WEBVTT 00:00:00.000 --> 00:00:04.970 align:middle line:90% 00:00:04.970 --> 00:00:08.946 align:middle line:90% [MUSIC PLAYING] 00:00:08.946 --> 00:00:18.900 align:middle line:90% 00:00:18.900 --> 00:00:19.560 align:middle line:90% Hello. 00:00:19.560 --> 00:00:21.330 align:middle line:90% Hello, everyone. 00:00:21.330 --> 00:00:23.900 align:middle line:90% Good morning. 00:00:23.900 --> 00:00:26.350 align:middle line:90% [NON-ENGLISH SPEECH] 00:00:26.350 --> 00:00:31.030 align:middle line:84% Come on, people from Indonesia, Malaysia, Singapore. 00:00:31.030 --> 00:00:34.750 align:middle line:90% [NON-ENGLISH SPEECH] 00:00:34.750 --> 00:00:35.860 align:middle line:90% Wonderful. 00:00:35.860 --> 00:00:38.830 align:middle line:84% It's an honor and a privilege to have all of you 00:00:38.830 --> 00:00:43.600 align:middle line:90% here for Oracle OpenWorld Asia. 00:00:43.600 --> 00:00:46.480 align:middle line:84% This is the first for us, and we are 00:00:46.480 --> 00:00:50.710 align:middle line:84% so happy to have all of you from so many countries 00:00:50.710 --> 00:00:53.460 align:middle line:90% join us for those two days. 00:00:53.460 --> 00:00:55.140 align:middle line:84% Some of you come, of course, from here-- 00:00:55.140 --> 00:00:59.220 align:middle line:84% Singapore, and next door, Malaysia. 00:00:59.220 --> 00:01:04.410 align:middle line:84% But also, from Indonesia and Thailand and Vietnam. 00:01:04.410 --> 00:01:06.910 align:middle line:90% Many more countries. 00:01:06.910 --> 00:01:09.880 align:middle line:84% Some of you come from pretty far away-- 00:01:09.880 --> 00:01:15.380 align:middle line:90% Australia, India, Japan, China. 00:01:15.380 --> 00:01:19.580 align:middle line:84% We are delighted and very grateful to have all of you 00:01:19.580 --> 00:01:25.030 align:middle line:84% with us for those fantastic two days. 00:01:25.030 --> 00:01:30.580 align:middle line:84% I can tell you that the Oracle crew has been working so 00:01:30.580 --> 00:01:37.140 align:middle line:84% hard to make this fantastic use of your time, 00:01:37.140 --> 00:01:43.230 align:middle line:84% because we know that you are all so very busy-- 00:01:43.230 --> 00:01:45.780 align:middle line:90% very, very busy. 00:01:45.780 --> 00:01:52.590 align:middle line:84% It's very hard, isn't it, to manage in this digital age. 00:01:52.590 --> 00:01:55.610 align:middle line:90% You know, just when you think-- 00:01:55.610 --> 00:01:57.960 align:middle line:90% and that never lasts long-- 00:01:57.960 --> 00:02:03.760 align:middle line:84% that things are OK, just when your business is growing, 00:02:03.760 --> 00:02:08.440 align:middle line:84% your systems are up and running, and even your network 00:02:08.440 --> 00:02:14.890 align:middle line:84% is performing, this is just when something else happens 00:02:14.890 --> 00:02:19.020 align:middle line:84% that throws all of that in the air again. 00:02:19.020 --> 00:02:20.910 align:middle line:90% So it's constant. 00:02:20.910 --> 00:02:29.520 align:middle line:84% You constantly have to worry, anticipate, think, be ready. 00:02:29.520 --> 00:02:35.940 align:middle line:84% You have to worry about security breaches, don't you? 00:02:35.940 --> 00:02:39.990 align:middle line:84% Well, I hope you do, because security breaches 00:02:39.990 --> 00:02:43.410 align:middle line:90% break careers every day. 00:02:43.410 --> 00:02:47.280 align:middle line:84% They also sink companies completely. 00:02:47.280 --> 00:02:49.620 align:middle line:90% Look at front page news. 00:02:49.620 --> 00:02:51.670 align:middle line:90% It's all over. 00:02:51.670 --> 00:02:53.510 align:middle line:90% Very tough. 00:02:53.510 --> 00:02:56.110 align:middle line:90% It's not a question of if. 00:02:56.110 --> 00:02:59.020 align:middle line:84% It's just a question of when you will get 00:02:59.020 --> 00:03:03.430 align:middle line:90% a major attack on your systems. 00:03:03.430 --> 00:03:06.310 align:middle line:84% It's not by coincidence that there are, today, 00:03:06.310 --> 00:03:10.210 align:middle line:84% more than three million open jobs just 00:03:10.210 --> 00:03:13.790 align:middle line:90% for cybersecurity specialists. 00:03:13.790 --> 00:03:17.740 align:middle line:84% You have to constantly worry about costs. 00:03:17.740 --> 00:03:22.300 align:middle line:84% The sheer volume of transactions, users, 00:03:22.300 --> 00:03:25.880 align:middle line:84% internal users but also external users-- 00:03:25.880 --> 00:03:30.780 align:middle line:84% the sheer volume of terabytes that you have to handle 00:03:30.780 --> 00:03:36.075 align:middle line:84% has skyrocketed in the last two years, all because of digital. 00:03:36.075 --> 00:03:38.870 align:middle line:90% 00:03:38.870 --> 00:03:43.690 align:middle line:84% And you have to worry about keeping 00:03:43.690 --> 00:03:50.110 align:middle line:84% your competitive edge over your competitors constantly. 00:03:50.110 --> 00:03:53.830 align:middle line:84% Have you anticipated the next big thing just 00:03:53.830 --> 00:03:56.800 align:middle line:84% around the corner that's going to redistribute everything 00:03:56.800 --> 00:03:59.070 align:middle line:90% once more? 00:03:59.070 --> 00:04:01.240 align:middle line:90% Do you have the right skills? 00:04:01.240 --> 00:04:03.930 align:middle line:84% Have you anticipated the skills that you 00:04:03.930 --> 00:04:05.130 align:middle line:90% will need in the future? 00:04:05.130 --> 00:04:08.980 align:middle line:90% Are you hiring the right people? 00:04:08.980 --> 00:04:13.750 align:middle line:90% You worry so much. 00:04:13.750 --> 00:04:18.510 align:middle line:84% But I'm here to tell you don't worry. 00:04:18.510 --> 00:04:20.850 align:middle line:90% That's why we are here-- 00:04:20.850 --> 00:04:23.020 align:middle line:90% to help you out. 00:04:23.020 --> 00:04:32.272 align:middle line:84% Did you know that we spend over $5 billion every year on R&D? 00:04:32.272 --> 00:04:34.230 align:middle line:84% Now, I've been here talking with you for, what? 00:04:34.230 --> 00:04:36.720 align:middle line:90% Just a few minutes? 00:04:36.720 --> 00:04:40.710 align:middle line:84% Probably we spent $200,000 or more in those few minutes-- 00:04:40.710 --> 00:04:43.360 align:middle line:90% just on R&D. 00:04:43.360 --> 00:04:49.730 align:middle line:84% I can tell you this is a lot of innovation. 00:04:49.730 --> 00:04:55.500 align:middle line:84% This is a lot of code, a lot of new features. 00:04:55.500 --> 00:05:00.480 align:middle line:84% And all of that is focused on helping you not worry-- 00:05:00.480 --> 00:05:07.710 align:middle line:84% helping you out-manage this digital age. 00:05:07.710 --> 00:05:10.710 align:middle line:90% At the core of all of that R&D-- 00:05:10.710 --> 00:05:15.630 align:middle line:84% at the core of what we do throughout our solutions-- 00:05:15.630 --> 00:05:21.900 align:middle line:84% we embed one very critical technology, 00:05:21.900 --> 00:05:25.800 align:middle line:90% which is shaping this new era. 00:05:25.800 --> 00:05:32.380 align:middle line:84% And of course, that is artificial intelligence. 00:05:32.380 --> 00:05:36.910 align:middle line:84% AI has been around for decades, right? 00:05:36.910 --> 00:05:41.720 align:middle line:84% It has been making big promises for probably 30 years. 00:05:41.720 --> 00:05:44.020 align:middle line:90% It's been a hot topic. 00:05:44.020 --> 00:05:47.290 align:middle line:84% I almost said a hot potato for 30 years. 00:05:47.290 --> 00:05:49.690 align:middle line:84% Maybe some of you remember AI guy 00:05:49.690 --> 00:05:53.480 align:middle line:90% from when you were a student. 00:05:53.480 --> 00:05:55.540 align:middle line:90% I do. 00:05:55.540 --> 00:05:58.940 align:middle line:84% My first job, interestingly, was actually 00:05:58.940 --> 00:06:02.060 align:middle line:90% to lecture AI in university. 00:06:02.060 --> 00:06:03.500 align:middle line:90% That's how I started. 00:06:03.500 --> 00:06:07.880 align:middle line:90% That was 32 years ago. 00:06:07.880 --> 00:06:12.560 align:middle line:84% And oddly enough, it was just next door. 00:06:12.560 --> 00:06:16.430 align:middle line:84% It was in University Malaya in Malaysia. 00:06:16.430 --> 00:06:19.400 align:middle line:84% That's where I started 32 years ago. 00:06:19.400 --> 00:06:23.760 align:middle line:84% I have fond memories of those two years. 00:06:23.760 --> 00:06:25.940 align:middle line:84% And the time, we were all so excited 00:06:25.940 --> 00:06:29.800 align:middle line:84% about AI and how it would change the world. 00:06:29.800 --> 00:06:31.510 align:middle line:90% We were right. 00:06:31.510 --> 00:06:33.690 align:middle line:90% We were right. 00:06:33.690 --> 00:06:40.500 align:middle line:84% In hindsight, maybe 28 years too early, but fundamentally right. 00:06:40.500 --> 00:06:44.490 align:middle line:90% Now AI is primetime. 00:06:44.490 --> 00:06:46.200 align:middle line:90% It is ready. 00:06:46.200 --> 00:06:49.940 align:middle line:90% There's no arguing around it. 00:06:49.940 --> 00:06:51.770 align:middle line:90% For me, the turning point-- 00:06:51.770 --> 00:06:54.560 align:middle line:84% and you I'm sure you heard about that-- the turning point 00:06:54.560 --> 00:07:00.740 align:middle line:84% was when neural nets finally beat humans at go. 00:07:00.740 --> 00:07:04.260 align:middle line:90% That was march 2016. 00:07:04.260 --> 00:07:06.980 align:middle line:90% Lee Sedol-- Korean, of course-- 00:07:06.980 --> 00:07:12.810 align:middle line:84% world champion at Go, has played Go his entire life, benefits 00:07:12.810 --> 00:07:17.980 align:middle line:84% from 2,500 years of great masters' knowledge, 00:07:17.980 --> 00:07:21.900 align:middle line:90% beaten by AI. 00:07:21.900 --> 00:07:25.740 align:middle line:84% For me, that was a turning point. 00:07:25.740 --> 00:07:30.380 align:middle line:84% You know, humans-- we've been beaten at chess by computers, 00:07:30.380 --> 00:07:32.230 align:middle line:90% 20 years ago. 00:07:32.230 --> 00:07:32.800 align:middle line:90% Right? 00:07:32.800 --> 00:07:35.710 align:middle line:84% But honestly speaking-- no disrespect for those of you who 00:07:35.710 --> 00:07:37.312 align:middle line:90% play chess-- 00:07:37.312 --> 00:07:38.770 align:middle line:84% I don't want to be too provocative, 00:07:38.770 --> 00:07:42.460 align:middle line:90% but chess is a simple play. 00:07:42.460 --> 00:07:46.760 align:middle line:84% Chess can be beaten by brute force. 00:07:46.760 --> 00:07:49.380 align:middle line:90% Go cannot. 00:07:49.380 --> 00:07:51.620 align:middle line:84% And we've known that for decades. 00:07:51.620 --> 00:07:54.070 align:middle line:84% And that's why it took so long-- it took 30 years 00:07:54.070 --> 00:07:56.800 align:middle line:90% to finally beat humans at Go. 00:07:56.800 --> 00:07:58.720 align:middle line:90% Maybe some of you play Go. 00:07:58.720 --> 00:08:02.230 align:middle line:84% I play a little Go, amateur, with my son. 00:08:02.230 --> 00:08:05.230 align:middle line:84% This is a game where the level of complexity, 00:08:05.230 --> 00:08:07.870 align:middle line:84% the level of combinations, of different positions 00:08:07.870 --> 00:08:12.680 align:middle line:90% on the board game, is gigantic. 00:08:12.680 --> 00:08:15.890 align:middle line:84% I don't know whether you realize why this is such a turning 00:08:15.890 --> 00:08:17.140 align:middle line:90% point. 00:08:17.140 --> 00:08:20.760 align:middle line:84% There is no chance you can beat Go by brute force. 00:08:20.760 --> 00:08:22.770 align:middle line:90% You need intelligence. 00:08:22.770 --> 00:08:25.340 align:middle line:84% You need very, very deep learning. 00:08:25.340 --> 00:08:27.390 align:middle line:90% No other way. 00:08:27.390 --> 00:08:31.470 align:middle line:84% Just to give you a sense, there are more board positions on Go, 00:08:31.470 --> 00:08:34.500 align:middle line:84% on the board, 19 by 19, than there 00:08:34.500 --> 00:08:38.840 align:middle line:90% are atoms in the universe. 00:08:38.840 --> 00:08:42.710 align:middle line:84% You probably don't believe me, but this is factually true. 00:08:42.710 --> 00:08:44.070 align:middle line:90% This is factually true. 00:08:44.070 --> 00:08:46.850 align:middle line:84% There is different math theories to assess how many positions in 00:08:46.850 --> 00:08:53.620 align:middle line:84% Go, but let's say it's around 10 of the power of 170. 00:08:53.620 --> 00:08:55.920 align:middle line:90% True. 00:08:55.920 --> 00:09:01.410 align:middle line:84% And the theoretical longest game you can play 00:09:01.410 --> 00:09:05.920 align:middle line:90% is 10 at the power of 50 moves. 00:09:05.920 --> 00:09:07.540 align:middle line:90% Just mind-blowing. 00:09:07.540 --> 00:09:08.800 align:middle line:90% You have to play really fast. 00:09:08.800 --> 00:09:12.310 align:middle line:84% I grant you that, because the universe, since the Big Bang, 00:09:12.310 --> 00:09:16.610 align:middle line:84% we've had around 10 at the power 17 seconds. 00:09:16.610 --> 00:09:18.610 align:middle line:84% So you would need to play around 10 at the power 00:09:18.610 --> 00:09:22.030 align:middle line:84% 30 moves per second since the beginning of the Big Bang 00:09:22.030 --> 00:09:24.180 align:middle line:90% to play that long game. 00:09:24.180 --> 00:09:25.300 align:middle line:90% OK. 00:09:25.300 --> 00:09:27.910 align:middle line:84% I know I lost all of you now, right? 00:09:27.910 --> 00:09:30.340 align:middle line:84% You're all saying, what is this geek guy? 00:09:30.340 --> 00:09:33.010 align:middle line:84% You know, once a geek, ever a geek, 00:09:33.010 --> 00:09:36.640 align:middle line:84% and I can see the Oracle crew here saying, oh, no. 00:09:36.640 --> 00:09:38.630 align:middle line:90% Here he goes again. 00:09:38.630 --> 00:09:41.420 align:middle line:84% Promise-- artificial intelligence 00:09:41.420 --> 00:09:46.740 align:middle line:84% is used for more interesting things than beating Lee Sedol. 00:09:46.740 --> 00:09:54.090 align:middle line:84% For example, with the aging population, all of us 00:09:54.090 --> 00:09:57.920 align:middle line:90% live healthier lives longer. 00:09:57.920 --> 00:10:04.720 align:middle line:84% Alzheimer's, cancer become huge, huge challenges. 00:10:04.720 --> 00:10:12.900 align:middle line:84% And AI is offering huge promise to help us. 00:10:12.900 --> 00:10:16.710 align:middle line:84% I was reading a research paper just recently on Alzheimer. 00:10:16.710 --> 00:10:20.670 align:middle line:84% They've trained a neural net on thousands and thousands 00:10:20.670 --> 00:10:23.550 align:middle line:90% of brain scans. 00:10:23.550 --> 00:10:28.890 align:middle line:84% It's learned so fast that now, that neural net can 00:10:28.890 --> 00:10:35.060 align:middle line:84% find very tiny, very early signs of risk of Alzheimer 00:10:35.060 --> 00:10:39.690 align:middle line:84% six years before the best human specialist can 00:10:39.690 --> 00:10:43.310 align:middle line:84% detect those signs and interpret them correctly. 00:10:43.310 --> 00:10:45.030 align:middle line:90% Huge hope. 00:10:45.030 --> 00:10:47.190 align:middle line:90% Huge hope coming from AI. 00:10:47.190 --> 00:10:49.800 align:middle line:90% 00:10:49.800 --> 00:10:51.840 align:middle line:90% Very excited about this. 00:10:51.840 --> 00:10:57.690 align:middle line:84% Yet, when you look at all the talks on AI, most of them 00:10:57.690 --> 00:11:01.500 align:middle line:90% are around bespoke or research-- 00:11:01.500 --> 00:11:04.670 align:middle line:90% advanced things. 00:11:04.670 --> 00:11:07.160 align:middle line:84% This is not the way we look at it at Oracle. 00:11:07.160 --> 00:11:11.840 align:middle line:84% When I said earlier that we embed AI in everything we do, 00:11:11.840 --> 00:11:13.310 align:middle line:84% this is not the way we think of it. 00:11:13.310 --> 00:11:16.430 align:middle line:84% We took a very different approach. 00:11:16.430 --> 00:11:21.310 align:middle line:84% We embed AI in your day-to-day tasks, 00:11:21.310 --> 00:11:25.860 align:middle line:90% in your day-to-day processes. 00:11:25.860 --> 00:11:31.440 align:middle line:84% We don't view AI as a separate, custom-built neural net 00:11:31.440 --> 00:11:35.100 align:middle line:84% that you will have to train on your own data 00:11:35.100 --> 00:11:38.600 align:middle line:84% until it becomes smart enough to help you out. 00:11:38.600 --> 00:11:41.670 align:middle line:84% That's not the way we look at it. 00:11:41.670 --> 00:11:44.190 align:middle line:84% We are in this unique position that we 00:11:44.190 --> 00:11:46.770 align:middle line:84% can train very specialized neural 00:11:46.770 --> 00:11:51.570 align:middle line:84% nets on many different business and technical problems 00:11:51.570 --> 00:11:56.570 align:middle line:84% and solve them for you out of the box. 00:11:56.570 --> 00:12:02.960 align:middle line:84% Our business applications-- our ERP Cloud, HCM Cloud, CX Cloud, 00:12:02.960 --> 00:12:06.460 align:middle line:84% sales, service, marketing, all of them-- 00:12:06.460 --> 00:12:11.980 align:middle line:84% benefit from embedded AI, very smart neural nets 00:12:11.980 --> 00:12:14.650 align:middle line:84% trained on gigantic quantity of data 00:12:14.650 --> 00:12:18.010 align:middle line:84% which are running in our cloud becoming super 00:12:18.010 --> 00:12:21.790 align:middle line:84% intelligent and able to provide help to you 00:12:21.790 --> 00:12:26.850 align:middle line:84% and your teams right as they are doing their daily job, 00:12:26.850 --> 00:12:30.080 align:middle line:90% and not as a separate thing. 00:12:30.080 --> 00:12:33.920 align:middle line:84% Think of being in a procurement process. 00:12:33.920 --> 00:12:36.560 align:middle line:84% We can have very smart recommendations 00:12:36.560 --> 00:12:39.770 align:middle line:84% right in the middle of that process on negotiation 00:12:39.770 --> 00:12:44.100 align:middle line:84% strategies for that specific procurement. 00:12:44.100 --> 00:12:45.800 align:middle line:90% Or think of HCM Cloud. 00:12:45.800 --> 00:12:50.600 align:middle line:84% We can provide you right out of the box very smart 00:12:50.600 --> 00:12:53.000 align:middle line:84% recommendations on who to interview. 00:12:53.000 --> 00:12:56.380 align:middle line:84% You've got this long list of 100 CVs-- 00:12:56.380 --> 00:12:58.270 align:middle line:84% are you going to screen 50 of them 00:12:58.270 --> 00:13:00.970 align:middle line:84% and really interview 50 of them like we do today 00:13:00.970 --> 00:13:03.220 align:middle line:90% until you go to a shortlist? 00:13:03.220 --> 00:13:06.400 align:middle line:84% I mean, AI, our neural net, is going to be able to tell you, 00:13:06.400 --> 00:13:11.380 align:middle line:84% oh, just interview those three- 95% chance one of those three 00:13:11.380 --> 00:13:14.820 align:middle line:84% will fit your job openings exactly. 00:13:14.820 --> 00:13:16.110 align:middle line:90% It's a game-changer. 00:13:16.110 --> 00:13:18.240 align:middle line:84% Think of that for talent management. 00:13:18.240 --> 00:13:20.520 align:middle line:84% Think of that for sales or marketing. 00:13:20.520 --> 00:13:24.955 align:middle line:84% Right out of the box, right inside your day-to-day core 00:13:24.955 --> 00:13:25.455 align:middle line:90% process. 00:13:25.455 --> 00:13:28.710 align:middle line:90% 00:13:28.710 --> 00:13:33.370 align:middle line:84% And of course we don't do that only for business applications. 00:13:33.370 --> 00:13:39.260 align:middle line:84% We obviously, obviously do that for our database. 00:13:39.260 --> 00:13:44.740 align:middle line:84% We put AI and machine learning everywhere in our database. 00:13:44.740 --> 00:13:49.870 align:middle line:84% This allows our database today to make split-second decisions 00:13:49.870 --> 00:13:56.650 align:middle line:84% on many things, like tuning, data recovery, etching, 00:13:56.650 --> 00:13:59.970 align:middle line:90% and security. 00:13:59.970 --> 00:14:04.740 align:middle line:84% Our database is now fully self-driving. 00:14:04.740 --> 00:14:10.390 align:middle line:84% It is the only self-driving database in the world. 00:14:10.390 --> 00:14:12.930 align:middle line:84% We call it the autonomous database. 00:14:12.930 --> 00:14:15.850 align:middle line:90% 00:14:15.850 --> 00:14:20.270 align:middle line:84% The autonomous database is self-patching. 00:14:20.270 --> 00:14:25.410 align:middle line:84% It removes human errors from the mix. 00:14:25.410 --> 00:14:29.280 align:middle line:84% Do you know that out of all of the security breaches 00:14:29.280 --> 00:14:35.840 align:middle line:84% that you read in front page news, 80% plus of them 00:14:35.840 --> 00:14:40.460 align:middle line:84% would have been avoided if the humans in charge 00:14:40.460 --> 00:14:44.870 align:middle line:84% had applied the latest patches, the latest security features 00:14:44.870 --> 00:14:46.460 align:middle line:90% had activated-- 00:14:46.460 --> 00:14:50.040 align:middle line:84% features that are available, and they didn't 00:14:50.040 --> 00:14:54.220 align:middle line:90% activate encryption and others. 00:14:54.220 --> 00:14:57.900 align:middle line:90% 80% were perfectly avoidable. 00:14:57.900 --> 00:15:00.540 align:middle line:84% Now, with the autonomous database, 00:15:00.540 --> 00:15:05.370 align:middle line:84% that level of human error is entirely managed and removed 00:15:05.370 --> 00:15:08.430 align:middle line:90% from the equation. 00:15:08.430 --> 00:15:13.590 align:middle line:84% All of those innovations in our suite of application cloud, 00:15:13.590 --> 00:15:20.110 align:middle line:84% in our database cloud, are now used widely all over the globe. 00:15:20.110 --> 00:15:24.510 align:middle line:84% But of course, in this region, you 00:15:24.510 --> 00:15:27.900 align:middle line:84% have also widely used them already. 00:15:27.900 --> 00:15:30.450 align:middle line:90% We've been here 31 years. 00:15:30.450 --> 00:15:33.570 align:middle line:84% We established shop here when I was finishing 00:15:33.570 --> 00:15:36.820 align:middle line:90% my days at University Malaya. 00:15:36.820 --> 00:15:42.820 align:middle line:84% And this region is hugely important for us. 00:15:42.820 --> 00:15:45.670 align:middle line:84% The last four years, I've been here almost every month. 00:15:45.670 --> 00:15:48.860 align:middle line:84% And I can see this is a vibrant region. 00:15:48.860 --> 00:15:52.510 align:middle line:84% There's no wonder why this region will lead 00:15:52.510 --> 00:15:54.790 align:middle line:90% the world in the next decade. 00:15:54.790 --> 00:15:57.730 align:middle line:84% For me, it's an obvious statement. 00:15:57.730 --> 00:16:01.880 align:middle line:84% So you have embraced these new technologies, 00:16:01.880 --> 00:16:04.420 align:middle line:84% these new solutions in the cloud, 00:16:04.420 --> 00:16:06.730 align:middle line:90% like no other region has. 00:16:06.730 --> 00:16:09.040 align:middle line:84% So I see a lot of amazing impact. 00:16:09.040 --> 00:16:11.950 align:middle line:84% Just one example here-- in Australia. 00:16:11.950 --> 00:16:17.040 align:middle line:84% APM-- that's Applied Precision Medicine. 00:16:17.040 --> 00:16:19.620 align:middle line:84% They are using our autonomous database 00:16:19.620 --> 00:16:25.300 align:middle line:84% to design treatments based on genetics. 00:16:25.300 --> 00:16:26.170 align:middle line:90% Isn't that cool? 00:16:26.170 --> 00:16:29.110 align:middle line:84% I mean, this is really the future of medicine, . 00:16:29.110 --> 00:16:32.480 align:middle line:84% and it's real for them in Australia. 00:16:32.480 --> 00:16:37.830 align:middle line:84% It will help all of us league live longer, healthier lives. 00:16:37.830 --> 00:16:40.940 align:middle line:84% In Bangladesh, the Ministry of Transport 00:16:40.940 --> 00:16:48.400 align:middle line:84% is using our cloud to build the longest bridge in the country. 00:16:48.400 --> 00:16:52.090 align:middle line:84% And that's also a game-changer for Bangladesh. 00:16:52.090 --> 00:16:54.460 align:middle line:84% This is going to connect the southwest 00:16:54.460 --> 00:16:59.470 align:middle line:84% with the capital, Dhaka, and it will boost the GDP 00:16:59.470 --> 00:17:01.960 align:middle line:90% in Bangladesh by more than 2%. 00:17:01.960 --> 00:17:03.160 align:middle line:90% Huge impact. 00:17:03.160 --> 00:17:05.260 align:middle line:90% In Vietnam, Bac Ky-- 00:17:05.260 --> 00:17:07.810 align:middle line:90% this is a logistic company-- 00:17:07.810 --> 00:17:10.589 align:middle line:84% is using our cloud, and in particular, 00:17:10.589 --> 00:17:15.250 align:middle line:84% IoT to track their trucks and transportations 00:17:15.250 --> 00:17:20.079 align:middle line:84% and parcels in a way that allows them now to find new revenue 00:17:20.079 --> 00:17:26.980 align:middle line:84% streams and cut their carbon footprint. 00:17:26.980 --> 00:17:30.460 align:middle line:84% And another example, just next door in Malaysia-- 00:17:30.460 --> 00:17:31.960 align:middle line:90% AirAsia. 00:17:31.960 --> 00:17:33.340 align:middle line:90% We all know AirAsia. 00:17:33.340 --> 00:17:38.290 align:middle line:84% They are using our ERP cloud to crunch numbers, 00:17:38.290 --> 00:17:41.560 align:middle line:84% and that helps them streamline their operations, 00:17:41.560 --> 00:17:45.000 align:middle line:84% grow their business, cut their costs. 00:17:45.000 --> 00:17:46.790 align:middle line:84% And actually, Tony Fernandes, the CEO, 00:17:46.790 --> 00:17:49.950 align:middle line:84% will be here tomorrow to talk about the experience 00:17:49.950 --> 00:17:55.170 align:middle line:84% of his team and how ERP cloud helped him. 00:17:55.170 --> 00:17:57.510 align:middle line:84% We have so many more of those stories. 00:17:57.510 --> 00:18:00.280 align:middle line:90% I could go on and on and on. 00:18:00.280 --> 00:18:03.350 align:middle line:84% What I'd like to do now, if that's OK, 00:18:03.350 --> 00:18:06.190 align:middle line:90% is leave you with a short video. 00:18:06.190 --> 00:18:10.510 align:middle line:84% This video will tell you about three stories 00:18:10.510 --> 00:18:17.430 align:middle line:84% of how our cloud has helped and had a profound social impact. 00:18:17.430 --> 00:18:20.400 align:middle line:84% Those stories are very close to my heart. 00:18:20.400 --> 00:18:22.300 align:middle line:90% You will see they are beautiful. 00:18:22.300 --> 00:18:26.040 align:middle line:84% And there are many more of those social impact stories 00:18:26.040 --> 00:18:29.550 align:middle line:90% that we are developing. 00:18:29.550 --> 00:18:33.690 align:middle line:84% This region, as I said, is vibrant. 00:18:33.690 --> 00:18:39.080 align:middle line:84% Every time I come you inspire me. 00:18:39.080 --> 00:18:42.840 align:middle line:84% So in turn, I hope that in those two days, 00:18:42.840 --> 00:18:46.890 align:middle line:90% we will inspire all of you. 00:18:46.890 --> 00:18:51.740 align:middle line:84% Thank you very much, and welcome to Oracle OpenWorld. 00:18:51.740 --> 00:18:56.150 align:middle line:90% [APPLAUSE] 00:18:56.150 --> 00:18:59.580 align:middle line:90% [MUSIC PLAYING] 00:18:59.580 --> 00:19:06.470 align:middle line:90% 00:19:06.470 --> 00:19:10.880 align:middle line:84% The apparel industry has received negative publicity 00:19:10.880 --> 00:19:12.020 align:middle line:90% for decades. 00:19:12.020 --> 00:19:16.670 align:middle line:84% You hear stories of accidents and there are no proper safety 00:19:16.670 --> 00:19:17.570 align:middle line:90% measures. 00:19:17.570 --> 00:19:22.830 align:middle line:84% We decided to do things a little differently. 00:19:22.830 --> 00:19:24.800 align:middle line:90% I co-founded MAS Holdings. 00:19:24.800 --> 00:19:29.210 align:middle line:84% I was very keen that we create the right environment in all 00:19:29.210 --> 00:19:31.040 align:middle line:84% our plants right from the beginning-- 00:19:31.040 --> 00:19:34.100 align:middle line:84% good infrastructure, good facilities, 00:19:34.100 --> 00:19:36.470 align:middle line:90% invest in good equipment. 00:19:36.470 --> 00:19:39.050 align:middle line:84% So MAS manufactures apparel for brands 00:19:39.050 --> 00:19:43.790 align:middle line:84% such as Victoria's Secret stores, Nike, Calvin Klein. 00:19:43.790 --> 00:19:46.400 align:middle line:84% And the business has grown successfully 00:19:46.400 --> 00:19:51.650 align:middle line:84% from a national company to a global company. 00:19:51.650 --> 00:19:55.420 align:middle line:84% We have 93,000 employees, and we have about 52 00:19:55.420 --> 00:19:58.870 align:middle line:84% plus manufacturing locations across the globe. 00:19:58.870 --> 00:20:03.480 align:middle line:84% We have always worked hard to be the best we can, 00:20:03.480 --> 00:20:06.120 align:middle line:84% and to bring out the best in our people. 00:20:06.120 --> 00:20:08.960 align:middle line:84% In a company that values its people, 00:20:08.960 --> 00:20:12.040 align:middle line:84% our premise of choosing Oracle to build 00:20:12.040 --> 00:20:16.870 align:middle line:84% the infrastructure that manages those people is very important. 00:20:16.870 --> 00:20:20.392 align:middle line:84% And we would not trust it with anyone else. 00:20:20.392 --> 00:20:28.264 align:middle line:90% 00:20:28.264 --> 00:20:32.200 align:middle line:90% [MUSIC PLAYING] 00:20:32.200 --> 00:20:39.100 align:middle line:90% 00:20:39.100 --> 00:20:45.550 align:middle line:84% In Japan, natural disaster threatens thousands of lives. 00:20:45.550 --> 00:20:48.070 align:middle line:84% The aim of the National Research Institute 00:20:48.070 --> 00:20:51.070 align:middle line:84% for Earth Science and Disaster Resilience 00:20:51.070 --> 00:20:56.220 align:middle line:84% is to protect people and their livelihoods. 00:20:56.220 --> 00:20:59.530 align:middle line:84% Oracle Cloud helps us share information 00:20:59.530 --> 00:21:03.910 align:middle line:84% to build safer cities and make sure response teams are always 00:21:03.910 --> 00:21:05.740 align:middle line:90% ready. 00:21:05.740 --> 00:21:09.580 align:middle line:84% We learn from every storm, earthquake, and tsunami 00:21:09.580 --> 00:21:11.635 align:middle line:90% so we can prepare for the next. 00:21:11.635 --> 00:21:14.300 align:middle line:90% 00:21:14.300 --> 00:21:17.130 align:middle line:84% It is not just our people that benefit. 00:21:17.130 --> 00:21:20.990 align:middle line:84% We share what we learn with people around the world. 00:21:20.990 --> 00:21:24.660 align:middle line:84% We trust the Oracle Cloud to keep our data secure, 00:21:24.660 --> 00:21:29.210 align:middle line:84% even when disaster strikes, so we can act fast in a crisis 00:21:29.210 --> 00:21:32.162 align:middle line:84% and build a safer future for everyone. 00:21:32.162 --> 00:21:40.910 align:middle line:90% 00:21:40.910 --> 00:21:43.840 align:middle line:90% [MUSIC PLAYING] 00:21:43.840 --> 00:21:47.590 align:middle line:84% One out of 140 children born anywhere in the world 00:21:47.590 --> 00:21:49.510 align:middle line:90% has a heart problem. 00:21:49.510 --> 00:21:53.350 align:middle line:84% In India, we produce 26 million babies a year. 00:21:53.350 --> 00:21:58.180 align:middle line:84% It's a huge number of kids who are born with a heart problem. 00:21:58.180 --> 00:22:00.910 align:middle line:84% Narayana Health was started with a single mission-- 00:22:00.910 --> 00:22:04.810 align:middle line:84% to build a hospital that would never have to turn anyone away 00:22:04.810 --> 00:22:07.940 align:middle line:90% for lack of funds. 00:22:07.940 --> 00:22:12.360 align:middle line:84% NH sees 20,000 patients a day, and they generate 00:22:12.360 --> 00:22:14.950 align:middle line:90% billions of lines of data. 00:22:14.950 --> 00:22:17.320 align:middle line:84% All of our data system is on a cloud. 00:22:17.320 --> 00:22:20.560 align:middle line:84% And ERP solutions are provided by Oracle. 00:22:20.560 --> 00:22:21.850 align:middle line:90% I'm a doctor. 00:22:21.850 --> 00:22:24.730 align:middle line:84% My job is saving lives and helping people. 00:22:24.730 --> 00:22:28.600 align:middle line:84% But when you run a hospital with a wafer-thin margin, 00:22:28.600 --> 00:22:31.690 align:middle line:84% you need to be very careful about your financial health. 00:22:31.690 --> 00:22:36.010 align:middle line:84% We need to have reliable data, real-time. 00:22:36.010 --> 00:22:40.140 align:middle line:84% We believe in God, but for everything else, we need data. 00:22:40.140 --> 00:22:49.259 align:middle line:90%