1 00:00:00,000 --> 00:00:01,640 Interviewer: Hi there. Welcome to 2 00:00:01,640 --> 00:00:03,460 the Future Technologies Conference 3 00:00:03,460 --> 00:00:05,190 here in Vancouver, Canada. 4 00:00:05,190 --> 00:00:06,840 With me Computer Scientist 5 00:00:06,840 --> 00:00:07,700 El Sayed Mahmoud. 6 00:00:07,700 --> 00:00:08,870 Interviewer: Hi there. 7 00:00:08,870 --> 00:00:09,680 El Sayed: Hi 8 00:00:09,680 --> 00:00:10,970 Interviewer: Tell me what research 9 00:00:10,970 --> 00:00:12,850 are you you involved in at the moment? 10 00:00:12,850 --> 00:00:14,670 El Sayed: Yeah, my current research 11 00:00:14,670 --> 00:00:17,360 focuses on machine learning. 12 00:00:17,570 --> 00:00:20,980 We are developing data analytics 13 00:00:20,980 --> 00:00:25,620 algorithms that help us develop innovative 14 00:00:25,620 --> 00:00:28,460 solutions for health and business problems. 15 00:00:28,460 --> 00:00:30,350 Interviewer: Okay. Health and business 16 00:00:30,350 --> 00:00:32,280 problems. Anything in particular? 17 00:00:32,280 --> 00:00:34,270 Can you give me one example maybe? 18 00:00:34,270 --> 00:00:36,390 El Sayed: Okay. So one of my current 19 00:00:36,390 --> 00:00:39,720 projects just promotes using 20 00:00:39,740 --> 00:00:41,620 food as medicine. 21 00:00:41,620 --> 00:00:42,850 Interviewer: Okay. 22 00:00:42,850 --> 00:00:44,680 El Sayed: In this particular project 23 00:00:44,680 --> 00:00:47,270 we are trying to use data analytics to 24 00:00:47,390 --> 00:00:49,450 extract this information from 25 00:00:49,450 --> 00:00:51,390 scientific papers. 26 00:00:51,390 --> 00:00:53,640 I mean, the type of information we are 27 00:00:53,640 --> 00:00:57,640 looking for which link the food component 28 00:00:57,640 --> 00:01:01,140 in nutrition to a specific or particular 29 00:01:01,140 --> 00:01:03,490 disease like heart attack 30 00:01:03,490 --> 00:01:04,920 or something like that. 31 00:01:04,920 --> 00:01:06,950 The ultimate goal of this project is 32 00:01:06,950 --> 00:01:08,480 to build a huge database 33 00:01:08,480 --> 00:01:10,630 which will link this useful information 34 00:01:10,630 --> 00:01:13,780 and this in future will change the way 35 00:01:13,780 --> 00:01:15,660 we treat diseases to outweigh 36 00:01:15,660 --> 00:01:17,300 the side effects of the drugs. 37 00:01:17,300 --> 00:01:19,560 Interviewer: Does that mean that if I get 38 00:01:19,560 --> 00:01:21,680 a disease, then what will happen to me 39 00:01:21,680 --> 00:01:23,510 once your research is finished? 40 00:01:23,510 --> 00:01:26,380 El Sayed: Okay, so you will, some foods 41 00:01:26,380 --> 00:01:28,680 will be recommended for you and that's all. 42 00:01:28,680 --> 00:01:29,940 Interviewer: Okay. 43 00:01:29,940 --> 00:01:32,420 El Sayed: And that is the future for medicine. 44 00:01:32,420 --> 00:01:34,310 Interviewer: Okay, so you will tell me 45 00:01:34,310 --> 00:01:35,610 JJ eat this and this and this 46 00:01:35,610 --> 00:01:36,850 and that's good for you. 47 00:01:36,850 --> 00:01:38,880 El Sayed: Yes, and we started the first 48 00:01:38,880 --> 00:01:41,150 step by preparing just a huge database 49 00:01:41,150 --> 00:01:44,670 which examines all the papers published, 50 00:01:44,780 --> 00:01:47,400 scientific papers, and approve the results 51 00:01:47,400 --> 00:01:50,870 published related to which relate 52 00:01:50,870 --> 00:01:53,840 the food components in nutrition 53 00:01:53,840 --> 00:01:56,280 to a particular health condition. 54 00:01:56,280 --> 00:01:58,690 Interviewer: Okay. And what are the challenges 55 00:01:58,690 --> 00:02:01,160 that you are facing in this research? 56 00:02:01,160 --> 00:02:04,150 El Sayed: Yeah, in this research actually 57 00:02:04,150 --> 00:02:07,670 the main challenge it's common for 58 00:02:07,670 --> 00:02:09,760 data analytics because the machine 59 00:02:09,760 --> 00:02:12,220 learning, our ultimate goal is just to 60 00:02:12,220 --> 00:02:15,780 teach the computer how to learn. That's it. 61 00:02:15,780 --> 00:02:19,110 So teaching the computer how to learn 62 00:02:19,110 --> 00:02:20,820 or extract useful information 63 00:02:20,820 --> 00:02:24,470 is not an easy task and actually this 64 00:02:24,470 --> 00:02:28,170 learning is limited by the amount of 65 00:02:28,170 --> 00:02:32,840 the available data and also it's limited 66 00:02:32,840 --> 00:02:34,960 with performance measures. 67 00:02:34,960 --> 00:02:37,150 When we measure, we need to select 68 00:02:37,150 --> 00:02:39,800 the best model which represents it. 69 00:02:39,800 --> 00:02:43,400 And my ultimate goal, I would like to 70 00:02:43,400 --> 00:02:45,680 alleve this limitation by something, 71 00:02:45,680 --> 00:02:47,750 I would like just to make it simple, 72 00:02:47,750 --> 00:02:51,750 we call it develop or derive analytic model. 73 00:02:51,750 --> 00:02:54,050 But simply that means we are trying 74 00:02:54,050 --> 00:02:56,500 to present the problem mathematically 75 00:02:56,500 --> 00:03:00,420 and find the solution in a mathematical context. 76 00:03:00,420 --> 00:03:04,420 Then this model will provide us with some 77 00:03:04,420 --> 00:03:08,070 instructions or guidelines to improve 78 00:03:08,070 --> 00:03:10,900 the robustness and scalability 79 00:03:10,900 --> 00:03:12,700 of our learning algorithms 80 00:03:12,700 --> 00:03:15,220 or provide better guidelines 81 00:03:15,220 --> 00:03:16,860 to develop this learning. 82 00:03:16,860 --> 00:03:19,156 Interviewer: Interesting and in the end you 83 00:03:19,156 --> 00:03:21,610 will make the world a more healthy place. 84 00:03:21,610 --> 00:03:22,430 Right? 85 00:03:22,430 --> 00:03:23,570 El Sayed: I hope. 86 00:03:23,570 --> 00:03:25,070 Interviewer: You hope. Okay good. 87 00:03:25,070 --> 00:03:26,390 That's what you're hoping for. 88 00:03:26,390 --> 00:03:28,920 This conference is about future technologies. 89 00:03:28,920 --> 00:03:30,880 Where do you think that technology 90 00:03:30,880 --> 00:03:32,830 will take us in the future? 91 00:03:33,360 --> 00:03:37,570 El Sayed: Based on my area, I believe 92 00:03:37,570 --> 00:03:42,720 that we are going to ultra thin smart 93 00:03:42,720 --> 00:03:45,140 phones which will be connected 94 00:03:45,140 --> 00:03:49,630 to unlimited cloud computing services, 95 00:03:49,630 --> 00:03:52,250 and within ten years I don't know if cloud 96 00:03:52,250 --> 00:03:54,310 computing will continue with the 97 00:03:54,310 --> 00:03:56,050 same name cloud computing. 98 00:03:56,050 --> 00:03:58,050 It will be something fundamental. 99 00:03:58,050 --> 00:04:00,170 Looks like right now when you use 100 00:04:00,170 --> 00:04:02,790 the computer you say I'm using the computer 101 00:04:02,790 --> 00:04:04,580 but you don't say I'm using the CPU 102 00:04:04,580 --> 00:04:06,840 because the CPU is something default, 103 00:04:06,840 --> 00:04:07,960 you don't say it. 104 00:04:07,960 --> 00:04:10,220 So it looks like cloud computing will be 105 00:04:10,220 --> 00:04:12,470 something fundamental in the future 106 00:04:12,470 --> 00:04:14,720 and I can see everything will be smart, 107 00:04:14,720 --> 00:04:21,710 flexible, optimal, robust, scalable, 108 00:04:21,815 --> 00:04:25,025 and big data has a big role in the future. 109 00:04:25,025 --> 00:04:28,705 Interviewer: Looking at this conference, 110 00:04:28,705 --> 00:04:30,095 how do you like it? 111 00:04:30,095 --> 00:04:32,235 El Sayed: I love it. Actually everything 112 00:04:32,235 --> 00:04:35,175 especially the key note speakers, 113 00:04:35,175 --> 00:04:37,088 and all the presented papers, 114 00:04:37,088 --> 00:04:40,728 they are relevant to what we are trying 115 00:04:40,728 --> 00:04:43,708 to do for the future, improve the world. 116 00:04:43,708 --> 00:04:45,348 Interviewer: Perfect. Well thank you, 117 00:04:45,348 --> 00:04:47,348 enjoy the rest of the conference. 118 00:04:47,348 --> 00:04:48,748 El Sayed: Yeah, thank you very much. 119 00:04:48,748 --> 00:04:50,138 Appreciate the effort here in the conference. 120 00:04:50,138 --> 00:04:52,298 Interviewer: Okay thank you, and if you 121 00:04:52,298 --> 00:04:54,048 would like to see more interviews like 122 00:04:54,048 --> 00:04:56,158 this, know about the research going on 123 00:04:56,158 --> 00:04:58,338 in the world, please check the website 124 00:04:58,338 --> 00:05:00,238 and you will find lots more videos. 125 00:05:00,368 --> 00:05:01,258 Thank you. 126 00:05:01,258 --> 00:05:18,908 [Music]