1 00:00:04,950 --> 00:00:11,670 In this lesson, we will talk about the evolution of artificial intelligence as a science. 2 00:00:12,840 --> 00:00:17,880 We will talk about the universalization of the artificial intelligence. 3 00:00:18,060 --> 00:00:24,930 And finally we will see why LM applications are at the core of. 4 00:00:25,760 --> 00:00:26,720 Revolution. 5 00:00:31,520 --> 00:00:38,240 You are probably familiar with pollution of artificial intelligence as a science. 6 00:00:38,570 --> 00:00:45,320 It all started years ago, like 50 years ago, with the invention of machine learning. 7 00:00:45,320 --> 00:00:50,180 Machine learning was a different way of working with computers. 8 00:00:50,210 --> 00:00:59,210 Until that time we used to ask computers for like a cooking recipe. 9 00:00:59,210 --> 00:01:05,180 We are going to tell them to follow steps one by one. 10 00:01:05,180 --> 00:01:05,870 Step one. 11 00:01:05,870 --> 00:01:11,450 Step two, step three, step four, in order to reach one last result. 12 00:01:11,870 --> 00:01:19,190 With machine learning, we changed that process and we show the computer that result we are looking 13 00:01:19,190 --> 00:01:27,200 for, and just let the computer find out a way to create that for us. 14 00:01:27,770 --> 00:01:33,500 It's a totally different way of communicating ourselves with her. 15 00:01:33,530 --> 00:01:39,800 This is what we call machine learning because the machine, the computer has to learn how to find out 16 00:01:40,070 --> 00:01:42,230 result, the process to get the result. 17 00:01:43,340 --> 00:01:54,530 With the, uh, internet boom, suddenly engineers had millions and millions of data they can guide 18 00:01:54,530 --> 00:02:04,880 to their computers and that the of internet and the big data era with the invention of neural networks 19 00:02:04,880 --> 00:02:13,520 and also of GPUs, which is a kind of hardware that which is using in the machine learning systems. 20 00:02:14,210 --> 00:02:22,790 We had a very, very big machine learning, uh, solutions and the name of machine learning because 21 00:02:22,790 --> 00:02:30,080 it was like a huge, uh, technology then changing into deep learning. 22 00:02:30,080 --> 00:02:37,490 So deep learning is just machine learning with much more data, and also with the inclusion of neural 23 00:02:37,490 --> 00:02:39,500 networks and GPUs. 24 00:02:39,920 --> 00:02:49,430 Just a few years ago, just a few years ago, with the invention of transformers, we saw the birth 25 00:02:49,430 --> 00:02:53,780 of ChatGPT and generative AI. 26 00:02:54,200 --> 00:02:59,750 So ChatGPT is just an example of generative AI. 27 00:02:59,750 --> 00:03:07,280 And in this bootcamp we call generative AI the new artificial Intelligence. 28 00:03:09,470 --> 00:03:10,490 So. 29 00:03:12,360 --> 00:03:15,150 Let's see why we say that. 30 00:03:15,150 --> 00:03:23,280 We are now in the beginning of the universalization of artificial intelligence. 31 00:03:24,850 --> 00:03:26,980 Before the launch of ChatGPT. 32 00:03:27,820 --> 00:03:29,410 Artificial intelligence. 33 00:03:29,500 --> 00:03:39,340 Artificial intelligence applications were focused mostly on solutions based mainly on data, some on 34 00:03:39,340 --> 00:03:49,420 images, and we had solutions like recommendation systems, predictive analysis systems, image classification 35 00:03:49,420 --> 00:03:53,770 systems, etc. so very narrow kind of solutions. 36 00:03:53,770 --> 00:03:59,470 But with the launch of ChatGPT on November. 37 00:04:00,500 --> 00:04:02,240 2022. 38 00:04:03,510 --> 00:04:12,900 We saw the potential of the new language based artificial intelligence applications, what we call LLM 39 00:04:12,900 --> 00:04:14,010 applications. 40 00:04:14,040 --> 00:04:18,690 LLM stands for Large language Models applications. 41 00:04:18,690 --> 00:04:21,600 We will see more about the LMS later. 42 00:04:22,300 --> 00:04:34,210 So suddenly we saw that these LM applications can be used for practically all kinds of activities. 43 00:04:35,790 --> 00:04:44,370 So it wasn't just for a narrow number of tasks that we were using artificial intelligence before that 44 00:04:44,370 --> 00:04:45,090 moment. 45 00:04:45,390 --> 00:04:53,070 Now suddenly we realized that we can use this new artificial intelligence, what we call generative 46 00:04:53,070 --> 00:04:55,980 AI and the LLM applications. 47 00:04:55,980 --> 00:04:59,670 We can use these new solutions everywhere. 48 00:04:59,670 --> 00:05:03,720 And you will see when we say everywhere is everywhere. 49 00:05:04,200 --> 00:05:14,310 So this started what we call the era of the universalization of artificial intelligence. 50 00:05:14,310 --> 00:05:19,440 So artificial intelligence is going to be everywhere. 51 00:05:20,760 --> 00:05:25,530 And and this is the most important take for this lesson. 52 00:05:26,390 --> 00:05:32,360 L.l.m. applications are at the heart of this revolution. 53 00:05:33,340 --> 00:05:36,400 And now is the main idea of this lesson. 54 00:05:37,340 --> 00:05:42,800 Just as all human activities originate from thought. 55 00:05:44,060 --> 00:05:54,140 LM applications have the potential to become the origin of all artificial intelligence activities. 56 00:05:55,200 --> 00:06:01,350 I repeat, just as all human activities originate from thought. 57 00:06:02,440 --> 00:06:11,380 LM applications have the potential to become the origin of all artificial intelligence activities. 58 00:06:13,150 --> 00:06:20,140 And I'm talking about all of them, whether they are based exclusively on language solutions or if they 59 00:06:20,140 --> 00:06:28,150 are multimodal AI, they are combining language plus images, videos, etc. and even hybrid solutions 60 00:06:28,360 --> 00:06:33,640 like artificial intelligence plus traditional software applications, for example. 61 00:06:34,390 --> 00:06:46,510 For this reason, we can say that learning to develop LM applications will put you in the most valuable 62 00:06:46,510 --> 00:06:50,740 position in the artificial intelligence market. 63 00:06:51,190 --> 00:07:01,780 So it is not casual that we are focusing this bootcamp on LM applications, because LM applications 64 00:07:01,780 --> 00:07:07,060 are at the core of the new artificial intelligence revolution. 65 00:07:09,150 --> 00:07:16,380 So in this lesson, we have been talking a little bit about the evolution of artificial intelligence 66 00:07:16,380 --> 00:07:17,460 as a science. 67 00:07:18,750 --> 00:07:26,250 We have been talking about the new era we are beginning right now, the era of the universalisation 68 00:07:26,250 --> 00:07:35,160 of artificial intelligence, and we have seen the most important idea of the lesson that l.l.m. applications 69 00:07:35,160 --> 00:07:39,030 are at the core of this revolution. 70 00:07:40,790 --> 00:07:46,070 In the next lesson, we are going to talk a little bit about ChatGPT. 71 00:07:46,910 --> 00:07:49,520 Is ChatGPT an LLM application? 72 00:07:50,420 --> 00:07:55,340 What are the differences between ChatGPT and LLM applications? 73 00:07:56,480 --> 00:07:58,340 We will see this next.