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Would you like to inspect the original subtitles? These are the user uploaded subtitles that are being translated: 1 00:00:09,650 --> 00:00:16,109 so what we do is we provide people flow 2 00:00:13,559 --> 00:00:18,509 we help people move in and between 3 00:00:16,109 --> 00:00:21,600 buildings in the cruelest and safest way 4 00:00:18,510 --> 00:00:25,260 globally we service more than 1.1 5 00:00:21,600 --> 00:00:29,099 million elevators and escalators we move 6 00:00:25,260 --> 00:00:32,189 more than 1 billion people every day if 7 00:00:29,099 --> 00:00:34,739 the equipment that we service are not 8 00:00:32,189 --> 00:00:37,620 operating we have a very significant 9 00:00:34,739 --> 00:00:39,360 impact on the way cities work people may 10 00:00:37,620 --> 00:00:41,250 not get to the work in the office 11 00:00:39,360 --> 00:00:44,010 building or people may have difficulties 12 00:00:41,250 --> 00:00:45,809 getting to their home we have many 13 00:00:44,010 --> 00:00:47,579 different types of customers we serve 14 00:00:45,809 --> 00:00:50,430 construction companies builders 15 00:00:47,579 --> 00:00:52,110 developers building owners and the 16 00:00:50,430 --> 00:00:54,660 expectations of our customers 17 00:00:52,110 --> 00:00:58,019 are increasing all the time they are 18 00:00:54,660 --> 00:01:00,000 expecting an oxide that is constant they 19 00:00:58,020 --> 00:01:03,030 are expecting transparency and 20 00:01:00,000 --> 00:01:04,709 predictability for what we do with 21 00:01:03,030 --> 00:01:06,689 Internet of Things we're going to be 22 00:01:04,709 --> 00:01:09,240 able to provide totally new types of 23 00:01:06,689 --> 00:01:11,490 services to our customers we looked at 24 00:01:09,240 --> 00:01:14,699 the whole market and quickly realized 25 00:01:11,490 --> 00:01:18,060 that IBM is clearly a leader in peyote 26 00:01:14,700 --> 00:01:20,210 and cognitive analytics we are using 27 00:01:18,060 --> 00:01:23,009 Watson IOT and it's positive 28 00:01:20,210 --> 00:01:25,770 capabilities in many different ways we 29 00:01:23,009 --> 00:01:28,799 can predict the condition of the 30 00:01:25,770 --> 00:01:30,470 elevator or escalator and that's why it 31 00:01:28,799 --> 00:01:32,570 helps our customers 32 00:01:30,470 --> 00:01:35,270 manage their equipment over the 33 00:01:32,570 --> 00:01:38,720 lifecycle in a much better way the NS 34 00:01:35,270 --> 00:01:40,399 could have have surprised Watson IOT is 35 00:01:38,720 --> 00:01:42,860 helping our field technician 36 00:01:40,400 --> 00:01:44,360 troubleshoot problems so when they face 37 00:01:42,860 --> 00:01:47,840 a problem they may not have seen before 38 00:01:44,360 --> 00:01:50,000 Watson can give them advisory and that's 39 00:01:47,840 --> 00:01:52,580 way have equipment up and running in 40 00:01:50,000 --> 00:01:55,610 much faster time than before we are also 41 00:01:52,580 --> 00:01:58,610 using IBM Watson to help our force 42 00:01:55,610 --> 00:02:00,860 sensor technicians perform their job and 43 00:01:58,610 --> 00:02:03,050 what is great with IBM Watson then it 44 00:02:00,860 --> 00:02:05,420 learns all the time the more exceed 45 00:02:03,050 --> 00:02:08,209 situation the more intelligent it 46 00:02:05,420 --> 00:02:11,600 becomes our customers no longer wants to 47 00:02:08,209 --> 00:02:13,670 buy product features they want to buy 48 00:02:11,600 --> 00:02:16,120 outcome what I think is the most 49 00:02:13,670 --> 00:02:18,500 exciting is that we can provide 50 00:02:16,120 --> 00:02:20,840 individualized services that 51 00:02:18,500 --> 00:02:23,090 specifically meet the needs of our 52 00:02:20,840 --> 00:02:25,880 customers it is no longer so that 53 00:02:23,090 --> 00:02:28,370 everyone has to get the same thing now 54 00:02:25,880 --> 00:02:33,549 our customers will get services and 55 00:02:28,370 --> 00:02:33,550 outcomes that fits their exactly 56 00:02:34,540 --> 00:02:38,299 [Music] 57 00:02:41,240 --> 00:02:44,490 [Music] 4169