WEBVTT 1 00:00:00.120 --> 00:00:02.580 In this lesson, we will learn about 2 00:00:02.580 --> 00:00:06.510 generative artificial intelligence or AI. 3 00:00:06.510 --> 00:00:11.010 Generative AI refers to artificial intelligence systems 4 00:00:11.010 --> 00:00:15.000 that create new content, such as text, images, 5 00:00:15.000 --> 00:00:16.770 code, or music. 6 00:00:16.770 --> 00:00:20.640 Generative AI learns patterns from existing data 7 00:00:20.640 --> 00:00:22.830 and generates outputs that resemble 8 00:00:22.830 --> 00:00:25.380 or extend the original data. 9 00:00:25.380 --> 00:00:28.950 Models like the generative pre-trained transformer 10 00:00:28.950 --> 00:00:32.670 or GPT are trained on large data sets 11 00:00:32.670 --> 00:00:36.480 to understand language, context, and structure. 12 00:00:36.480 --> 00:00:39.570 Based on their large amount of training data, 13 00:00:39.570 --> 00:00:44.570 GPTs can produce coherent and contextually relevant content. 14 00:00:45.090 --> 00:00:49.260 Baseline generative AI concepts include code assist 15 00:00:49.260 --> 00:00:51.000 and documentation. 16 00:00:51.000 --> 00:00:53.250 Code assist helps developers 17 00:00:53.250 --> 00:00:55.800 by suggesting or completing code, 18 00:00:55.800 --> 00:00:59.700 while documentation functions automatically generate 19 00:00:59.700 --> 00:01:03.990 technical documents such as user guides, release notes, 20 00:01:03.990 --> 00:01:06.810 and other technical documentation. 21 00:01:06.810 --> 00:01:11.010 Let's learn more about generative AI content creation, 22 00:01:11.010 --> 00:01:15.090 code assist, and AI generated documentation. 23 00:01:15.090 --> 00:01:18.840 First, we have generative artificial intelligence 24 00:01:18.840 --> 00:01:21.690 or AI content creation. 25 00:01:21.690 --> 00:01:23.790 Generative artificial intelligence 26 00:01:23.790 --> 00:01:26.910 refers to artificial intelligence systems 27 00:01:26.910 --> 00:01:31.320 designed to create new content across various formats 28 00:01:31.320 --> 00:01:35.670 such as text, images, code, or music. 29 00:01:35.670 --> 00:01:38.850 By studying and learning patterns from a broad range 30 00:01:38.850 --> 00:01:43.200 of existing data, generative AI can produce outputs 31 00:01:43.200 --> 00:01:46.920 that mimic or expand on the original data. 32 00:01:46.920 --> 00:01:48.570 A prominent example 33 00:01:48.570 --> 00:01:51.720 is the generative pre-trained transformer model 34 00:01:51.720 --> 00:01:54.510 often abbreviated as GPT. 35 00:01:54.510 --> 00:01:57.990 GPT models trained on extensive data sets 36 00:01:57.990 --> 00:01:59.610 have a deep knowledge base 37 00:01:59.610 --> 00:02:02.700 of language, context, and structure, 38 00:02:02.700 --> 00:02:05.010 allowing them to generate coherent 39 00:02:05.010 --> 00:02:08.100 and contextually relevant responses. 40 00:02:08.100 --> 00:02:11.670 So when a GPT encounters a word, 41 00:02:11.670 --> 00:02:14.550 it interprets the word based on its context 42 00:02:14.550 --> 00:02:17.220 within the sequence of other words. 43 00:02:17.220 --> 00:02:20.130 To do this, GPT models are trained 44 00:02:20.130 --> 00:02:22.680 on massive data sets of texts, 45 00:02:22.680 --> 00:02:25.860 allowing them to learn patterns of word use, 46 00:02:25.860 --> 00:02:28.560 relationships, and meanings. 47 00:02:28.560 --> 00:02:33.060 Also, instead of treating each word as an isolated unit, 48 00:02:33.060 --> 00:02:36.870 GPT breaks down language into tokens, 49 00:02:36.870 --> 00:02:40.020 which represent full words, parts of words, 50 00:02:40.020 --> 00:02:43.710 or even just characters depending on the complexity 51 00:02:43.710 --> 00:02:45.180 of the language. 52 00:02:45.180 --> 00:02:47.640 These tokens are then transformed 53 00:02:47.640 --> 00:02:50.220 into numerical representations, 54 00:02:50.220 --> 00:02:54.540 which the model processes to understand word relationships 55 00:02:54.540 --> 00:02:56.100 and context. 56 00:02:56.100 --> 00:02:58.410 The model's understanding of a word 57 00:02:58.410 --> 00:03:01.800 then involves layers of attention mechanisms 58 00:03:01.800 --> 00:03:05.280 where attention mechanisms help GPTs 59 00:03:05.280 --> 00:03:09.270 focus on specific parts of a sentence or passage, 60 00:03:09.270 --> 00:03:11.850 giving more weight to certain words 61 00:03:11.850 --> 00:03:14.400 that provide context to others. 62 00:03:14.400 --> 00:03:19.400 For example, in the sentence I went to the bank to fish, 63 00:03:19.590 --> 00:03:24.060 attention layers would weigh fish heavily to interpret bank 64 00:03:24.060 --> 00:03:26.640 as referring to the edge of a river 65 00:03:26.640 --> 00:03:29.700 rather than a financial institution. 66 00:03:29.700 --> 00:03:33.630 By using these layers and associated word tokens, 67 00:03:33.630 --> 00:03:38.630 GPTs dynamically adjust their interpretation of each word 68 00:03:39.120 --> 00:03:42.000 according to the other words around it, 69 00:03:42.000 --> 00:03:46.080 aiming to capture the most relevant meaning in context, 70 00:03:46.080 --> 00:03:48.600 and finally, to generate a coherent 71 00:03:48.600 --> 00:03:51.660 and contextually accurate response. 72 00:03:51.660 --> 00:03:54.241 Generative AI is especially useful 73 00:03:54.241 --> 00:03:58.590 for content creation tasks that require consistency, 74 00:03:58.590 --> 00:04:02.190 style, or adhere to specific themes. 75 00:04:02.190 --> 00:04:05.670 This is because it can adapt to different requirements 76 00:04:05.670 --> 00:04:09.900 generating unique content within set parameters. 77 00:04:09.900 --> 00:04:12.660 This enables businesses, educators, 78 00:04:12.660 --> 00:04:16.260 and content creators to speed up the creation 79 00:04:16.260 --> 00:04:18.270 of engaging materials, 80 00:04:18.270 --> 00:04:22.740 making generative AI a valuable tool for automating 81 00:04:22.740 --> 00:04:25.470 and enhancing the creative process. 82 00:04:25.470 --> 00:04:28.440 Second, we have code assist. 83 00:04:28.440 --> 00:04:33.030 Code assist is a powerful application of generative AI, 84 00:04:33.030 --> 00:04:35.910 focused on enhancing software development 85 00:04:35.910 --> 00:04:39.360 by assisting programmers with writing code. 86 00:04:39.360 --> 00:04:43.020 Code assist tools analyze existing code 87 00:04:43.020 --> 00:04:44.730 and programming patterns, 88 00:04:44.730 --> 00:04:47.610 allowing them to suggest improvements 89 00:04:47.610 --> 00:04:51.810 for auto-complete code as the developer types. 90 00:04:51.810 --> 00:04:54.780 So through real-time recommendations, 91 00:04:54.780 --> 00:04:58.890 generative AI can help developers write code faster 92 00:04:58.890 --> 00:05:02.880 and with more accuracy, improving productivity, 93 00:05:02.880 --> 00:05:07.440 and enabling them to focus on more creative problem solving 94 00:05:07.440 --> 00:05:11.190 rather than repetitive or tedious coding tasks. 95 00:05:11.190 --> 00:05:14.190 Developers can also benefit significantly 96 00:05:14.190 --> 00:05:19.190 from code assist tools like GitHub, copilot, and tab nine, 97 00:05:19.560 --> 00:05:22.920 which reduce the time spent on manual coding 98 00:05:22.920 --> 00:05:24.630 and error correction. 99 00:05:24.630 --> 00:05:29.430 These tools offer solutions ranging from simple syntax fixes 100 00:05:29.430 --> 00:05:33.540 to complex code snippets that align with best practices 101 00:05:33.540 --> 00:05:35.490 in software development. 102 00:05:35.490 --> 00:05:38.610 As the code assist model becomes familiar 103 00:05:38.610 --> 00:05:42.090 with the particular coding language or framework, 104 00:05:42.090 --> 00:05:45.090 it can generate tailored recommendations 105 00:05:45.090 --> 00:05:47.970 that meet the needs of specific projects 106 00:05:47.970 --> 00:05:50.430 or development environments. 107 00:05:50.430 --> 00:05:54.990 Code assist tools also allow less experienced developers 108 00:05:54.990 --> 00:05:58.980 to quickly learn and apply new coding practices 109 00:05:58.980 --> 00:06:03.980 by observing and using the code suggested by AI models. 110 00:06:04.290 --> 00:06:08.130 So AI generated suggestions help developers 111 00:06:08.130 --> 00:06:11.190 maintain consistency across projects 112 00:06:11.190 --> 00:06:14.880 by enforcing coding standards and conventions. 113 00:06:14.880 --> 00:06:17.160 By improving workflow efficiency 114 00:06:17.160 --> 00:06:19.620 and reducing debugging time, 115 00:06:19.620 --> 00:06:22.710 code assist tools streamline development, 116 00:06:22.710 --> 00:06:27.210 leading to a higher quality code in much less time. 117 00:06:27.210 --> 00:06:32.010 Third and last, we have AI generated documentation. 118 00:06:32.010 --> 00:06:36.540 AI generated documentation is a specialized application 119 00:06:36.540 --> 00:06:38.310 of generative AI 120 00:06:38.310 --> 00:06:42.690 that focuses on creating technical documents automatically 121 00:06:42.690 --> 00:06:47.310 based on the existing code base or system configuration. 122 00:06:47.310 --> 00:06:49.920 Documentation generation tools 123 00:06:49.920 --> 00:06:53.490 such as GitBook and Document 360 124 00:06:53.490 --> 00:06:57.750 analyze code structure, functions, and dependencies 125 00:06:57.750 --> 00:07:00.720 to generate user guides, release notes, 126 00:07:00.720 --> 00:07:03.300 and other technical materials. 127 00:07:03.300 --> 00:07:06.660 This allows developers and technical writers 128 00:07:06.660 --> 00:07:11.250 to quickly produce up-to-date consistent documentation. 129 00:07:11.250 --> 00:07:15.600 Creating documentation manually can be time consuming, 130 00:07:15.600 --> 00:07:20.130 requiring close attention to detail and frequent updates. 131 00:07:20.130 --> 00:07:24.630 AI generated documentation alleviates this burden 132 00:07:24.630 --> 00:07:27.210 by automatically creating detailed, 133 00:07:27.210 --> 00:07:29.730 accurate technical documentation 134 00:07:29.730 --> 00:07:32.670 aligned with the latest code changes. 135 00:07:32.670 --> 00:07:36.510 By using natural language generation capabilities, 136 00:07:36.510 --> 00:07:39.457 documentation tools can produce explanations 137 00:07:39.457 --> 00:07:43.320 of code, functionality, and configurations 138 00:07:43.320 --> 00:07:46.080 in an easy to understand format 139 00:07:46.080 --> 00:07:50.490 suitable for both technical and non-technical audiences. 140 00:07:50.490 --> 00:07:54.750 This allows developers to focus on their primary tasks 141 00:07:54.750 --> 00:07:58.230 without sacrificing the quality of documentation 142 00:07:58.230 --> 00:08:00.960 resulting in a well-rounded product 143 00:08:00.960 --> 00:08:05.610 that is easier to understand, implement, and maintain. 144 00:08:05.610 --> 00:08:09.210 So while ensuring that all project documentation 145 00:08:09.210 --> 00:08:11.550 remains consistent and complete, 146 00:08:11.550 --> 00:08:16.290 the documentation can also adapt to changes in the code base 147 00:08:16.290 --> 00:08:20.070 automatically updating release notes or user guides 148 00:08:20.070 --> 00:08:23.130 when new features or functions are added. 149 00:08:23.130 --> 00:08:27.030 For organizations with fast-paced development cycles, 150 00:08:27.030 --> 00:08:29.970 AI driven documentation generation 151 00:08:29.970 --> 00:08:34.050 offers an efficient way to keep documentation current, 152 00:08:34.050 --> 00:08:37.500 making it easier for users and support teams 153 00:08:37.500 --> 00:08:41.310 to access accurate up-to-date information. 154 00:08:41.310 --> 00:08:46.310 So remember, generative artificial intelligence or AI 155 00:08:46.890 --> 00:08:50.640 is designed to create new content across formats 156 00:08:50.640 --> 00:08:54.450 like text, images, code, and music 157 00:08:54.450 --> 00:08:57.540 by learning from existing data. 158 00:08:57.540 --> 00:09:01.440 This learning allows AI models to produce coherent, 159 00:09:01.440 --> 00:09:03.690 contextually relevant outputs 160 00:09:03.690 --> 00:09:06.720 that can expand on the original data. 161 00:09:06.720 --> 00:09:11.640 In content creation, generative AI is particularly useful 162 00:09:11.640 --> 00:09:14.820 for maintaining consistency and style, 163 00:09:14.820 --> 00:09:17.370 enabling organizations to automate 164 00:09:17.370 --> 00:09:19.920 and scale production efficiently. 165 00:09:19.920 --> 00:09:23.490 Generative AI concepts include code assist 166 00:09:23.490 --> 00:09:25.290 and documentation. 167 00:09:25.290 --> 00:09:27.990 For developers, code assist tools 168 00:09:27.990 --> 00:09:30.870 provide real-time coding suggestions, 169 00:09:30.870 --> 00:09:35.100 improving productivity and accuracy by reducing the need 170 00:09:35.100 --> 00:09:38.280 for manual coding and error correction. 171 00:09:38.280 --> 00:09:42.120 Additionally, AI generated documentation tools 172 00:09:42.120 --> 00:09:45.840 can automatically produce technical documentation, 173 00:09:45.840 --> 00:09:49.140 keeping the content up to date and accurate, 174 00:09:49.140 --> 00:09:52.290 benefiting developers and support teams 175 00:09:52.290 --> 00:09:56.073 by easing the documentation generation workload.