1 00:00:00,000 --> 00:00:04,860 Alright, let's jump right in. Have you ever stopped to think about how the world you actually experience, 2 00:00:05,040 --> 00:00:10,640 you know, with all its smooth sounds and continuous colors, somehow gets crammed inside your phone? 3 00:00:11,039 --> 00:00:15,199 It's because our world and our gadgets speak two totally different languages. 4 00:00:15,820 --> 00:00:18,879 Today, we're going to crack the code and learn how to speak both. 5 00:00:19,379 --> 00:00:23,660 So, let's start with a really simple question. How do computers even talk? 6 00:00:23,940 --> 00:00:27,420 I mean, they don't understand sunlight or sound waves the way our brains do. 7 00:00:27,420 --> 00:00:32,880 they need a translator, a way to turn our world into a language they can actually understand. 8 00:00:33,539 --> 00:00:38,359 And that brings us to these two completely different worlds. On one side, you have analog. 9 00:00:38,960 --> 00:00:43,780 Think of this as the language of nature. It's smooth, it's continuous, and it has an infinite 10 00:00:43,780 --> 00:00:48,020 number of shades and tones. But on the other side, you've got digital. That's the language 11 00:00:48,020 --> 00:00:53,780 of computers. It's chunky, it moves in distinct steps, and it only uses a limited set of values. 12 00:00:54,460 --> 00:00:56,439 Okay, let's really dig into this. 13 00:00:56,840 --> 00:01:02,039 How does this huge difference between a smooth, flowing reality and this kind of step-by-step data 14 00:01:02,039 --> 00:01:07,120 actually work in the world around us and, you know, inside all the electronics we use every single day? 15 00:01:07,859 --> 00:01:10,260 First up, let's talk about the analog signal. 16 00:01:10,659 --> 00:01:12,739 The best way to think about it is like a ramp. 17 00:01:13,079 --> 00:01:15,640 It's a perfect, smooth reflection of reality. 18 00:01:15,739 --> 00:01:17,819 Its value changes continuously. 19 00:01:18,239 --> 00:01:19,819 There are no breaks, no jumps. 20 00:01:20,400 --> 00:01:24,219 Between any two points on that ramp, there's an infinite number of other points. 21 00:01:24,599 --> 00:01:27,060 It's just a completely smooth, unbroken line. 22 00:01:27,540 --> 00:01:31,299 And you are literally swimming in analog signals all day long. 23 00:01:31,540 --> 00:01:35,519 I mean, the temperature doesn't just leap from 70 degrees to 71 degrees, right? 24 00:01:35,519 --> 00:01:39,019 It flows through every single possible value in between. 25 00:01:39,519 --> 00:01:44,359 And it's the same for the brightness of a light, the sound waves coming from a guitar, or the pressure of the wind. 26 00:01:44,620 --> 00:01:47,200 It is all smooth, continuous change. 27 00:01:47,200 --> 00:01:51,659 Now, let's flip the coin and look at the digital signal. 28 00:01:51,659 --> 00:01:56,180 So if analog is a smooth ramp, think of digital as a staircase. 29 00:01:56,180 --> 00:01:57,959 It's not a continuous flow at all. 30 00:01:57,959 --> 00:02:01,519 It's just a series of very specific, separate steps. 31 00:02:01,519 --> 00:02:03,920 It can only be one value or another. 32 00:02:03,920 --> 00:02:06,700 You're either on this step or you're on that step. 33 00:02:06,700 --> 00:02:08,879 There's absolutely nothing in between. 34 00:02:08,879 --> 00:02:10,360 And this right here? 35 00:02:10,360 --> 00:02:12,120 This is the heart of it all. 36 00:02:12,120 --> 00:02:16,000 The simplest, most basic digital signal is called binary. 37 00:02:16,000 --> 00:02:20,120 It's the native language of all electronics, and it has only two states. 38 00:02:20,120 --> 00:02:21,120 That's it. 39 00:02:21,120 --> 00:02:25,319 A high voltage, which we call a one, and a low voltage, which we call a zero. 40 00:02:25,319 --> 00:02:27,680 It's just on or off. 41 00:02:27,680 --> 00:02:29,719 That is the entire alphabet. 42 00:02:29,719 --> 00:02:31,180 So hold on. 43 00:02:31,180 --> 00:02:36,439 If computers can only understand on and off, just ones and zeros, how on earth do they 44 00:02:36,439 --> 00:02:41,159 manage to represent a super complex photo or a beautiful piece of music? 45 00:02:41,159 --> 00:02:42,159 Let's get into it. 46 00:02:42,159 --> 00:02:46,460 Well, to understand how computers count, it really helps to first look at how we count. 47 00:02:46,900 --> 00:02:51,520 We use the decimal system, right? Or base 10. It's probably because we have 10 fingers. 48 00:02:51,860 --> 00:02:56,780 It gives us 10 symbols to work with, 0 through 9, to build any number we can possibly imagine. 49 00:02:57,300 --> 00:03:02,919 And in our system, where you put the number is everything. Take 358. It's not just a 3, 50 00:03:03,039 --> 00:03:08,840 a 5, and an 8 next to each other. We all know it's 300s plus 5 10s plus 8 1s. 51 00:03:08,840 --> 00:03:13,159 Each position is a power of 10. We've been thinking this way our whole lives. 52 00:03:13,800 --> 00:03:20,180 Okay, so computers take that exact same idea and they just simplify it, radically. They use binary 53 00:03:20,180 --> 00:03:27,939 or base 2. So instead of 10 symbols, they only have 2, 0, and 1. We call each one a bit. And this 54 00:03:27,939 --> 00:03:32,879 isn't just a random choice. It's brilliant, because it perfectly matches the physical reality of an 55 00:03:32,879 --> 00:03:38,319 electrical circuit. Is there a low voltage? That's a 0. Is there a high voltage? That's a 1. Simple. 56 00:03:38,319 --> 00:03:42,599 And, check this out, this chart is basically the translation guide. 57 00:03:42,599 --> 00:03:45,840 On the left, you've got the decimal numbers we use every day. 58 00:03:45,840 --> 00:03:48,580 And on the right, that's how a computer writes them. 59 00:03:48,580 --> 00:03:51,659 So our number 2 becomes 0010. 60 00:03:51,659 --> 00:03:54,219 Our number 7 becomes 0111. 61 00:03:54,219 --> 00:03:57,879 It's a totally different alphabet used to write the exact same things. 62 00:03:57,879 --> 00:04:03,460 So we have the analog world we live in, and we have the digital alphabet, computers speak. 63 00:04:03,460 --> 00:04:07,340 So the next logical question is, how do we translate between the two? 64 00:04:07,340 --> 00:04:08,560 This right here? 65 00:04:08,560 --> 00:04:11,360 This is the aha moment where it all clicks. 66 00:04:11,360 --> 00:04:12,580 And this magic trick? 67 00:04:12,580 --> 00:04:14,500 It's called digitization. 68 00:04:14,500 --> 00:04:18,939 This is the process, the bridge that connects the physical world to the world that exists 69 00:04:18,939 --> 00:04:20,519 inside our computers. 70 00:04:20,519 --> 00:04:25,800 It's how we translate that smooth, analog signal into a bunch of discrete digital numbers. 71 00:04:25,800 --> 00:04:28,240 So how does this translation actually happen? 72 00:04:28,240 --> 00:04:29,399 Let's just walk through it. 73 00:04:29,399 --> 00:04:33,139 First, you start with that smooth, analog signal, like a sound wave. 74 00:04:33,139 --> 00:04:36,060 Second, at super regular fixed moments in time, 75 00:04:36,060 --> 00:04:37,579 you measure its value. 76 00:04:37,579 --> 00:04:38,759 This is called sampling. 77 00:04:38,759 --> 00:04:41,139 It's like taking thousands of little snapshots. 78 00:04:41,139 --> 00:04:43,500 Third, each one of those snapshots gets converted 79 00:04:43,500 --> 00:04:45,360 into its closest binary number. 80 00:04:45,360 --> 00:04:46,819 And what you're left with at the end 81 00:04:46,819 --> 00:04:49,459 is a clean, simple sequence of zeros and ones 82 00:04:49,459 --> 00:04:51,379 that represents that original sound. 83 00:04:51,379 --> 00:04:53,899 And here is the absolute key takeaway. 84 00:04:53,899 --> 00:04:55,819 Just look at how that stepped blue line 85 00:04:55,819 --> 00:04:58,199 tries to follow the smooth gray curve. 86 00:04:58,199 --> 00:05:00,319 The digital signal is never a perfect, 87 00:05:00,319 --> 00:05:02,459 identical copy of the analog wave. 88 00:05:02,459 --> 00:05:08,459 it can't be. Instead, it's a very, very close approximation, one that's built from thousands 89 00:05:08,459 --> 00:05:14,939 or even millions of those tiny, discrete snapshots. But you might be asking, why go through all this 90 00:05:14,939 --> 00:05:20,300 trouble just to create an approximation? Why not stick with the original? Well, what makes this 91 00:05:20,300 --> 00:05:26,920 whole process so incredibly powerful is the big payoff. And here it is. This is the whole reason 92 00:05:26,920 --> 00:05:32,220 we do it. Once information is converted into a clear sequence of ones and zeros, it becomes 93 00:05:32,220 --> 00:05:37,459 incredibly tough, incredibly robust. You can store it, you can copy it a million times perfectly, 94 00:05:37,720 --> 00:05:42,180 and you can send it across the world without it getting easily messed up by noise or static. 95 00:05:42,819 --> 00:05:48,019 And you have absolutely seen this for yourself. Remember the snow and static you'd get on an old 96 00:05:48,019 --> 00:05:53,439 analog TV during a thunderstorm? Now think about a digital broadcast today. It's either perfectly 97 00:05:53,439 --> 00:05:59,000 clear or it's just not there. It doesn't get fuzzy or degrade. And that's because the receiver 98 00:05:59,000 --> 00:06:05,420 only has one job. Figure out if the signal is a one or a zero. It can completely ignore all that 99 00:06:05,420 --> 00:06:10,000 messy static in between. And that leads us to a final, really fascinating question to think about. 100 00:06:10,420 --> 00:06:15,259 We've seen that this digital world with all its perfect clarity is built on an approximation of 101 00:06:15,259 --> 00:06:21,079 our real analog world. It's a world made of snapshots, not a continuous flow. So the question 102 00:06:21,079 --> 00:06:22,240 to leave you with is this. 103 00:06:22,660 --> 00:06:23,420 In that translation, 104 00:06:23,699 --> 00:06:25,240 from the infinite to the finite, 105 00:06:25,779 --> 00:06:26,699 what, if anything, 106 00:06:26,980 --> 00:06:27,920 actually gets lost?