1 00:00:00,540 --> 00:00:05,530 I'd like to show you, in more detail, what we are going to build in this course. 2 00:00:05,530 --> 00:00:11,670 For starters, we are going to build this in IBM's cloud platform, called Bluemix. 3 00:00:11,670 --> 00:00:15,990 Bluemix enables developers to rapidly build, deploy, and 4 00:00:15,990 --> 00:00:17,925 manage cloud applications. 5 00:00:17,925 --> 00:00:23,460 And easily tap into IBM's services, like the Watson APIs. 6 00:00:23,460 --> 00:00:26,460 This means you don't need to set up a server or 7 00:00:26,460 --> 00:00:29,260 anything special to run this chat bot. 8 00:00:29,260 --> 00:00:33,650 We set it up in Bluemix and then you can use it immediately. 9 00:00:33,650 --> 00:00:37,980 Take a moment and create a new free account for your app. 10 00:00:37,980 --> 00:00:42,870 Search for Bluemix or use the link in the teacher's notes to come to 11 00:00:42,870 --> 00:00:47,730 this page and then follow the simple prompts to create an account. 12 00:00:49,020 --> 00:00:53,670 Now, I will log into my account to show you some fully functional examples 13 00:00:53,670 --> 00:00:55,485 of apps built with Watson. 14 00:00:56,770 --> 00:01:01,430 As you can see from this screen, I have already logged into my Bluemix. 15 00:01:02,450 --> 00:01:05,370 I want to bring your attention to the Catalog tab. 16 00:01:05,370 --> 00:01:10,100 That's exactly where this page is landed at. 17 00:01:10,100 --> 00:01:16,620 And if you notice, there are a lot of services on our platform as a service. 18 00:01:16,620 --> 00:01:18,460 And not just Watson services. 19 00:01:18,460 --> 00:01:22,020 Blockchain, DevOps, Finance, and so forth. 20 00:01:22,020 --> 00:01:25,260 I want to bring your attention to the Watson services down here. 21 00:01:26,640 --> 00:01:29,720 Currently, we have 12 services. 22 00:01:29,720 --> 00:01:33,580 We would be working closely with the Conversation service and 23 00:01:33,580 --> 00:01:35,590 the Discovery service. 24 00:01:35,590 --> 00:01:40,380 Interesting to note that some of these other services are also built 25 00:01:40,380 --> 00:01:43,510 within the Conversation and the Discovery service. 26 00:01:43,510 --> 00:01:44,510 For example, 27 00:01:44,510 --> 00:01:50,800 the Natural Language Classifier service is built inside the Conversation service. 28 00:01:50,800 --> 00:01:56,290 The Natural Language Understanding and the Retrieve and 29 00:01:56,290 --> 00:02:01,500 Rank services are built within the Discovery service. 30 00:02:01,500 --> 00:02:06,544 Now, let me bring your attention to one of my favorite places, and yours will be 31 00:02:06,544 --> 00:02:12,786 robust with applications before long, and that Is the Dashboard field. 32 00:02:15,750 --> 00:02:20,752 As you can see I happen to have 9 applications built and 33 00:02:20,752 --> 00:02:27,955 the 16 services that cater to those applications that I have running above. 34 00:02:29,005 --> 00:02:32,542 And this will be very much the same scenario that you would have. 35 00:02:33,585 --> 00:02:38,090 I want to bring your attention to a number of interesting services. 36 00:02:38,090 --> 00:02:40,860 Let's start with my car conversation. 37 00:02:40,860 --> 00:02:46,240 If you recall, this is very much the cognitive dashboard in your car 38 00:02:46,240 --> 00:02:51,240 where you speak with the machine and you issue commands. 39 00:02:51,240 --> 00:02:52,840 You don't press any buttons. 40 00:02:52,840 --> 00:02:56,920 You just tell turn on the wipers and turn on the lights and so forth. 41 00:02:56,920 --> 00:02:57,610 Let's try that. 42 00:03:00,590 --> 00:03:05,394 Notice one of the very first things that took place is that my browser 43 00:03:05,394 --> 00:03:07,428 asked to share my location. 44 00:03:07,428 --> 00:03:11,640 This is something that you will discover in your exercises. 45 00:03:11,640 --> 00:03:16,330 And you will make your browser also Geo location aware, because at some 46 00:03:16,330 --> 00:03:22,040 point we're going to ask how is the weather while we are driving the car. 47 00:03:22,040 --> 00:03:26,980 And so the browser takes a look at your actual location where you are and 48 00:03:26,980 --> 00:03:32,870 it would return back the exact true weather live at that very location. 49 00:03:32,870 --> 00:03:34,840 So I'm going to click share location. 50 00:03:35,950 --> 00:03:39,530 Very well, it begins with, Hi, it looks like a nice drive today. 51 00:03:39,530 --> 00:03:41,420 What would you like to do? 52 00:03:41,420 --> 00:03:44,400 I'll perhaps ask the question. 53 00:03:49,042 --> 00:03:52,750 I'd like you to note that I have mistyped turn on wipers. 54 00:03:54,070 --> 00:03:58,100 But Watson understands the semantics behind my syntactic. 55 00:03:58,100 --> 00:04:00,890 It knows that I want to turn on the wipers. 56 00:04:00,890 --> 00:04:04,410 This actually is the power of the Natural Language Classifier 57 00:04:04,410 --> 00:04:07,290 built within the Conversation system. 58 00:04:07,290 --> 00:04:09,790 I may ask the following question. 59 00:04:15,532 --> 00:04:16,890 It's a dialogue. 60 00:04:16,890 --> 00:04:17,420 Sure thing. 61 00:04:17,420 --> 00:04:18,810 Which genre would you prefer? 62 00:04:18,810 --> 00:04:19,942 Jazz is my favorite. 63 00:04:19,942 --> 00:04:22,150 May be I like rock. 64 00:04:24,510 --> 00:04:28,390 Now you can imagine if you are connected to Spotify, for 65 00:04:28,390 --> 00:04:33,730 example, you could use the APIs to actually play some music on your car. 66 00:04:33,730 --> 00:04:36,920 But we are indeed connected to another entity, and 67 00:04:36,920 --> 00:04:40,280 that is the weather company, the Wunderground company. 68 00:04:40,280 --> 00:04:42,100 So I'm going to ask the following question. 69 00:04:49,078 --> 00:04:52,863 That is the exact location that I happen to be in, and 70 00:04:52,863 --> 00:04:58,470 right now it happens to be low 70s in Orlando where we are running this temp.