1 00:00:00,600 --> 00:00:02,240 Speaker 1: Already and this is the daily. 2 00:00:02,560 --> 00:00:04,120 Speaker 2: This is the daily, This is the daily. 3 00:00:04,200 --> 00:00:15,520 Speaker 1: Ohs oh, now it makes sense. Hello and welcome to 4 00:00:15,560 --> 00:00:18,320 Speaker 1: the Daily OS. It's Tuesday, the twenty fifth of June. 5 00:00:18,400 --> 00:00:19,680 Speaker 2: I'm Sam, I'm Lucy. 6 00:00:20,040 --> 00:00:23,720 Speaker 1: Last week, for a brief moment, tech company and Video 7 00:00:23,920 --> 00:00:27,880 Speaker 1: became the most valuable company in the world, overtaking Microsoft. 8 00:00:28,320 --> 00:00:31,400 Speaker 1: While Microsoft has now clawed its way back, just for now, 9 00:00:31,720 --> 00:00:34,360 Speaker 1: it's clear that Nvidia is going to only grow in 10 00:00:34,400 --> 00:00:39,640 Speaker 1: its influence, value and technological capabilities. But what exactly is 11 00:00:39,880 --> 00:00:42,760 Speaker 1: and Video? What do they make? And why is it 12 00:00:42,840 --> 00:00:45,880 Speaker 1: worth so much? In twenty twenty four, We're going to 13 00:00:45,920 --> 00:00:48,280 Speaker 1: break all of this down for you in today's deep dive. 14 00:00:48,320 --> 00:00:50,320 Speaker 1: But first, Lucy, what is making headlines? 15 00:00:53,080 --> 00:00:55,560 Speaker 2: Three teenage boys have been arrested over the brawl that 16 00:00:55,680 --> 00:00:59,280 Speaker 2: shut down an Adelaide shopping center over the weekend. Westfield 17 00:00:59,320 --> 00:01:02,960 Speaker 2: Marion and Adelaide's South was evacuated on Sunday afternoon after 18 00:01:03,000 --> 00:01:05,959 Speaker 2: a fight broke out in the food court. The three boys, 19 00:01:06,040 --> 00:01:08,520 Speaker 2: aged fifteen and sixteen, have been charged with as salt 20 00:01:08,520 --> 00:01:11,840 Speaker 2: and aggravated robbery. Police say investigations are ongoing. 21 00:01:13,640 --> 00:01:17,120 Speaker 1: Australia's Agriculture Minister Murray Watt has said there is quote 22 00:01:17,240 --> 00:01:21,280 Speaker 1: absolutely no risk of egg supply shortages following a second 23 00:01:21,400 --> 00:01:24,040 Speaker 1: detection of bird flu at a farm in New South Wales. 24 00:01:24,440 --> 00:01:26,720 Speaker 1: Both farms where bird flu has been detected in New 25 00:01:26,760 --> 00:01:30,319 Speaker 1: South Wales are within the state government's biosecurity zone, where 26 00:01:30,360 --> 00:01:33,720 Speaker 1: four farms are currently under quarantine. What said the spread 27 00:01:33,760 --> 00:01:37,280 Speaker 1: of the disease in Victoria, where seven farms have confirmed cases, 28 00:01:37,640 --> 00:01:39,480 Speaker 1: is being quote brought under control. 29 00:01:41,240 --> 00:01:44,839 Speaker 2: Over eighty percent of deaths during Hajj, the Muslim pilgrimage 30 00:01:44,840 --> 00:01:47,560 Speaker 2: to the city of Mecca or Macha in Saudi Arabia, 31 00:01:47,840 --> 00:01:50,760 Speaker 2: were people who weren't registered to be there. The Saudi 32 00:01:50,840 --> 00:01:54,080 Speaker 2: Arabian government requires pilgrims to register and pay online for 33 00:01:54,160 --> 00:01:57,760 Speaker 2: Hajj packages ahead of time, which include transport and accommodation. 34 00:01:58,320 --> 00:02:01,120 Speaker 2: The Saudi Health Minister said unread just died pilgrims had 35 00:02:01,240 --> 00:02:05,200 Speaker 2: quote walked long distances under direct sunlight without adequate shelter 36 00:02:05,320 --> 00:02:10,320 Speaker 2: or comfort, including several elderly and chronically ill individuals. Temperatures 37 00:02:10,320 --> 00:02:12,799 Speaker 2: in the area have hovered around forty five to fifty 38 00:02:12,800 --> 00:02:15,240 Speaker 2: degrees celsius. 39 00:02:15,760 --> 00:02:19,160 Speaker 1: And today's good news Iceland's government is increasing the number 40 00:02:19,160 --> 00:02:21,960 Speaker 1: of artists it funds for the first time since two 41 00:02:22,000 --> 00:02:25,320 Speaker 1: thousand and nine. Under a grant system called the Artist's 42 00:02:25,320 --> 00:02:29,680 Speaker 1: Salary Fund. Visual artists, musicians, writers and others are paid 43 00:02:29,680 --> 00:02:33,480 Speaker 1: a monthly allowance. That program now covers artists over the 44 00:02:33,520 --> 00:02:37,160 Speaker 1: age of sixty seven and screenwriters. The Minister of Culture 45 00:02:37,160 --> 00:02:39,920 Speaker 1: and Trade in Iceland said income is one thing, but 46 00:02:40,000 --> 00:02:43,239 Speaker 1: it is equally important to nurture our identity as a nation. 47 00:02:46,720 --> 00:02:50,079 Speaker 2: So SAM and Nvidia last week became the most valuable 48 00:02:50,080 --> 00:02:53,800 Speaker 2: company in the world. Went past Microsoft, went past. 49 00:02:53,639 --> 00:02:56,000 Speaker 1: Apple, just for a brief moment, very. 50 00:02:55,840 --> 00:02:58,960 Speaker 2: Briefly, for one shining moment, hit a market cap of 51 00:02:59,120 --> 00:03:04,120 Speaker 2: five point one trillion Australian dollars three trillion US. While 52 00:03:04,160 --> 00:03:08,440 Speaker 2: Microsoft has since got its own back, it's clear and 53 00:03:08,520 --> 00:03:11,560 Speaker 2: video is not slipping out of the top anytime soon, right, 54 00:03:12,000 --> 00:03:14,280 Speaker 2: So talk to me about in video? What are they? 55 00:03:14,520 --> 00:03:16,520 Speaker 2: What do they do? Why have I suddenly been hearing 56 00:03:16,560 --> 00:03:17,080 Speaker 2: about them? 57 00:03:17,160 --> 00:03:19,040 Speaker 1: I feel like it's the most valuable company in the 58 00:03:19,040 --> 00:03:21,480 Speaker 1: world you've never heard of, and I thought this would 59 00:03:21,480 --> 00:03:23,760 Speaker 1: be a really cool opportunity to break down what they 60 00:03:23,800 --> 00:03:28,400 Speaker 1: do because they're deep in the world's AI revolution, and 61 00:03:28,720 --> 00:03:32,080 Speaker 1: as we all know that has exploded in popularity and 62 00:03:32,160 --> 00:03:35,440 Speaker 1: curiosity in the last couple of years. Figuring out how 63 00:03:35,480 --> 00:03:38,320 Speaker 1: AI is incorporated into at least your work, if not 64 00:03:38,400 --> 00:03:41,200 Speaker 1: your life has almost become a necessity for most jobs. 65 00:03:41,560 --> 00:03:43,680 Speaker 1: But I feel like we're all still playing around with 66 00:03:43,800 --> 00:03:46,760 Speaker 1: exactly how to use it. So this is how in 67 00:03:46,880 --> 00:03:50,840 Speaker 1: VideA comes into it, and Video specializes in designing graphics 68 00:03:50,960 --> 00:03:54,600 Speaker 1: processing units or GPUs. I'm not going to do a 69 00:03:54,600 --> 00:03:56,400 Speaker 1: lot of tech jargon. This is the one piece of 70 00:03:56,440 --> 00:03:59,960 Speaker 1: tech jargon you need to remember. So GPUs a crew 71 00:04:00,400 --> 00:04:03,480 Speaker 1: for high performance computing, and that's the general area that 72 00:04:03,520 --> 00:04:07,560 Speaker 1: AI fits into. Basically, it's the brain that helps AI 73 00:04:07,680 --> 00:04:10,360 Speaker 1: be AI. So if you boil it all down, AI 74 00:04:10,480 --> 00:04:14,200 Speaker 1: involves a bunch of little tasks and processes done super 75 00:04:14,240 --> 00:04:17,920 Speaker 1: super quickly, and the GPU is the tool that makes 76 00:04:17,920 --> 00:04:21,320 Speaker 1: everything run smoothly and quickly. So when Video started in 77 00:04:21,360 --> 00:04:23,560 Speaker 1: the nineties, it was actually started as a company that 78 00:04:23,600 --> 00:04:27,599 Speaker 1: focused on graphics for games, but since then it has exploded. 79 00:04:27,760 --> 00:04:30,760 Speaker 1: It now has reached into artificial intelligence. It also does 80 00:04:30,839 --> 00:04:33,120 Speaker 1: data centers we'll talk about what they are soon, and 81 00:04:33,279 --> 00:04:34,360 Speaker 1: autonomous vehicles. 82 00:04:34,720 --> 00:04:37,360 Speaker 2: I think I know about like graphics cards for gaming, 83 00:04:37,440 --> 00:04:38,560 Speaker 2: is that what a GPU is. 84 00:04:38,560 --> 00:04:41,080 Speaker 1: Is it like a physical thing exactly. It's kind of 85 00:04:41,360 --> 00:04:43,680 Speaker 1: a small physical card. It can be big based on 86 00:04:43,800 --> 00:04:47,120 Speaker 1: the machine that is put inside a piece of technology 87 00:04:47,240 --> 00:04:48,960 Speaker 1: like a phone or the laptop in front of you, 88 00:04:49,680 --> 00:04:54,280 Speaker 1: and it helps the technology process images and videos quickly. Now, 89 00:04:54,360 --> 00:04:58,000 Speaker 1: its neighbor inside the machine is called the CPU, and 90 00:04:58,040 --> 00:05:01,440 Speaker 1: that's the central processing unit, and that handles pretty much 91 00:05:01,480 --> 00:05:04,600 Speaker 1: everything else. So it leaves the graphics and visuals to 92 00:05:04,880 --> 00:05:07,039 Speaker 1: the GPU and it runs the rest of the show. 93 00:05:07,400 --> 00:05:10,560 Speaker 2: How does and Video get from being the gaming graphics 94 00:05:10,600 --> 00:05:13,560 Speaker 2: company to the most important company in the world because 95 00:05:13,560 --> 00:05:14,800 Speaker 2: it's so essential to AI. 96 00:05:15,120 --> 00:05:16,640 Speaker 1: I was trying to work out whether this was a 97 00:05:16,720 --> 00:05:19,920 Speaker 1: case of right place, right time and stumbling across an 98 00:05:19,920 --> 00:05:23,120 Speaker 1: amazing opportunity or just incredible foresight, and I think it's 99 00:05:23,120 --> 00:05:25,360 Speaker 1: probably a little bit of both. So when the early 100 00:05:25,440 --> 00:05:28,200 Speaker 1: two thousands, and Video had been in business for ten years, 101 00:05:28,480 --> 00:05:31,520 Speaker 1: they recognized that their GPUs, which like I said before, 102 00:05:31,520 --> 00:05:34,159 Speaker 1: were the little chips that produced visuals and graphics for 103 00:05:34,240 --> 00:05:38,600 Speaker 1: video games, they were also really good at other processing tasks. 104 00:05:39,040 --> 00:05:41,599 Speaker 1: And so essentially what they found was that this little 105 00:05:41,640 --> 00:05:45,480 Speaker 1: chip could, regardless of the subject matter, take one task 106 00:05:45,560 --> 00:05:48,839 Speaker 1: and break it up into thousands of smaller independent tasks, 107 00:05:49,040 --> 00:05:51,880 Speaker 1: and complete it all at once. Think about if you 108 00:05:52,000 --> 00:05:54,640 Speaker 1: ask an AI generator to make a photo of you 109 00:05:54,839 --> 00:05:58,039 Speaker 1: as a Pixar character. So the AI system needs to 110 00:05:58,279 --> 00:06:00,600 Speaker 1: in only a couple of seconds, work out what it 111 00:06:00,640 --> 00:06:03,279 Speaker 1: picks our character actually looks like, what you look like, 112 00:06:03,760 --> 00:06:06,040 Speaker 1: how it can make you look like that, which colors 113 00:06:06,040 --> 00:06:09,000 Speaker 1: to use, how to frame you, which expressions it once 114 00:06:09,040 --> 00:06:10,960 Speaker 1: on your face, and how to actually present it back 115 00:06:10,960 --> 00:06:13,560 Speaker 1: to you as a JPEG. And then it actually has 116 00:06:13,600 --> 00:06:15,880 Speaker 1: to make all of that. That's a lot of brain power, 117 00:06:16,200 --> 00:06:20,080 Speaker 1: and Video's technology is the key behind what makes all 118 00:06:20,120 --> 00:06:22,680 Speaker 1: of that happen so quickly, I mean in some cases 119 00:06:22,680 --> 00:06:25,960 Speaker 1: basically instantly. And so once they tapped into this big 120 00:06:26,000 --> 00:06:29,640 Speaker 1: idea that their technology could do all these different smaller 121 00:06:29,680 --> 00:06:32,280 Speaker 1: tasks at once, this really opened up the world to 122 00:06:32,320 --> 00:06:35,080 Speaker 1: them and they started getting more involved in the way 123 00:06:35,080 --> 00:06:39,760 Speaker 1: that scientific research is conducted artificial intelligence, and in those spaces, 124 00:06:40,080 --> 00:06:43,120 Speaker 1: massive amounts of data needs to be processed really quickly. 125 00:06:43,440 --> 00:06:46,039 Speaker 2: So they've got this technology that is really good at 126 00:06:46,080 --> 00:06:49,400 Speaker 2: doing the one thing everyone needs right now is that 127 00:06:49,480 --> 00:06:51,880 Speaker 2: kind of how they start making a lot of money exactly. 128 00:06:51,920 --> 00:06:54,360 Speaker 1: So what they actually sell, I mean, how they actually 129 00:06:54,440 --> 00:06:56,960 Speaker 1: get your credit card details off you and make their 130 00:06:57,000 --> 00:07:00,920 Speaker 1: money is they sell the technology both as physical technology, 131 00:07:00,960 --> 00:07:03,440 Speaker 1: as the little chips, or as software. They've got some 132 00:07:03,480 --> 00:07:06,479 Speaker 1: programs that you can buy. And I feel like this 133 00:07:06,560 --> 00:07:08,400 Speaker 1: is almost the most simple bit. They're kind of just 134 00:07:08,480 --> 00:07:11,880 Speaker 1: a shopfront with some really cool technology that they own themselves, 135 00:07:12,280 --> 00:07:15,560 Speaker 1: and they've patented all of that technology. And what a 136 00:07:15,600 --> 00:07:17,800 Speaker 1: patent means is they own the rights to how that 137 00:07:17,840 --> 00:07:20,520 Speaker 1: particular product works and it can't be copied. So if 138 00:07:20,520 --> 00:07:23,840 Speaker 1: you think about Coca Cola or your favorite recipe for 139 00:07:23,880 --> 00:07:24,720 Speaker 1: a chocolate cake. 140 00:07:24,600 --> 00:07:27,720 Speaker 2: The original light bulbs Edison bowl right exactly. 141 00:07:27,800 --> 00:07:30,520 Speaker 1: So the original patents of these ideas that end up 142 00:07:30,560 --> 00:07:33,880 Speaker 1: being in everybody's devices can be really really powerful. And 143 00:07:33,920 --> 00:07:37,080 Speaker 1: they've got thousands of patents and they've actually applied for 144 00:07:37,200 --> 00:07:39,840 Speaker 1: a lot more so they're still growing. But to give 145 00:07:39,840 --> 00:07:42,559 Speaker 1: you a sense of what you're using in daily life 146 00:07:42,640 --> 00:07:46,800 Speaker 1: that has an Nvidia product inside it. They're used in HP, 147 00:07:47,160 --> 00:07:51,600 Speaker 1: Dell and Lenovo laptops. They're inside a Nintendo switch, they're 148 00:07:51,640 --> 00:07:57,640 Speaker 1: in Volvos, Audi's and Mercedes Benz either the technology that 149 00:07:57,720 --> 00:08:01,600 Speaker 1: runs the car and soon autonomous view. That's all really 150 00:08:01,680 --> 00:08:03,880 Speaker 1: good the kind of consumer side of things for them, 151 00:08:04,000 --> 00:08:06,560 Speaker 1: But the real money is when they sell heaps of 152 00:08:06,680 --> 00:08:10,840 Speaker 1: chips to data centers and huge servers. So if we 153 00:08:10,920 --> 00:08:14,680 Speaker 1: go back to CHATJBT, Chat GBT is made with Nvideo 154 00:08:14,760 --> 00:08:18,400 Speaker 1: GPUs so in Video Brain okay, so OpenAI partnered with 155 00:08:18,440 --> 00:08:21,200 Speaker 1: Microsoft to make chat GPT. They built the brain with 156 00:08:21,400 --> 00:08:24,640 Speaker 1: thousands of N Video chips that they bought from Nvideo, 157 00:08:25,080 --> 00:08:28,000 Speaker 1: and as CHATJPT gets more popular, they're just going to 158 00:08:28,040 --> 00:08:31,280 Speaker 1: have to order more chips from Video. And it doesn't 159 00:08:31,280 --> 00:08:33,800 Speaker 1: stop there. I mean Adobe is now using Nvideo to 160 00:08:33,880 --> 00:08:37,880 Speaker 1: incorporate AI into its software like Photoshop or Premiere Blackmagic, 161 00:08:37,920 --> 00:08:40,080 Speaker 1: which are the cameras we use to film this podcast. 162 00:08:40,120 --> 00:08:43,400 Speaker 1: They're using it in their editing and graphics software Windows 163 00:08:43,400 --> 00:08:46,040 Speaker 1: Copilot AI is using it. I mean, this is going 164 00:08:46,120 --> 00:08:47,480 Speaker 1: on and on. It's everywhere. 165 00:08:47,679 --> 00:08:50,240 Speaker 2: So in videos making a lot of money. 166 00:08:50,000 --> 00:08:51,960 Speaker 1: Right, It's making a lot of money, but not as 167 00:08:52,000 --> 00:08:54,200 Speaker 1: much as I thought it would make. So last calendar 168 00:08:54,280 --> 00:08:57,440 Speaker 1: year they made about twenty seven billion US dollars, which 169 00:08:57,480 --> 00:08:59,160 Speaker 1: is a lot. I mean, if the daily os made 170 00:08:59,160 --> 00:09:02,679 Speaker 1: that much money, we'd be pretty pumped. But it is 171 00:09:02,800 --> 00:09:05,120 Speaker 1: not as much as a company like Apple. So Apple 172 00:09:05,200 --> 00:09:08,319 Speaker 1: made three hundred and eighty three billion dollars and then 173 00:09:08,320 --> 00:09:10,120 Speaker 1: the question becomes, well, how do you build a company 174 00:09:10,160 --> 00:09:13,000 Speaker 1: as valuable as Apple if you're doing, you know, less 175 00:09:13,000 --> 00:09:15,920 Speaker 1: than ten percent of that revenue. And I guess the 176 00:09:15,920 --> 00:09:18,880 Speaker 1: answer there is the potential. So how big the available 177 00:09:19,000 --> 00:09:22,440 Speaker 1: market is? I mean, realistically speaking, for Apple to go 178 00:09:22,600 --> 00:09:25,240 Speaker 1: from three hundred and eighty three billion to seven hundred 179 00:09:25,240 --> 00:09:28,040 Speaker 1: billion is going to be really really tough. Yeah, most 180 00:09:28,240 --> 00:09:31,520 Speaker 1: of us have iPhones or an Apple products somewhere. They 181 00:09:31,559 --> 00:09:34,440 Speaker 1: don't really have another explosive growth moment unless they build 182 00:09:34,600 --> 00:09:39,040 Speaker 1: new products before and video. They're just getting started and 183 00:09:39,280 --> 00:09:41,520 Speaker 1: the growth is really just beginning. 184 00:09:41,800 --> 00:09:43,400 Speaker 2: Yeah, and it seems like there's not really going to 185 00:09:43,440 --> 00:09:45,960 Speaker 2: be any way of slowing them down right. 186 00:09:45,840 --> 00:09:48,800 Speaker 1: No, I mean AI is now everywhere, think about autonomous vehicles, 187 00:09:48,920 --> 00:09:52,040 Speaker 1: virtual reality, all of these products need and video or 188 00:09:52,040 --> 00:09:54,760 Speaker 1: something like it. But n VideA is also expanding the 189 00:09:54,800 --> 00:09:57,800 Speaker 1: types of products they make, and it now pretty much 190 00:09:57,800 --> 00:10:00,000 Speaker 1: has a deal with every tech company in the world 191 00:10:00,160 --> 00:10:02,880 Speaker 1: except for Apple. Because Apple have their own version of 192 00:10:02,920 --> 00:10:05,720 Speaker 1: the GBU that's called the Apple Silicon Chip. But now 193 00:10:05,760 --> 00:10:10,680 Speaker 1: their client bases stuff like research institutions, financial institutions, healthcare providers. 194 00:10:10,720 --> 00:10:12,600 Speaker 1: I mean, most X ray machines are going to have 195 00:10:12,640 --> 00:10:15,680 Speaker 1: and video chips in them soon. And even governments want 196 00:10:15,720 --> 00:10:18,880 Speaker 1: powerful computing hardware to train their own AI models, to 197 00:10:18,920 --> 00:10:22,920 Speaker 1: make new AI models. All of those organizations need data centers, 198 00:10:22,960 --> 00:10:26,079 Speaker 1: they all need cloud computing, and those two use again 199 00:10:26,120 --> 00:10:28,720 Speaker 1: and video technology. And the really scary thing, as I 200 00:10:28,720 --> 00:10:31,400 Speaker 1: said before about this potential, is that I really do 201 00:10:31,480 --> 00:10:34,160 Speaker 1: think that they're sprinting out of the blocks with AI 202 00:10:34,480 --> 00:10:36,920 Speaker 1: in order not to get caught. So the big threat 203 00:10:36,960 --> 00:10:40,200 Speaker 1: here is that another company like Intel is actually going 204 00:10:40,280 --> 00:10:43,160 Speaker 1: to overtake them. So and video is going super hard, 205 00:10:43,200 --> 00:10:45,040 Speaker 1: super early to try to get out in front and 206 00:10:45,080 --> 00:10:46,200 Speaker 1: have an uncatchable lead. 207 00:10:46,520 --> 00:10:48,800 Speaker 2: Whenever a company starts really taking off like this, I 208 00:10:48,800 --> 00:10:52,720 Speaker 2: feel like they're always concerns. Certainly, I've read about some 209 00:10:52,840 --> 00:10:56,439 Speaker 2: of the environmental challenges around AI. What are some of 210 00:10:56,480 --> 00:10:57,560 Speaker 2: the concerns around in video. 211 00:10:57,760 --> 00:11:01,160 Speaker 1: Well, I've kind of broken it down into three main concerns. Power, 212 00:11:01,320 --> 00:11:03,240 Speaker 1: not you know, plug it into the war power, but 213 00:11:03,360 --> 00:11:06,319 Speaker 1: how much power they have in the market, Those environmental concerns, 214 00:11:06,320 --> 00:11:09,240 Speaker 1: which are really substantive, and the ethical concerns of AI. 215 00:11:09,679 --> 00:11:13,040 Speaker 1: So just quickly, the power discussion here is about how 216 00:11:13,160 --> 00:11:16,319 Speaker 1: much of the GPU market they dominate. So what percentage 217 00:11:16,320 --> 00:11:18,360 Speaker 1: of these chips being sold are and Video And the 218 00:11:18,360 --> 00:11:21,720 Speaker 1: stat is about ninety five percent projects being sold are 219 00:11:21,800 --> 00:11:25,000 Speaker 1: and Video. So the argument there, the criticism there is 220 00:11:25,000 --> 00:11:27,680 Speaker 1: that this is a company that's getting too powerful. Yeah, 221 00:11:28,000 --> 00:11:30,440 Speaker 1: and it's also the same argument applied to the other 222 00:11:30,800 --> 00:11:35,360 Speaker 1: Magnificent seven they're now called Apple, Microsoft, Meta, Amazon, Tesla, 223 00:11:35,480 --> 00:11:39,520 Speaker 1: and Alphabet, which is Google. Then there's those environmental concerns 224 00:11:39,559 --> 00:11:41,840 Speaker 1: you mentioned. I mean, all of those data centers that 225 00:11:41,960 --> 00:11:46,199 Speaker 1: use and Video's hardware produce carbon emissions. If we're to 226 00:11:46,240 --> 00:11:48,480 Speaker 1: reach net zero as quick as possible, we're not going 227 00:11:48,480 --> 00:11:50,160 Speaker 1: to be able to do it if we keep growing 228 00:11:50,200 --> 00:11:53,800 Speaker 1: the number of data warehouses that's being predicted. There's huge 229 00:11:53,800 --> 00:11:56,920 Speaker 1: amounts of electricity and cooling that goes into the maintenance 230 00:11:57,000 --> 00:11:59,760 Speaker 1: of these warehouses. Now Navideo actually knows that this is 231 00:11:59,760 --> 00:12:02,040 Speaker 1: a problem and they say that they're going to invest 232 00:12:02,120 --> 00:12:06,720 Speaker 1: in more energy efficient technologies. And then the AI ethics issue, 233 00:12:06,760 --> 00:12:10,040 Speaker 1: which has just really grabbed me this year, of how 234 00:12:10,040 --> 00:12:14,040 Speaker 1: do we make ethical choices within AI? I mean, arguably 235 00:12:14,120 --> 00:12:18,520 Speaker 1: and video technology could be used for privacy or security concerns, 236 00:12:18,679 --> 00:12:22,040 Speaker 1: threats to governments, and this is really going to be 237 00:12:22,040 --> 00:12:24,640 Speaker 1: a big challenge for the company. And should something negative 238 00:12:24,720 --> 00:12:27,640 Speaker 1: happen using and video technology, they're going to have a 239 00:12:27,640 --> 00:12:28,560 Speaker 1: real case to answer for. 240 00:12:28,840 --> 00:12:30,880 Speaker 2: So do you reckon and video can stay at the top? 241 00:12:31,240 --> 00:12:33,440 Speaker 1: Oh gosh, Lucy. If I could answer that properly, I 242 00:12:33,480 --> 00:12:35,400 Speaker 1: would not be sitting in this chair. I would be. 243 00:12:37,440 --> 00:12:37,960 Speaker 2: Fools. 244 00:12:38,480 --> 00:12:40,480 Speaker 1: I mean, the people who bought into this stock three 245 00:12:40,559 --> 00:12:42,800 Speaker 1: or four years ago. It's got kind of a Bitcoin 246 00:12:42,840 --> 00:12:44,800 Speaker 1: effect about it now, where you know, you might have 247 00:12:44,800 --> 00:12:46,719 Speaker 1: bought one thousand dollars worth of the stock, it's now 248 00:12:46,720 --> 00:12:49,360 Speaker 1: worth a couple of million. So I thought the best 249 00:12:49,360 --> 00:12:51,959 Speaker 1: way to answer this, because I obviously don't know myself, 250 00:12:52,360 --> 00:12:55,200 Speaker 1: is to ask chat JBT ask and then video chip 251 00:12:55,240 --> 00:12:57,839 Speaker 1: the question of whether it's going to be worth more 252 00:12:58,240 --> 00:13:01,560 Speaker 1: in ten years time. It said it is impossible to 253 00:13:01,600 --> 00:13:05,440 Speaker 1: predict the future with certainty. While Nvidia has strong potential 254 00:13:05,480 --> 00:13:08,160 Speaker 1: to grow and maintain a leading position in the tech industry, 255 00:13:08,360 --> 00:13:11,120 Speaker 1: becoming the most valuable company in the world would require 256 00:13:11,160 --> 00:13:16,040 Speaker 1: sustained innovation, strategic decisions, and favorable market conditions. It's also 257 00:13:16,120 --> 00:13:18,560 Speaker 1: going to depend on how well they navigate challenges and 258 00:13:18,679 --> 00:13:23,560 Speaker 1: competition over the next decade. So you know, whilst CHATBTAI 259 00:13:24,320 --> 00:13:27,760 Speaker 1: and video can seemingly do everything, can't make us rich. 260 00:13:28,040 --> 00:13:29,320 Speaker 2: No, can't predict the future. 261 00:13:29,440 --> 00:13:31,439 Speaker 1: No, I can go pretty close well. 262 00:13:31,559 --> 00:13:35,079 Speaker 2: In human language, sounds like there's a lot of challenges 263 00:13:35,160 --> 00:13:37,920 Speaker 2: facing and video. Who's to say if they're actually going 264 00:13:37,960 --> 00:13:39,800 Speaker 2: to be able to hold onto their position at the top. 265 00:13:40,200 --> 00:13:42,640 Speaker 2: Thanks for explaining that for me, Sam, Thanks Lucy, thanks 266 00:13:42,679 --> 00:13:44,800 Speaker 2: so much for joining us today on The Daily YOURDS. 267 00:13:44,840 --> 00:13:47,840 Speaker 2: We hope you come back tomorrow. You can play our 268 00:13:47,920 --> 00:13:51,120 Speaker 2: game picture. This will be linking dog. Thank you link 269 00:13:51,160 --> 00:13:54,080 Speaker 2: it in the show notes. Subscribe to our newsletter and 270 00:13:54,160 --> 00:13:55,479 Speaker 2: our sport newsletter. 271 00:13:55,520 --> 00:13:57,600 Speaker 1: We should get you in every day. It's a fantastic good. 272 00:13:57,920 --> 00:14:04,160 Speaker 2: Ah and de tomorrow. My name is Lily Maddon and 273 00:14:04,200 --> 00:14:07,959 Speaker 2: I'm a proud Arunda Bunjelung Calcuttin woman from Gadighl Country. 274 00:14:08,800 --> 00:14:11,960 Speaker 2: The Daily oz acknowledges that this podcast is recorded on 275 00:14:12,000 --> 00:14:14,480 Speaker 2: the lands of the Gadighl people and pays respect to 276 00:14:14,559 --> 00:14:17,880 Speaker 2: all Aboriginal and torrest Rate island and nations. We pay 277 00:14:17,880 --> 00:14:20,800 Speaker 2: our respects to the first peoples of these countries, both 278 00:14:20,880 --> 00:14:21,760 Speaker 2: past and present,