, but also easier to use. This will change our world dramatically and it is happening at a faster pace than most people think. Let's take a look at a few examples. AI has been influencing retail as long as it existed. For instance, machine learning algorithms are already helping Google's AdSense and Shopping to deliver relevant information to our customers. But so much more is just waiting to be done such as supply chain optimization for routes and inventory, or predicting changes in demand over time. Drones navigation and self-driving vehicles for delivery of items customers ordered. Intelligent analysis for loss prevention and safety. Or understanding customer movements and perception in stores to optimize shelf space, displays, and visibility.
Another example from media and culture already being influenced by AI. Do you have a teenager at home? Wonder why – what is the technology that is mesmerizing them with the cat ear and rainbow filters of the Snapchat app? That is a clever computer vision technology. Machine learning already delivers Google Photo automatic image tagging and YouTube's recommendation list. But media experiences will soon make much more use of it. AR and VR will rely on computer vision for motion tracking, environment detection, and games. More and more news content will be automatically generated, allowing journalists to focus on bigger and deeper stories. And AI will play a growing role in helping us to create and stylize our own content, such as videos, music, and artwork. In the financial service world, we are already seeing machine learning to help fairly and intelligently to predict credit card risk for new applicants or even anticipate delinquencies among existing customers. And many similar advances are in the work as we speak.
Insurance claim will be assessed by machine learning agents. Banking will become even more virtual as conversation bots take over call centers or even in person bankers when managing finances. And as HSBC said earlier, our own perception will be augmented with intelligent agents to flag criminal activities such as money laundering or fraud. Last but not the least example here, healthcare is among the most profound applications of AI for truly improving peoples' lives. We have already seen some incredible AI achievements in recent years. A few months ago, my colleagues at Google Brain have shown that using a deep learning algorithm, a computer can detect signs of diabetic retinopathy, a disease that could potentially blind more than 400 million people. Now imagine that kind of insight spanning the entire healthcare industry. So many forms of visual diagnosis may soon be automated to help doctors and reduce overhead and errors, and extending treatment to the underserved population. Machines can also help to handle clerical tasks such as scribing doctor visits, managing chronic diseases, leading to more reliable and faster services.
And this will accumulate into in full scale smart hospitals and homes with intelligent sensors to track hospital activity, keep patients safe, ensure adherence to hygiene practices, and augment surgical protocols. I hope you're excited just as I am about the opportunities that AI and machine learning can deliver. But this remains a field of high barriers. It requires rare expertise and resources few companies can afford on their own. That's why cloud is the ideal platform for AI. That is also why we're making huge investments in cloud AI that will emerge over the next year in the form of powerful, easy to use tools that will give every cloud customer an app into this field. In other words, Google Cloud is democratizing AI. This entails four broad steps, democratizing computing, democratizing algorithms, democratizing data, and democratizing talent and expertise. Let's talk about each of – what each of these means. First and foremost, AI requires enormous computing. Today, a deep learning algorithm that can easily boast tens of millions of parameters and billions of connections.
Training and using such models requires computational resources. Of course that is exactly what the cloud was designed to deliver. Last year we introduced the beta version of Cloud ML Engine. Today I am here to announce its general availability. Cloud ML Engine is a platform that can harness all of the power – computing power and deliver it to you transparently. Simply put, you develop the machine learning models however you like using familiar tools like the TensorFlow Library in your own environment. ML Engine allows you to focus on the creativity of your solution and leave the infrastructure to us. Then when it's time to train those models, upload them to the cloud where ML Engine can do it much faster and at a much larger scale. Finally, deploy the result anywhere from your own premise to a mobile device where it can put its training to use to solve real-world problems. But even with the compute power in the world, AI remains among the most complex field in computer science, and that is still a serious obstacle for many enterprise and customers.
For developers not quite ready to build their own models, the easiest way to put AI to use today is through one of the APIs Google has provided to deliver fully trained machine learning models to tackle common problems. These APIs are like a switch that immediately activate an intelligent component in any application, allowing it to understand speech and photos or translate text or parse natural language. But there is a lot more to Google's depth and breadth of AI technology. At Google, we have numerous research teams housing an enormous amount of ongoing AI research, spanning many areas of AI and machine learning. Our researchers are some of the most prolific authors of scientific papers at top AI journals and conferences and our teams are frequent winners of best papers and AI competitions. And the results of this work are quickly turned into products and services that we want to deliver to our customers. So I am especially eager to announce some of the latest products of that effort.
The Vision API has been under steady development and features some significant new capabilities. First is an expansion of the API's metadata to recognize millions of entities from Google's knowledge graph from images that are available on the web. We are now using the same metadata that powers the entire Google Image Search. Second, an enhanced optical character recognition capable of retrieving text from images of text heavy documents such as legal contracts and other complex paperwork. But the world of pixels go beyond just pictures. In fact, videos are among the most prevalent form of internet data. YouTube alone sees hundreds of hours of videos uploaded every minute. Understanding the rich content of videos has been a tremendous technology challenge for many years. In fact, many of us computer vision researchers, we have often considered videos the dark matter of the digital universe. Today I am very excited to announce an entirely new API powered by machine intelligence, the video intelligence API.
I would like to introduce my colleague Sara Robinson to demonstrate this API in more detail. Sarah. >> SARA ROBINSON: Thank you, Fei-Fei. Thank you. So the best way to experience the video API is through a live demo. And let's start by taking this video of a Super Bowl commercial for Google Home. And I'm going to play the first few seconds. We can see that it starts with a mountain landscape and we see a house, a city street, then it goes to a dog and a garage. So lots of scene changes happening in this video and if we were to manually categorize what is happening throughout it, we'd need to watch the entire thing and write down what was happening in every scene. Luckily the video API takes care of this for us with just a single REST API request. So it tells us two things. One, at a high level it tells us what is this video about and then it also tells us at a more granular level what labels it finds in the video in each scene. So if we scroll down here, we can see it identifies a dog and it can tell us exactly where in the video that dog appears.
It also identifies at the end of the video, there is a birthday cake and if we scroll down a bit more, we can see that not only does it know it's a dog, it knows what type of dog it is, that it's a dachshund. And if we scroll down through the rest of the labels, we can see that it also successfully identifies that mountain pass scene from the beginning. So this is what the API can do with one video, but you likely have more than one video that you want to analyze. So let's take a look at how a company might use the video intelligence API. A media publisher could have hundreds of petabytes of video data sitting in storage buckets and one common thing they might want to do is create a highlight reel focused on a specific type of content or search their large library for a specific entity. So let's see how we would use the video intelligence API to search a large library of videos given all of this metadata that we get back from it. So we've got a lot of videos here and let's say this media publisher has hours of sports video but they only want to find the content relevant to baseball.
So let's go ahead and search our library here for baseball videos. And we can see that not only does it show us which videos have baseball, it tells us exactly when in those videos baseball appears. My favorite example is this one. We have this video which only has a tiny bit about baseball but it's able to identify that clip for us, whereas if we were to manually do this, we'd have to watch the whole video looking for that specific scene. So if you click on this scene, we can see that this is from last year's Year in Search video when the Cubs won the World Series. So let's do one more search. I live on the East Coast where it's pretty cold right now. I have heard there's been a ton of rain in SF this past year. I think we can all agree it'd be pretty nice to be on a beach right now. And while machine learning can't take us there, it can do the next best thing and find all of the beach clips in our video library for us. So let's search for our beach videos and then we can click to all of our beach clips in the videos below.
So as you saw through this demo, the video intelligence API makes it easy to quickly and easily understand a large library of video content, something that was almost impossible just a few months ago. Tasks that used to take hours now take seconds with the video intelligence API and I am excited to make it available to all of you today. Thank you. I'm going to hand it back to Fei-Fei. >> FEI-FEI LI: Thank you. Thank you, Sara. So I am so excited to see this as a computer vision researcher. I have seen my field working on video understanding for decades and now finally we are beginning to shine light onto the dark matter of the digital universe and provide values to our customers who can use it to harness the enormous amount of information embedded in these videos. Now let's go on. Data is the next piece of the democratization puzzle. Just as we learned through a lifetime of exposure to the world to gain our human intelligence, AI requires a huge amount of data to develop its own insight.
But these data sets are among the steepest barriers to overcome. I have a lot of personal experience of this, having led the development of the image net data set which provides over fifteen million label images to the machine vision community. Many of you are now familiar with the history after image net. In 2012, it became one of the most important enablers of the deep learning revolution. To this day, it is still one of the most used training data sets and benchmarks of deep learning algorithms. While the results of image net have been incredible, the long, difficult journey of putting it together was a tremendous testament of how great the challenge still remains. What we need is a more scalable and effective way to democratize data to more data scientists, machine learning developers, domain experts, and eventually to our business. That is why I am thrilled to make the next announcement, Google Cloud's acquisition of Kaggle. For years, led by co-founders Anthony Goldbloom and Ben Hamner, the Kaggle team, has been building an unprecedented community of over 850,000 data scientists, hosting contests, and making new data sets publicly available.
By merging with Google Cloud Platform, we're giving this community direct access to the most advanced machine learning environment as well as providing a direct path to market their models. Working together with Kaggle, we're empowering the largest concentration of machine learning talent in the world. In fact, Kaggle is already partnering with Google Cloud and research to host the largest video understanding competition called the YouTube 8 million video understanding challenge. So speaking of talent and expertise, we're being – we've also been extremely committed to help our partners and customers to develop more machine learning and AI expertise at the levels they need. At Google, we've always made significant investment in research. Every year, Google gives large grants to over 250 academic research projects worldwide, supports dozens of PhD students, and hosts thousands of interns. Moreover, the Google Brain Residency Program recognized that expertise in AI will be an increasingly important resource in years ahead and is taking steps to find, educate, and empower the future leaders of this field.
At Google Cloud, in parallel with all of these efforts, we're equally committed to using our expertise to deliver real results right now to our customers. The advanced solution lab allows customers with more ambitious goals to partner directly with Google to solve complex AI problems. Let's take the insurance company USAA as a recent example. Many of their engineers were well versed in data size and some even had a background in machine learning. But they needed help to build a true foundation of expertise. To do this, a team of USAA developers came to Google's Advanced Solutions Lab where they learned directly from our own machine learning engineers and experts. That team now is hard at work putting their new skills to use with additional teams being trained in the same way. So I think the most meaningful technologies are the ones that transform a precious resource into something that can benefit everyone. The printing press helped literacy expand beyond the privileged, made books so affordable that they could fill the shelves in the homes and libraries all over the world.
The electric grid delivered power to the entire communities, turning heat and light from luxuries to staples of everyday life. The mass production of the industrial revolution and the artisanal objects that were once prohibitively expensive could now enrich the lives of hundreds and millions of people. And of course the internet has made everything from newspaper to university courses so easy to share that they can reach a worldwide audience overnight, often for free. What these examples have in common is the transformation from exclusivity to ubiquity. I believe AI can deliver this transformation at a scale we've never seen and imagined before, to help spread the luxuries of the privileged few to the rest of us at a global scale. This is why I am inviting everyone in this audience to be part of this. We at Google Cloud are making the tools available but it's up to you to put them to use. And speaking of AI, it took a few years to convince our next speaker of the power – the sweeping power of AI.
So if you're still on this journey, it is really not a shame because you're in very good company. It is my honor and privilege to invite Mr. Eric Schmidt. >> ERIC SCHMIDT: Thank you very much, Fei-Fei. >> FEI-FEI LI: Hi. Good luck. >> ERIC SCHMIDT: Thank you. Fei-Fei said leave the infrastructure to us and I don't think anyone could have said it better. Last year when I was here, I said we will meet you where you are. What I thought about this year is just get to the cloud now. Just go there now. There is no time to waste anymore. There are lots of reasons and I think we've talked about them this morning, but imagine a model that goes something like this. You're sitting there and you are building something on a container on your laptop. You get it working and then you just release it to the cloud and it scales infinitely. That is how easy this is now. That is how easy it is for you to do this as an individual programmer. Now does this matter? Well it mattered in the last year.
Let's think about Pokémon Go, right? So here is a fantastic product which had fifty times more demand in its first two hours than ever planned in their most optimistic forecasts, and I'm pleased to say that our system expanded, right, that the container architecture and the use of Kubernetes actually could handle the load. And I'm quite convinced that there was no other way to handle such a global phenomenon. And you sit there and you go well, I'm not trying to be Pokémon Go. Well if you could, you'd be pretty happy. Think about the sort of global success. So you might as well plan for global success and infinite demand, and even if you don't hit it, your architecture will be alright and your costs will be lower. I'll give you another example. Start – well if it sounds like open source, right, using Kubernetes, Apache Beam, Spinnaker, using GRPC, Redis, HBase, you're going to have a blast. It's going to be a great week, right? I'll give you another example consistent with this.
We just had the strongest IPO in a long time in tech and snap and Snapchat. As part of that, when you read the narrative, there are two things that strike you. First was their incredibly fast software development in their app both on Android and iPhone and in their community with huge success, new models, new models of interaction which you all know and many of you use. But the other confusion that is interesting in their process was nobody could figure out how they could do this with so little capital and the answer is because they used our infrastructure, right? In a deal that is a hugely successful deal for both corporations. So you sit there and you go well why would they do that? I mean after all, had they spent two billion dollars in data centers, they would have two billion dollars' worth of data centers. Yeah, but then they'd be putting three billion and four billion and five billion and six billion in whereas this way they can ride the scale and the investment that we have done.
So are you not planning to be like Snapchat? Well I think everyone here who represents a corporation would be happy to be as successful as they are. It makes sense, right? But the interesting insight is in the last year we have done two things since this conference than I am particularly proud of. One Fei-Fei talked about which is the sort of making machine learning real at a commercial and enterprise grade scale. You saw the demos. You understand the message. I'll talk about that in a minute. But the other thing that we did is we took the Google network which is vastly better than anything else you've ever seen, all that dark fiber, all that special fiber, all the interconnect, and we made it directly accessible to the programs that you're using. So using Snap as an example, not only can they use our platform infrastructure but they get access to their global customers through our network by virtue of the way this works. That is a very big deal. So you say well, I'm only trying to get regional customers.
Dream big. Think about having customers in pretty much every country. You get the idea. So what I want you to do is I want you to sort of understand that we can do both great cloud, that is great technology in the cloud, but we can also now work with you as a customer and a partner to build a business that actually scales globally and which you make a lot of money which is ultimately what everybody cares about. So I want you to imagine that – and the good news is, that Fei-Fei talked about and the others have talked about it as well – we have this incredible leadership platform for the things that I think matter for the future. But the truth is that most of our customers are still struggling with the enormous challenge of their existing infrastructure. Most customers say that is a great speech but I'm still trying to deal with my non-X86 apps, my AS400 mainframe, all of the kind of stuff that they have and many of you work in such companies or run them. So what – how do you do that?
So let's imagine a sales call where I am your salesperson visiting you and we say what are we going to do? Well I'll tell you the first thing to do is take your X86 binaries that you have in some data center inside your company and move them to the Google VM. And you go huh. Well it turns out it's cheaper and if it's cheaper, that frees up some money to do the next step. So the first thing is the easiest one. Literally take the existing PCs and existing PC software that is X86 software specifically, and put it under the Google VM. What do you do with the existing systems? You leave them running. Makes perfect sense. That's phase one. What do you do next? What you do is you take that system. Now you've got it working. Half in the cloud, half not. And you say I am now carefully going to take the data out of all of these systems and put them in a modern scalable managed database, either SQL or non-SQL. How do I do that? Well we work with you to do that. And then of course overtime, you build and move that data to modern end to end services.
I'll bet my – the rest of my professional career that the future of your business is big data and machine learning applied to the business opportunities, customer challenges, and things before you. It's true whether it's the video API and intelligence service we just announced or more traditional classification or the new deep learning approaches that are being pioneered at Google and elsewhere. So what happens is at that point, you say okay, I managed to get the data over here and now I don't know what to do. Well Google has a lot of resources that we can throw at this. We have customer engineers ready to help you. We've got an office of the CTO to help you with technology. We've got solutions architects who actually do a whole business solution for you. We have an advanced solutions lab that actually showcases some of these things. We have professional services that you can work with in the ways that you would imagine. We have people who can – are called strategic customer engineers who help you build your cloud.
And we finally have customer reliability engineering to keep the thing running, right? So not only is it used to be we would say well we have this incredible technology derived from the way Google operates but we didn't have a full service product offering. We didn't have all of the service. We didn't have all of the people who could help you. And you're sitting there going well, do I really believe you? Well we have the references now. They are among you and you've heard some of them today. And what's interesting is that not only do you have to do that but you're going to need additional help, especially with the legacy systems. So we have system integrator partners. Examples that I wrote down, Pithion, Agosto, Guvnats, Sata. Global systems integrators like Accenture and PWC. So okay, that sounds like a pretty good pitch. The last time anybody looked at this, it takes years to make this transition. So that was another problem that we faced a year ago and we figured out how to solve that.
We're working now to get these conversions to occur in one month, two months, three months, four months. Why? Because time is everything and you – while you're doing this conversion, to some degree some of your customer experience software, some of your value added is sort of being held captive. So – another example, we have Lush which is a cosmetics retailer, move their point of sale in a month. Ocado rebuilt into the cloud in six hours. We used all of Evernote with three petabytes of data in three months. That is how fast in the model that I am describing, you can get there. So I think that there was a speed limit. That speed limit was defined by our ability to work with the data that you had and the install base that you had and moving it into this new model. The new model works. Trust me. And if you're doing a new build, you're clearly going to do that anyway because you're intelligent. The problem was you're stuck in between. You can't get to the new one.
You're still stuck on the old one. So I don't know. What are some examples? If you have data as an object, we now have a software mechanism that will take the data and – which we call by the way, simple transfer service, that will basically just move it into our cloud structure and just do it all over it. That is how the data gets there so quickly. You built on containers. Again, we can support every model of containers. You're built on Hadoop; we love Hadoop in the sense that it is very similar to the architectures that it was based on and it's easy to host it inside of our model or use something even more extensive like big query. You like building virtual machines? As I said, just move them straight over. So we've made huge strides in terms of engineering investment and sales and customer service investment to scale that. So how do you do this? Well in the first place, if you leave the infrastructure to us, we put thirty billion dollars – and I know because I approved it so it's real, right, into this platform.
Please do not attempt to duplicate it. You have better uses of your money. I would much rather have you take the money that you have and the talents that you have and build on top of this platform to provide that rapid iteration and that rapid extension in the model that I am describing. What is interesting is that we're continuing to take this stuff and make it stronger. We just launched Spanner and if you don't know what Spanner is, Spanner is a – in my view, a work of art in a computer science sense. It's a way of doing SQL, so it's a proper database, but it's both globally essentially replicated and also globally coherent at a scale of data that has never been seen before. And by the way, we use it. It's how Google works. And by the way, we released it a week ago for the cloud. We have a container builder that does the same thing. So if you think about it, your model is something like this. Big query provides petabyte scale analysis on demand. Big table provides millions of QPS.
Google Cloud Storage for the actual millions of objects, right? Again, the prices are very, very low. And all of this platform that I am describing, this get to the cloud now model, and most people by the way are still in the moving their X86s into VMs, getting some of the data out of the VMs, putting them into proper databases, right? So you're still in the sort of getting there phase. Once you have the data, you have an opportunity for real transformation. I think that big data is so powerful that nation states will fight over how much data matters, right, that he who has the data, that can do the analytics and the algorithms that Fei-Fei talked about at the scale that we're talking about will provide huge nation state benefits in terms of global companies and benefits for their citizens and so forth and so on. But this is all basically because once you have the data, you have to do one more thing. You have to change from writing programs to instead building programs that learn outcomes.
And what machine learning really is and AI really is is it is a change to the way you program. And over and over again, and we've talked about this to some length already as a company, we've seen because of vision, right, we have the possibility of drastically reducing the number of deaths in automobile accidents and truck accidents, a big deal, right? A huge deal. And by the way, accidents in cars are going up right now in America because distractors appear to be – drivers appear to be distracted by the very technology that is going into the cars. So we've got to solve that problem and we've got to do it now. That is happening. In healthcare, in pathology, radiology, all of these sort of patient-centered issues, we're not that different from each other and the machine learning and collaborative learning that is now possible really will produce amazing healthcare outcomes. And there is a possibility that the kind of intelligence that is going to be buildable on these platforms will really surpass the kinds of insights that the average person in a business is going to have.
We're seeing over and over again, people are using big data to do customer analysis, pattern matching analysis, and customer targeting that really does produce extra insight and that extra insight is worth billions and billions of dollars in their marketing programs and knowing it. So let me finish by saying that we're here for real. You're here for real. This is an incredibly serious mission, something I have wanted to do since I joined the company seventeen years ago. It's something that I know that the people you heard whenever they started, care a great deal about it. The company has both the money, the means, and the commitment to pull off a new platform of computation globally for everybody who needs it, and something which allows you to be satisfied that our principles which are basically about openness and openness access really will allow you both the freedom of choice – you won't be locked in – but also the freedom to innovate. When I look at our partners and I look at the speed with which they can now use their scarce resources which are always programmers, to scale their business solutions, their enterprise solutions, their customer solutions, their video solutions, and their marketing solutions, it just warms my heart.
It's something we've looked at – we've looked forward to for decades. With that, thank you very much and I'm going to bring you back to Diane. Thank you. >> DIANE GREENE: So much. Eric – it's always so wonderful to hear Eric's brilliant insights and perspectives. He was one of the original enterprise people way back when. So I want to just recap what you heard from our customers, our partners. You heard from Disney. They're doing a full lift and shift to Google Cloud. They're using – they're going after machine learning. I like to say bring the magic to the magic. Our SAP partnership is so broad. You heard about certifying HANA. You heard about integrating with G Suite, the machine learning partnership, and also this very interesting partnership we're doing for a data custodian to help our customers solve the difficult issues around compliance, regulatory security. And then you heard from our joint customer Colgate, a 211 year old company. You have to keep reinventing yourself to make it that long and they are transforming themselves today with G Suite.
And then Verizon, moving 150,000 employees to G Suite, again going after a cultural transformation and dealing with some really difficult issues around moving to the cloud in their environment. Then we had Home Depot, very progressive, forward looking retailer, looking to technology to get the advantage, looking to machine learning to get the advantage. Already taking advantage of Google's scale to get them through things like Black Friday. Then we had a very interesting look into one of the world's largest banks, HSBC, about how they're going to use Google Cloud and the technology and the machine learning to really streamline their operations and do things people didn't really realize was possible. And then we closed out with EBay. They definitely see Google Cloud as a technology that gives them huge competitive advantage. Very interesting how easily they were able to run their catalog on our cloud and work in a hybrid environment. Then of course we saw that wonderful demo where the chat bot running on Google Cloud was talking to Google Home, giving answers about the price of a camera in their catalog.
Just terrific stuff. I want to also you know – where are all of the product announcements? All of the product announcements – we have dozens of them. They're tomorrow when you'll hear from our leaders. You'll hear from Urs Hölzle. You'll hear from Brian Stevens. You'll hear from Prabhakar Raghavan around G Suite. You'll hear from Chet Kapoor, the CEO of Apogee, telling you all kinds of new products that we're bringing out and where we're going and quite a bit of vision. Then Friday it's about developers through and through. It's about open source, startups, and Sam Ramji will lead that up. Before I wrap, I want to really thank all of our partners, our precious partners, all 150 of them on the floor. I really look forward to running into you on the showcase floor and personally, I also want to express my deep appreciation to all of the thousands of people in Google Cloud. I mean, you're amazing people. It's why I'm at Google. And the hard work you've done over the last year, you know, and how smart and excellent your work is.
Much appreciation. I want to remind you – we're going to take a break but at 12:30, we're going to have two real internet giants. I was a judge in the first Queen Elizabeth Prize for Engineering. I think it's now in its third year. Vint Cerf and Marc Andreesen were two of the winners for inventing the internet. Those two haven't skipped a beat. They are actively leading and defining our world and technology and that's an ongoing basis. They'll be here for a discussion with Quentin Hardy. So with that I'm really wrapping it up. It's been a long keynote. Thank you for staying. We really appreciate it. And hey everybody. Enjoy the show. Thank you very much.
Hear from Diane Greene, SVP of Google Cloud; Sundar Pichai, CEO of Google; Eric Schmidt, Chairman of Alphabet and Fei-Fei Li, Chief Scientist for Google Cloud Machine Learning and AI and Professor of Computer Science at Stanford. Our lineup of executives will discuss what Google Cloud offers today and discuss Google Cloud’s vision for the future. Attendees will also hear how our customers and partners are embracing the cloud in new and innovative ways.
Missed the conference? Watch all the talks here: https://goo.gl/c1Vs3h