1 00:00:00,01 --> 00:00:01,05 - [Instructor] Have you ever thought about 2 00:00:01,05 --> 00:00:04,07 the internet on our devices? 3 00:00:04,07 --> 00:00:06,05 We are so used to having access 4 00:00:06,05 --> 00:00:10,03 to all information we need at the tip of our fingers. 5 00:00:10,03 --> 00:00:12,01 Have you wondered about the process 6 00:00:12,01 --> 00:00:15,00 of how something like artificial intelligence 7 00:00:15,00 --> 00:00:18,07 makes its way into our devices? 8 00:00:18,07 --> 00:00:22,06 I want you to join me to expand your thinking 9 00:00:22,06 --> 00:00:27,04 of how artificial intelligence powers everything around us. 10 00:00:27,04 --> 00:00:29,01 What about cars? 11 00:00:29,01 --> 00:00:32,00 How are they processing information in real time 12 00:00:32,00 --> 00:00:35,01 without always having access to the cloud? 13 00:00:35,01 --> 00:00:36,04 In this course, 14 00:00:36,04 --> 00:00:40,03 we will learn how that happens using edge AI 15 00:00:40,03 --> 00:00:42,09 and how to build and create value 16 00:00:42,09 --> 00:00:46,04 from the many different AI on the edge of a device, 17 00:00:46,04 --> 00:00:48,09 anywhere from your home to industrial cameras 18 00:00:48,09 --> 00:00:52,04 to connected and autonomous cars. 19 00:00:52,04 --> 00:00:54,08 Edge AI is simply 20 00:00:54,08 --> 00:00:58,08 AI running inference on the edge of any device. 21 00:00:58,08 --> 00:01:01,07 This is about deploying AI to customers 22 00:01:01,07 --> 00:01:05,05 who use internet connected devices, big and small, 23 00:01:05,05 --> 00:01:07,06 and about getting customer data 24 00:01:07,06 --> 00:01:12,00 to improve the AI to work for them from the edge. 25 00:01:12,00 --> 00:01:15,03 It is not about AI being built on a mobile device. 26 00:01:15,03 --> 00:01:20,00 The training of the AI can happen on the cloud or edge. 27 00:01:20,00 --> 00:01:23,02 Autonomous vehicles have innovated farming 28 00:01:23,02 --> 00:01:27,02 from manual toiling into precision farming. 29 00:01:27,02 --> 00:01:30,02 Precision farming made farming digital 30 00:01:30,02 --> 00:01:32,09 by calculating real-time data 31 00:01:32,09 --> 00:01:35,09 from weather, soil, and historic data 32 00:01:35,09 --> 00:01:38,08 to predict the right time to farm 33 00:01:38,08 --> 00:01:42,04 with the right seeds, water, and fertilizers, 34 00:01:42,04 --> 00:01:45,09 and the farmer gets to ride an autonomous tractor 35 00:01:45,09 --> 00:01:49,08 that does tilling, sowing, de-weeding, and harvesting. 36 00:01:49,08 --> 00:01:52,06 This is artificial intelligence at work 37 00:01:52,06 --> 00:01:54,03 on the edge of devices, 38 00:01:54,03 --> 00:01:57,05 such as autonomous vehicles. 39 00:01:57,05 --> 00:02:01,07 Running inference on devices can come in many forms. 40 00:02:01,07 --> 00:02:05,09 My favorite example is an autonomous warehouse robot, 41 00:02:05,09 --> 00:02:08,01 or AMR, as they're known, 42 00:02:08,01 --> 00:02:12,08 in a warehouse that loads items to be shipped faster 43 00:02:12,08 --> 00:02:14,06 without any error, 44 00:02:14,06 --> 00:02:18,00 that augments humans in warehouses. 45 00:02:18,00 --> 00:02:22,06 When these robotic arms are making decisions autonomously, 46 00:02:22,06 --> 00:02:24,09 that is edge AI, 47 00:02:24,09 --> 00:02:27,03 using real-time data processing 48 00:02:27,03 --> 00:02:32,05 to use sensors on the arm to complete its task. 49 00:02:32,05 --> 00:02:35,01 So, you're not stuck monitoring every move. 50 00:02:35,01 --> 00:02:37,09 Instead, you can trust the data that is uploaded 51 00:02:37,09 --> 00:02:40,04 to this device to work for you 52 00:02:40,04 --> 00:02:43,08 using the intelligence of AI to make decisions 53 00:02:43,08 --> 00:02:48,08 to help with manufacturing, production, or mobility. 54 00:02:48,08 --> 00:02:52,01 Edge AI can be found in mining, 55 00:02:52,01 --> 00:02:55,00 collecting, and dumping minerals 56 00:02:55,00 --> 00:02:57,04 that humans should not handle. 57 00:02:57,04 --> 00:02:59,07 These are done by autonomous mobility vehicles, 58 00:02:59,07 --> 00:03:01,06 also known as AMV. 59 00:03:01,06 --> 00:03:04,02 We will talk more about AMVs 60 00:03:04,02 --> 00:03:09,02 as we learn about deploying edge AI in future lessons. 61 00:03:09,02 --> 00:03:12,00 All this is powered by AI, 62 00:03:12,00 --> 00:03:15,01 AI that tracks sounds and listens to voices, 63 00:03:15,01 --> 00:03:17,09 AI that does computer vision for cameras, 64 00:03:17,09 --> 00:03:21,01 AI that combines sensors and haptics data 65 00:03:21,01 --> 00:03:22,06 to work well with humans 66 00:03:22,06 --> 00:03:26,03 in the workflow of factories, mines, farms, and roads. 67 00:03:26,03 --> 00:03:29,01 Traditional AI, such as machine learning and deep learning, 68 00:03:29,01 --> 00:03:31,05 is combined with generative AI 69 00:03:31,05 --> 00:03:34,05 to understand and engage with humans. 70 00:03:34,05 --> 00:03:37,08 Any of this AI is running in production as edge AI, 71 00:03:37,08 --> 00:03:41,09 making sense of the environment and going past navigation 72 00:03:41,09 --> 00:03:45,07 to support the very purpose of the devices. 73 00:03:45,07 --> 00:03:48,01 AI is where we can innovate 74 00:03:48,01 --> 00:03:50,09 by designing the human-centric AI 75 00:03:50,09 --> 00:03:52,08 to fit into our workflow, 76 00:03:52,08 --> 00:03:55,07 earn trust, and help us innovate. 77 00:03:55,07 --> 00:03:58,03 All AI have common characteristics. 78 00:03:58,03 --> 00:03:59,09 AI is trained by data, 79 00:03:59,09 --> 00:04:01,04 AI makes predictions, 80 00:04:01,04 --> 00:04:02,09 AI keeps learning, 81 00:04:02,09 --> 00:04:07,01 and all AI works with humans. 82 00:04:07,01 --> 00:04:11,03 There are many ways Edge AI finds its way to us. 83 00:04:11,03 --> 00:04:13,08 We can find all of them in autonomous vehicles 84 00:04:13,08 --> 00:04:16,01 or in autonomous mobility vehicles, 85 00:04:16,01 --> 00:04:18,02 which we will use as example 86 00:04:18,02 --> 00:04:20,07 to learn edge AI in this course. 87 00:04:20,07 --> 00:04:23,08 In order for you to get the full experience of edge AI, 88 00:04:23,08 --> 00:04:26,01 this is going to be a hands-on course. 89 00:04:26,01 --> 00:04:27,09 We'll provide demos and challenges 90 00:04:27,09 --> 00:04:29,06 for you to learn hands-on, 91 00:04:29,06 --> 00:04:32,02 and you will find detailed instructions 92 00:04:32,02 --> 00:04:35,06 in text files and handouts for reference. 93 00:04:35,06 --> 00:04:37,06 I'm also going to teach you a framework 94 00:04:37,06 --> 00:04:40,05 to understand the three components of edge AI 95 00:04:40,05 --> 00:04:43,02 and the tech stack of autonomous vehicles. 96 00:04:43,02 --> 00:04:47,09 You can apply the same to your favorite edge AI device. 97 00:04:47,09 --> 00:04:50,00 Join me on this fun drive.