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Nvidia CEO resigns, worst post-Diwali air since 2021, and J&K attack

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WEBVTT 1 00:00:00.510 --> 00:00:03.270 In this episode, we talk about the extent to which 2 00:00:03.370 --> 00:00:07.589 firecrackers have worsened Delhi's air pollution and what the city's 3 00:00:07.769 --> 00:00:11.169 air quality monitors are not telling us. We also talk 4 00:00:11.210 --> 00:00:14.339 about a recent terror attack in Jammu and Kashmir that 5 00:00:14.390 --> 00:00:18.239 killed three CRPF personnel in the Kulgam district. But we 6 00:00:18.280 --> 00:00:21.059 begin today by talking about the biggest news that has 7 00:00:21.120 --> 00:00:27.989 dominated the AI sector these past few days. Hi, I 8 00:00:28.030 --> 00:00:30.609 am Niharika Nanda and you are listening to 3 Things, 9 00:00:30.890 --> 00:00:39.909 the Indian Express News Show. Yesterday, NVIDIA CEO and co-founder 10 00:00:39.990 --> 00:00:44.060 Jensen Huang resigned, bringing an end to his 33-year tenure 11 00:00:44.200 --> 00:00:47.500 at the chip-making giant he built into an AI powerhouse. 12 00:00:48.079 --> 00:00:51.670 His departure comes soon after the controversy surrounding reports of 13 00:00:51.789 --> 00:00:55.729 extramarital affairs with allegations that the woman involved may have 14 00:00:55.770 --> 00:00:59.130 been working as a Chinese spy. The company has now 15 00:00:59.189 --> 00:01:03.509 launched an investigation into reports that Chinese intelligence targeted its 16 00:01:03.609 --> 00:01:06.890 chief executive through this woman, who was a former executive 17 00:01:07.010 --> 00:01:11.280 at a company called Megaspeed, a Singapore-based data centre operator 18 00:01:11.469 --> 00:01:14.939 with Chinese origins. The company has been under scrutiny by 19 00:01:15.030 --> 00:01:19.400 American authorities since 2024 over suspicions that it was helping 20 00:01:19.459 --> 00:01:23.439 China gain access to restricted AI chips. The controversy has 21 00:01:23.500 --> 00:01:27.659 raised larger questions about China's access to such technology, the 22 00:01:27.700 --> 00:01:31.700 effectiveness of US export restrictions and the risks that companies 23 00:01:31.760 --> 00:01:35.640 like NVIDIA face when their business depends so heavily on 24 00:01:35.840 --> 00:01:40.000 one single individual. So to understand how this controversy unfolded 25 00:01:40.219 --> 00:01:43.420 and what it means for NVIDIA and the wider AI industry, 26 00:01:43.840 --> 00:01:47.230 my colleague Shashank Bhargav speaks to the Indian Express's National 27 00:01:47.269 --> 00:01:49.109 Business Editor, Anil Sasi. 28 00:01:50.299 --> 00:01:54.170 Anil, let's start this conversation by talking about NVIDIA. Tell 29 00:01:54.230 --> 00:01:56.890 us just how important a player is it and what 30 00:01:56.969 --> 00:02:00.340 role does it occupy in the AI ecosystem? 31 00:02:01.329 --> 00:02:04.909 So, Shashank, NVIDIA is, you know, in some ways or 32 00:02:04.969 --> 00:02:08.139 in a lot of ways, the bedrock of this whole 33 00:02:08.159 --> 00:02:12.020 AI boom. It is essentially in some ways the, you know, 34 00:02:12.039 --> 00:02:15.300 the foundational building block, so to speak, because it is 35 00:02:15.360 --> 00:02:18.120 providing the chips that it makes. 36 00:02:18.180 --> 00:02:21.830 These are specialized chips. They're called GPUs or Graphic Processing Units. 37 00:02:22.110 --> 00:02:25.490 NVIDIA started out as a graphic processing card maker for 38 00:02:25.629 --> 00:02:29.030 video games. It just so happened that when the AI 39 00:02:29.050 --> 00:02:33.289 boom started, NVIDIA's GPUs turned out to be far better 40 00:02:33.650 --> 00:02:37.569 at being deployed on a large scale in what are 41 00:02:37.590 --> 00:02:40.870 called servers, server farms, what we otherwise refer to as cloud, 42 00:02:41.090 --> 00:02:46.150 which essentially powers the compute. To train a large language model, 43 00:02:46.189 --> 00:02:49.039 you need a lot of compute. Nvidia's GPUs turned out 44 00:02:49.060 --> 00:02:51.919 to be really apt for this. So effectively in this 45 00:02:51.939 --> 00:02:55.719 whole AI race, Nvidia is selling shovels. I mean, it's 46 00:02:55.840 --> 00:02:58.599 peddling shovels in a gold rush. We still don't know 47 00:02:58.750 --> 00:03:01.870 if any of the AI players have hit paydart because 48 00:03:02.090 --> 00:03:04.909 monetization is still, you know, there's a big question mark 49 00:03:05.009 --> 00:03:07.500 over it. But Nvidia is the one that is actually 50 00:03:07.560 --> 00:03:09.840 selling the real hardware. you know, or for which it's 51 00:03:09.879 --> 00:03:12.979 getting paid for, you know, which you can see on 52 00:03:13.000 --> 00:03:15.620 the ground where there is a queue. So in that sense, 53 00:03:15.759 --> 00:03:18.979 NVIDIA is quite indispensable to this whole AI rush. 54 00:03:19.560 --> 00:03:22.870 And of course, Jensen Huang had headed this company. Can 55 00:03:22.889 --> 00:03:25.250 you tell us what kind of role did he play 56 00:03:25.909 --> 00:03:28.050 in making this company what. 57 00:03:27.909 --> 00:03:28.330 It is now? 58 00:03:29.569 --> 00:03:33.129 So Jensen Huang is someone who started the company. He's 59 00:03:33.189 --> 00:03:37.669 been with NVIDIA through all of this. He has helped 60 00:03:37.789 --> 00:03:42.069 the company pivot towards this new source of opportunity and 61 00:03:42.129 --> 00:03:45.370 income when the whole AI race started. 62 00:03:45.409 --> 00:03:47.430 That's in the late 2016-2017, around that time. 63 00:03:49.500 --> 00:03:51.500 When it was felt that maybe you need a lot 64 00:03:51.539 --> 00:03:54.180 of compute at scale and the GPU sort of completely 65 00:03:54.219 --> 00:03:56.240 fit into that equation. 66 00:03:56.460 --> 00:03:58.319 So he is a larger. 67 00:03:58.000 --> 00:04:01.419 Than life figure, not just for NVIDIA, but also for 68 00:04:01.439 --> 00:04:03.990 the AI race in that sense, you know, alongside Sam 69 00:04:04.090 --> 00:04:08.090 Altman and, you know, the Anthropic
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Chief. Well, quite clearly, 70 00:04:08.210 --> 00:04:10.770 this guy is in some ways, you know, the rock 71 00:04:10.789 --> 00:04:13.229 star of sorts for the AI boom as well. 72 00:04:13.860 --> 00:04:17.839 Okay, now let's talk about this controversy. It recently came 73 00:04:17.879 --> 00:04:22.620 to light that Huang was having an extramarital affair, which 74 00:04:22.680 --> 00:04:24.839 of course would not have been a big deal. But 75 00:04:24.980 --> 00:04:28.040 the allegations are that the person he was having an 76 00:04:28.079 --> 00:04:31.920 affair with is a Chinese spy. Tell us, where do 77 00:04:31.959 --> 00:04:33.819 these allegations stem from? 78 00:04:34.660 --> 00:04:38.620 So it's part of American policy, especially after the second 79 00:04:38.699 --> 00:04:41.860 Trump administration to sort of try and curtail the sales 80 00:04:42.199 --> 00:04:47.060 of the high end NVIDIA chips to countries that are not, 81 00:04:47.480 --> 00:04:50.839 you know, either they're competing with the US or not 82 00:04:50.879 --> 00:04:54.319 exactly aligned with the, you know, the US foreign policy 83 00:04:54.519 --> 00:04:58.389 and strategic imperative. So China is one such country or 84 00:04:58.410 --> 00:05:01.350 it's been identified with the Trump administration as one such country. 85 00:05:01.769 --> 00:05:02.930 So, you know, an. 86 00:05:02.910 --> 00:05:06.089 Extramarital affair by itself would not really have caused a 87 00:05:06.110 --> 00:05:09.329 lot of consternation. It is the person who's allegedly in 88 00:05:09.379 --> 00:05:12.439 the equation here, this lady called Alice Wang, who's working 89 00:05:12.560 --> 00:05:16.420 for a Singapore-based company called Megaspeed International. It is alleged 90 00:05:16.519 --> 00:05:20.389 that this company is fronting for some Chinese end users 91 00:05:20.430 --> 00:05:20.829 of the chips. 92 00:05:21.290 --> 00:05:23.410 And that she's a Chinese national. It is also being 93 00:05:23.449 --> 00:05:23.949 alleged that. 94 00:05:23.930 --> 00:05:28.029 She was also working for the Chinese Secret Service, the 95 00:05:28.069 --> 00:05:31.569 Ministry of State Security, you know, in overt or covert manner. 96 00:05:31.610 --> 00:05:34.740 She was an ex-journalist and someone who's, I think, worked 97 00:05:34.800 --> 00:05:40.399 with HSBC earlier. And then she transitioned to this role 98 00:05:40.540 --> 00:05:44.779 in Megaspeed. She, it seems, had left Megaspeed in between, 99 00:05:44.839 --> 00:05:46.860 but she continued to sort of steer affairs at the 100 00:05:46.920 --> 00:05:50.000 helm of this company and quite clearly was aligned to 101 00:05:50.050 --> 00:05:53.509 some broad Chinese interests is what the allegation is. Given 102 00:05:53.569 --> 00:05:57.250 that Jensen Huang is in charge of a company that 103 00:05:57.610 --> 00:06:01.009 is selling products where, you know, China is one country 104 00:06:01.050 --> 00:06:02.689 where there is a certain amount of restriction, at least 105 00:06:02.750 --> 00:06:06.589 on the US side, on supplies of NVIDIA's top-end chips, 106 00:06:06.629 --> 00:06:09.000 the sort of Blackwell chips that it makes. You know, 107 00:06:09.009 --> 00:06:12.180 there's a huge conflict of interest when in light of 108 00:06:12.240 --> 00:06:14.240 all of this, it's been seen that there's a Chinese 109 00:06:14.259 --> 00:06:18.180 spy who's managed to come into his confidence. And of course, 110 00:06:18.459 --> 00:06:20.540 you know, the allegation is that she managed to influence 111 00:06:20.600 --> 00:06:24.720 his decisions in, you know, ferreting out chips, etc. to 112 00:06:25.019 --> 00:06:28.600 her company through which these were, you know, then allegedly 113 00:06:28.839 --> 00:06:30.699 sold to companies such as Alibaba. 114 00:06:31.360 --> 00:06:33.899 And you mentioned that US has a policy to restrict 115 00:06:34.360 --> 00:06:37.980 the supply of these chips to countries like China, you know, countries... 116 00:06:38.089 --> 00:06:41.670 that are competing with US in the AI race. But 117 00:06:41.930 --> 00:06:45.779 Jensen Huang had been pushing that US should be selling 118 00:06:45.839 --> 00:06:47.620 these chips to China, right? 119 00:06:48.060 --> 00:06:49.410 What was his argument? 120 00:06:50.160 --> 00:06:52.819 Now, look, to clarify, the first set of photographs where 121 00:06:52.939 --> 00:06:55.060 the two of them, Jensen Huang and Alice Huang, were 122 00:06:55.240 --> 00:06:58.430 captured together was in 2024. Just as a disclaimer, Jensen 123 00:06:58.509 --> 00:07:01.889 Huang has had this view for a long time that 124 00:07:01.970 --> 00:07:04.829 the chips ought to be sold to China. Now, his 125 00:07:05.290 --> 00:07:07.670 arguments could be professional in the sense he heads a 126 00:07:07.709 --> 00:07:12.519 company and China is the biggest customer of his high-end 127 00:07:12.579 --> 00:07:16.060 chips after the U.S., His argument, you know, through all 128 00:07:16.079 --> 00:07:19.439 of this has been that if we do not supply 129 00:07:19.500 --> 00:07:20.139 these chips. 130 00:07:20.230 --> 00:07:22.250 They will develop them on their own. It's just a 131 00:07:22.269 --> 00:07:22.910 question of time. 132 00:07:23.149 --> 00:07:24.750 If we sell it to them, we might have better 133 00:07:24.769 --> 00:07:27.189 control over this and there might not be sufficient incentive 134 00:07:27.209 --> 00:07:28.540 for them to develop it on their own. 135 00:07:28.649 --> 00:07:29.839 But more than that, I think. 136 00:07:30.199 --> 00:07:33.339 You know, the commercial interest really sort of superseded all 137 00:07:33.360 --> 00:07:35.759 of these arguments because I think he's an entrepreneur. He 138 00:07:35.800 --> 00:07:38.019 has his company, which has a unique product for which 139 00:07:38.040 --> 00:07:39.920 there is demand. And the demand is, after the US, 140 00:07:39.939 --> 00:07:42.970 the highest in a
particular geography. And he would really 141 00:07:43.009 --> 00:07:45.149 want that jurisdiction to be able to access those chips. 142 00:07:45.170 --> 00:07:48.350 So I sense that his arguments were essentially commercial. And 143 00:07:48.509 --> 00:07:50.889 it helped that he had slowly sort of started to 144 00:07:50.949 --> 00:07:54.149 become President Donald Trump's advisor on tech affairs. He started 145 00:07:54.230 --> 00:07:57.040 out as a call that it seems that President Trump had. 146 00:07:56.889 --> 00:07:59.199 Made to Wang on one of his birthdays. 147 00:07:59.319 --> 00:08:02.199 And slowly he sort of, you know, came into the 148 00:08:02.300 --> 00:08:07.000 old advisory pool and became a very influential advisor of sorts, 149 00:08:07.060 --> 00:08:10.139 something that probably was not taken too very kindly by 150 00:08:10.199 --> 00:08:12.860 the dispensation in the White House. Because if you see 151 00:08:12.920 --> 00:08:15.220 how this whole memo was leaked, it probably came out, 152 00:08:15.459 --> 00:08:17.680 you know, it was an intelligence memo that was submitted 153 00:08:17.699 --> 00:08:17.879 to the. 154 00:08:17.860 --> 00:08:19.779 White House and probably leaked out of the White House. 155 00:08:19.899 --> 00:08:21.819 So somebody in the White House had an incentive to 156 00:08:21.860 --> 00:08:24.379 leak this out. which shows the kind of distrust perhaps 157 00:08:24.430 --> 00:08:28.250 that was there internally within the administration in how close 158 00:08:28.449 --> 00:08:30.850 this person had gotten to President Trump and how, you know, 159 00:08:30.870 --> 00:08:34.110 he was perhaps influencing his decisions and how those decisions 160 00:08:34.210 --> 00:08:38.049 were in contradiction to the broader sort of, you know, 161 00:08:38.070 --> 00:08:42.779 technological and strategic goals and initiatives that the administration flagged 162 00:08:42.820 --> 00:08:43.320 at the outset. 163 00:08:44.019 --> 00:08:48.120 And Anil, do we know why the intelligence agencies started 164 00:08:48.419 --> 00:08:49.149 investigating him? 165 00:08:50.029 --> 00:08:53.360 So it was always known that people in the US 166 00:08:53.409 --> 00:08:57.220 who are dealing with China would perhaps be vulnerable to 167 00:08:57.259 --> 00:09:00.639 such tactics. It is possible that he was under the 168 00:09:00.679 --> 00:09:04.559 scanner for multiple other things, as would be a lot 169 00:09:04.580 --> 00:09:06.830 of other people who have dealings with China. 170 00:09:06.889 --> 00:09:08.389 It's possible that Elon Musk could. 171 00:09:08.289 --> 00:09:09.789 Have been under the scanner because he has a lot 172 00:09:09.830 --> 00:09:11.990 of business coming in from China. It just so happened 173 00:09:12.070 --> 00:09:15.690 that this whole affair sort of started and they would 174 00:09:15.710 --> 00:09:19.710 have probably been looking at this lady because she was 175 00:09:19.769 --> 00:09:23.840 born in
mainland China and, you know, she had some links. 176 00:09:24.039 --> 00:09:27.000 And in that sense, I'm sure the intelligence tracking would 177 00:09:27.039 --> 00:09:29.620 have happened purely because of that. And I don't know 178 00:09:29.820 --> 00:09:31.980 what precedes what in the sense the affair was discovered 179 00:09:32.059 --> 00:09:34.299 because they were tracking her or, you know, they tracked 180 00:09:34.340 --> 00:09:35.279 the affair and they got. 181 00:09:35.179 --> 00:09:37.960 Hold to her. But it does seem that he was 182 00:09:38.000 --> 00:09:38.970 under the scanner for a while. 183 00:09:39.500 --> 00:09:41.990 And Anil, do we have any proof that China got 184 00:09:42.029 --> 00:09:45.169 hold of chips by Nvidia through Megaspeed? 185 00:09:45.950 --> 00:09:48.809 Yeah, so there are a few things that happened which 186 00:09:49.250 --> 00:09:53.409 raised suspicion. It seems Megaspeed came out of nowhere around 187 00:09:53.450 --> 00:09:56.129 the time that these American restrictions kicked in. 188 00:09:56.700 --> 00:09:59.740 Mega speeds, you know, balance sheets, it suddenly. 189 00:09:59.480 --> 00:10:02.539 Ballooned from some, you know, $ 33 million at the end 190 00:10:02.580 --> 00:10:04.259 of 2023 to about $ 3 billion in a span of 191 00:10:04.259 --> 00:10:11.799 12 months. Megaspeed's biggest customer through two step-down subsidiaries. There 192 00:10:11.820 --> 00:10:14.070 was a Malaysian subsidiary and there was a Thai subsidiary. 193 00:10:14.419 --> 00:10:17.529 It seems one of the big customers was Alibaba. Alibaba 194 00:10:17.629 --> 00:10:21.549 is a private company, but all private companies in China 195 00:10:21.610 --> 00:10:24.190 have some sort of a hand of the state, so 196 00:10:24.230 --> 00:10:26.669 to speak. It could be the federal government, it could 197 00:10:26.690 --> 00:10:28.679 be the provincial government. So there is a sort of 198 00:10:28.720 --> 00:10:31.740 a loop that sort of fits in. In between, it 199 00:10:31.799 --> 00:10:35.399 seems that this lady resigned from Megaspeed, but she continued 200 00:10:35.480 --> 00:10:38.179 to be associated with Megaspeed. In fact, there is someone 201 00:10:38.220 --> 00:10:43.309 who was quoted by NYT that they still reported to her, 202 00:10:43.570 --> 00:10:47.090 even though she was technically not in charge. Alice Huang, 203 00:10:47.269 --> 00:10:50.610 according to this NYT story, had bragged about her access 204 00:10:50.649 --> 00:10:54.720 to Jensen Huang and NVIDIA. And she said that all 205 00:10:54.779 --> 00:10:57.620 that had helped her raise funds for the business. She 206 00:10:57.720 --> 00:11:03.100 said that apparently in internal conversations. So Megaspeed was essentially intermediary. 207 00:11:03.159 --> 00:11:05.580 You know, it was procuring chips and supplying it to people. 208 00:11:06.000 --> 00:11:08.080 And if you look at just the, you know, the 209 00:11:08.120 --> 00:11:10.799 fact that it doesn't pass the smell test, if the 210 00:11:10.899 --> 00:11:14.370 person who's working for an intermediary has a liaison with 211 00:11:14.490 --> 00:11:17.970 the head of the supplier, a really coveted supplier, and 212 00:11:19.029 --> 00:11:22.769 this intermediary then supplies, you know, the procured chips to Alibaba. 213 00:11:22.990 --> 00:11:26.610 And Alibaba is one of the three entities in China 214 00:11:26.649 --> 00:11:29.970 that have come out with their own large language models, 215 00:11:30.009 --> 00:11:33.139 which in some ways compete with, you know, the models 216 00:11:33.179 --> 00:11:37.679 that OpenAI and Google and Anthropic have in the market. So, 217 00:11:37.759 --> 00:11:40.019 you know, if you join the dots, clearly there is 218 00:11:40.059 --> 00:11:40.440 a problem. 219 00:11:41.039 --> 00:11:43.679 And now with this controversy, NVIDIA is said to be 220 00:11:43.759 --> 00:11:47.659 facing a key man risk, right? Can you explain to 221 00:11:47.730 --> 00:11:49.309 our listeners what that means? 222 00:11:50.289 --> 00:11:52.620 So a key man risk is essentially a term that's 223 00:11:52.740 --> 00:11:55.559 used to describe, you know, how much of a risk 224 00:11:55.860 --> 00:11:59.559 or how vulnerable a corporate entity is to a key personnel. 225 00:11:59.600 --> 00:12:01.799 That could be a founder. It could be a high 226 00:12:01.840 --> 00:12:04.259 paid employee. It could be the CEO. And that typically 227 00:12:04.279 --> 00:12:07.309 arises when, you know, there's a larger than life figure 228 00:12:07.529 --> 00:12:11.629 associated with a big entity, a strategic entity, and there's 229 00:12:11.649 --> 00:12:14.149 no succession planning in place. You know, the key man risk, 230 00:12:14.330 --> 00:12:18.009 this term really came into vogue last year when Elon 231 00:12:18.080 --> 00:12:22.440 Musk bulldozed the board and the Tesla board and the 232 00:12:22.720 --> 00:12:26.399 shareholders to OK a package for him, which is, I think, 233 00:12:26.519 --> 00:12:29.009 over a period of years, close to about $ 1 trillion 234 00:12:29.389 --> 00:12:30.570 in benefits, cumulative benefits. 235 00:12:30.889 --> 00:12:32.029 And his whole. 236 00:12:31.929 --> 00:12:34.529 Argument during that time was that I will resign if 237 00:12:34.549 --> 00:12:35.210 you don't approve it. 238 00:12:35.470 --> 00:12:38.769 You know, and so the risk of maybe paying out. 239 00:12:38.610 --> 00:12:42.009 $ 1 trillion versus having a situation where you've not paid 240 00:12:42.029 --> 00:12:44.960 out that amount, but Musk goes. In some ways, you know, 241 00:12:45.039 --> 00:12:47.919 at least the shareholders weighed it as maybe giving that 242 00:12:47.940 --> 00:12:51.960 money being better than him leaving. That is how vulnerable 243 00:12:52.000 --> 00:12:55.080 Tesla is to this one man. The same happens for 244 00:12:55.600 --> 00:12:58.039 Jensen Wang. You know, you just know this one guy. 245 00:12:58.220
--> 00:13:00.990 It's a bit like Jamie Dimon in JP Morgan. 246 00:13:01.019 --> 00:13:03.029 You know, we don't know, I mean, what happens. Or 247 00:13:03.110 --> 00:13:05.549 like Mark Zuckerberg in Meta. Right. 248 00:13:05.620 --> 00:13:08.340 And ever since this matter came to light, ever since 249 00:13:08.379 --> 00:13:10.360 we got to know about these allegations, I mean, this 250 00:13:10.379 --> 00:13:14.870 has really impacted Nvidia stock. It has really tanked over 251 00:13:14.909 --> 00:13:15.590 the past few days. 252 00:13:16.470 --> 00:13:18.710 And to that extent, there could be more damage that 253 00:13:18.730 --> 00:13:19.330 could be coming in. 254 00:13:19.750 --> 00:13:22.590 And, you know, I think the most scary part is 255 00:13:22.610 --> 00:13:24.929 that this whole allegation comes at a time when AI 256 00:13:24.980 --> 00:13:28.120 valuations are under the scanner. AI stocks have been tanking 257 00:13:28.240 --> 00:13:31.000 ever since the midterm results came out and the Democrats 258 00:13:31.220 --> 00:13:33.700 came to power, you know, in the two houses, the 259 00:13:33.759 --> 00:13:35.840 Senate and the House of Representatives. So, you know, there 260 00:13:35.879 --> 00:13:38.220 is a general sense that the sort of the push 261 00:13:38.500 --> 00:13:42.399 for AI and for AI capacities such as these, you know, 262 00:13:42.440 --> 00:13:45.990 server farms, etc., would perhaps go down now that the 263 00:13:46.409 --> 00:13:50.830 Democrats have come in. The whole NVIDIA controversy comes at 264 00:13:50.850 --> 00:13:54.269 a time when the larger sort of operating environment and 265 00:13:54.350 --> 00:13:58.860 the larger feeling about AI being an investable sort of sector, 266 00:13:59.059 --> 00:14:01.399 that whole thing is under cloud. And to that extent, 267 00:14:01.600 --> 00:14:04.620 this could also have a ripple effect on the already 268 00:14:04.639 --> 00:14:08.080 sort of sliding fortunes of AI valuations. 269 00:14:08.899 --> 00:14:11.549 And Anand, could this have any repercussions for India? How 270 00:14:11.590 --> 00:14:15.090 does it affect things here? And how does it impact 271 00:14:15.149 --> 00:14:17.080 the overall AI sector? 272 00:14:18.070 --> 00:14:22.789 Look, India as jurisdiction has predominantly been outside, or it's 273 00:14:22.809 --> 00:14:25.549 been felt that India is outside of the whole AI, 274 00:14:25.690 --> 00:14:29.250 you know, investing boom that we've sort of seen unfold 275 00:14:29.269 --> 00:14:31.990 over the last two or three years. One implication for 276 00:14:32.110 --> 00:14:35.950 India could be that, you know, if this incident further 277 00:14:36.029 --> 00:14:39.590 sort of stokes the AI downside, India as an investment 278 00:14:39.610 --> 00:14:44.409 destination for foreign portfolio investors, you know, that proposition might 279 00:14:44.460 --> 00:14:47.679 become stronger. Because if big foreign investors were to pull 280 00:14:47.759
--> 00:14:50.240 out of Nvidia, and there's already a pullout happening from 281 00:14:50.259 --> 00:14:52.580 across a lot of AI stocks, where will that money 282 00:14:52.620 --> 00:14:54.960 be deployed? Well, you know, there is a chance that 283 00:14:55.139 --> 00:14:56.940 money could sort of, you know, a part of that 284 00:14:56.980 --> 00:15:00.320 money could come back into India. But of course, you know, 285 00:15:00.399 --> 00:15:04.470 I think for investors, for policymakers, This is a big 286 00:15:04.509 --> 00:15:08.230 lesson in terms of how do you value a company 287 00:15:08.269 --> 00:15:10.629 or how do you keep investing in a company where 288 00:15:10.710 --> 00:15:14.470 the risks are, you know, overtly sort of shaped. 289 00:15:14.350 --> 00:15:18.000 By one larger than life personality. So it's a warning. 290 00:15:18.080 --> 00:15:20.159 It serves as a warning in terms of where to 291 00:15:20.179 --> 00:15:23.399 draw the line somewhere and realistically sort of, you know, 292 00:15:23.500 --> 00:15:27.350 see if these sort of commercial decisions are not clouded by, 293 00:15:27.730 --> 00:15:28.970 you know, any such incident. 294 00:15:28.990 --> 00:15:30.730 And that possibility is always there. 295 00:15:31.009 --> 00:15:33.370 It is a clear and present danger and it's just 296 00:15:33.409 --> 00:15:35.470 that it's come to the fore like this in the 297 00:15:35.529 --> 00:15:37.820 NVIDIA case, but it's a warning for businesses across the world. 298 00:15:42.539 --> 00:15:46.259 And next, we turn our attention to Delhi's deteriorating air quality. 299 00:15:46.899 --> 00:15:49.539 It has been more than four days since Diwali, but 300 00:15:49.559 --> 00:15:52.259 the capital is still dealing with the fallout from the 301 00:15:52.340 --> 00:15:56.009 firecrackers burst on the night of the festival. Data shows 302 00:15:56.049 --> 00:15:59.669 that before Diwali, the major contributors to pollution in Delhi 303 00:15:59.710 --> 00:16:03.909 NCR were farm fires and vehicle emissions. But that changed 304 00:16:04.070 --> 00:16:09.519 dramatically on Diwali night when firecrackers accounted for 71% of 305 00:16:09.559 --> 00:16:14.480 the region's fine particulate pollution. And so, unsurprisingly, Delhi recorded 306 00:16:14.639 --> 00:16:17.919 its worst air quality on Diwali Day since 2021. The 307 00:16:17.940 --> 00:16:23.000 impact was felt indoors as well, with residents reporting persistent coughing, 308 00:16:23.399 --> 00:16:28.350 respiratory problems and difficulty stepping outdoors. In fact, even on Wednesday, 309 00:16:28.629 --> 00:16:33.330 firecrackers remained a significant source of the city's PM2. 5 pollution, 310 00:16:33.789 --> 00:16:38.090 accounting for 7.4% of the total particulate load. So to 311 00:16:38.169 --> 00:16:41.190 understand how Delhi's air quality has changed in the days 312 00:16:41.250 --> 00:16:43.990 since Diwali, what can we expect in the coming days 313 00:16:44.230 -->
00:16:47.049 and what steps can people take to protect themselves from 314 00:16:47.090 --> 00:16:50.299 the pollution, we speak to the Indian Express's Sophia Matthew 315 00:16:50.379 --> 00:16:53.600 who has been tracking the issue. Sophia, can you begin 316 00:16:53.639 --> 00:16:57.360 by telling us what was the situation like on Diwali evening? 317 00:16:58.000 --> 00:17:02.019 As a Delhiite myself, I could hear crackers bursting till post-midnight. 318 00:17:02.759 --> 00:17:07.650 So firstly, like you said, this time, even after midnight, 319 00:17:07.750 --> 00:17:11.670 there were widespread firecrackers that were being burst. And this 320 00:17:11.710 --> 00:17:16.890 was despite Supreme Court's order permitting green firecrackers only for 321 00:17:16.970 --> 00:17:20.680 particular time slots. That is from 6 to 7 a.m. 322 00:17:21.019 --> 00:17:24.099 on November 7 and 8 and also 8 to 10 p.m. 323 00:17:24.380 --> 00:17:27.519 on these two particular days. Now, the police officials had 324 00:17:27.579 --> 00:17:31.029 also said that there were so many violations and they 325 00:17:31.069 --> 00:17:35.769 had tried to stop people and counsel residents on the restrictions. 326 00:17:36.150 --> 00:17:40.630 According to police officials, from October 1st and November 6th, 327 00:17:40.910 --> 00:17:45.799 around 15,000 kilograms of firecrackers were seized. So, already on 328 00:17:45.859 --> 00:17:49.420 the background, there were a lot of activities that were 329 00:17:49.440 --> 00:17:52.940 going on. going on and there were no assurances that 330 00:17:53.000 --> 00:17:57.990 these were green firecrackers so pm 2.5 levels especially like 331 00:17:58.089 --> 00:18:02.329 if we see delhi pollution control committee's data we saw 332 00:18:02.410 --> 00:18:07.519 that in some stations it even neared 5000 micrograms per 333 00:18:07.539 --> 00:18:11.259 cubic meter Now that is huge because the national safe 334 00:18:11.359 --> 00:18:16.319 limit is only 60 micrograms per cubic meter. So it 335 00:18:16.400 --> 00:18:21.210 was like about 83 times this national safe limit. And 336 00:18:21.309 --> 00:18:25.950 WHO limits it like 15 microgram per cubic meter of 337 00:18:26.009 --> 00:18:29.549 PM 2.5 can only be allowed in 24 hours. So 338 00:18:29.950 --> 00:18:33.150 in Delhi stations, this cross like over 330 times when 339 00:18:33.190 --> 00:18:34.170 you consider WHO limits. 340 00:18:36.940 --> 00:18:39.500 And these readings, like you said, are from the Delhi 341 00:18:39.519 --> 00:18:43.089 Pollution Control Committee. But then there is also data from 342 00:18:43.250 --> 00:18:46.009 the Central Pollution Control Board or the CPCB. 343 00:18:46.470 --> 00:18:47.880 So what is the difference there? 344 00:18:48.849 --> 00:18:54.549 So CPCB systems, the analyzers, they do not take measurements 345 00:18:54.690 --> 00:18:58.349 above 1000 microgram per cubic meter. So which is why 346 00:18:58.390 --> 00:19:02.029 we see this difference that the state pollution control boards 347 00:19:02.109 --> 00:19:05.329 monitoring data is different in the sense that they also 348 00:19:05.390 --> 00:19:10.210 record above 1000 microgram per cubic meter. But the central 349 00:19:10.250 --> 00:19:14.390 pollution control board, on the other hand, after 1000 microgram 350 00:19:14.410 --> 00:19:17.210 per cubic meter, they'll show it has blank for those 351 00:19:17.269 --> 00:19:22.539 hourly recordings. Also, CPCB collects all the data from the 352 00:19:22.579 --> 00:19:26.819 state pollution control boards, AQI stations, and also there are 353 00:19:26.859 --> 00:19:31.289 some other AQI stations set up by IATM, IMD, all 354 00:19:31.349 --> 00:19:34.289 of that. And its own, CPCB's own AQI stations are 355 00:19:34.329 --> 00:19:37.779 there in all states. Now, from these different stations, it 356 00:19:37.799 --> 00:19:44.000 collects Amalgam collects all the data for 8 different pollutants 357 00:19:44.160 --> 00:19:49.589 and then it finally calculates the day's average AQI. So 358 00:19:49.970 --> 00:19:53.730 if any data is missing, then the final AQI number 359 00:19:53.779 --> 00:19:55.460 is also then impacted. 360 00:19:56.259 --> 00:19:59.240 And we understand that on the night of Diwali, the 361 00:19:59.279 --> 00:20:04.039 readings of some monitoring stations were not available, both for 362 00:20:04.079 --> 00:20:07.490 the CPCB and the Delhi Pollution Control Committee. Do we 363 00:20:07.509 --> 00:20:10.170 know why that is? Is it because the levels were 364 00:20:10.190 --> 00:20:11.869 too high or something else? 365 00:20:12.779 --> 00:20:16.720 Right. So, in fact, Central Pollution Control Board has issued 366 00:20:16.819 --> 00:20:22.200 a statement saying that its instruments have a upper limit 367 00:20:22.299 --> 00:20:26.769 of 1000 microgram per cubic meter. So, its analyzers do 368 00:20:26.829 --> 00:20:30.670 not record anything above that. which is why it said 369 00:20:30.730 --> 00:20:35.470 that it can appear as, you know, missing or data 370 00:20:35.509 --> 00:20:39.359 that is not there. But before that, the Delhi Pollution 371 00:20:39.400 --> 00:20:44.640 Control Committee also, there are a few stations that it 372 00:20:44.700 --> 00:20:48.339 has in Delhi and among those stations also, there were 373 00:20:48.359 --> 00:20:53.410 some Missing readings. Now that happens, the station level officers 374 00:20:53.509 --> 00:20:58.829 had told us it's because of some instruments getting very much, 375 00:20:59.130 --> 00:21:02.759 you know, overloaded. And because of that, there are some 376 00:21:03.099 --> 00:21:08.170 interruptions or sensor related issues that are faced. Especially during 377 00:21:08.269 --> 00:21:12.920 these peak, episodic, Diwali or festive related, you know, time. 378 00:21:13.279 --> 00:21:17.339 And DPCC also has a control room where they are 379 00:21:17.380 --> 00:21:21.740 supposed to trigger alerts to the
monitoring station if a 380 00:21:21.779 --> 00:21:25.180 station is not giving reading in real time. These also 381 00:21:25.220 --> 00:21:30.289 take place and... So when we analyzed that data was missing, 382 00:21:30.609 --> 00:21:33.990 basically we noticed that from, it was not only Diwali night, 383 00:21:34.089 --> 00:21:38.849 but a week before that also, at least 282 missing 384 00:21:39.150 --> 00:21:44.279 PM10 readings were observed. And some stations had continuous hours 385 00:21:44.380 --> 00:21:48.599 of outage. So, you know, this then definitely has an 386 00:21:49.000 --> 00:21:51.359 impact on the final AQI also. 387 00:21:52.019 --> 00:21:52.279 Right. 388 00:21:52.400 --> 00:21:56.029 So, Sophia, is the CPCB now planning to remove the 389 00:21:56.069 --> 00:21:58.170 cap that their air monitoring systems have? 390 00:21:58.789 --> 00:22:00.250 Have they said anything about that? 391 00:22:01.009 --> 00:22:01.210 Right. 392 00:22:01.329 --> 00:22:05.589 So it has said that there are internal consultations and 393 00:22:05.650 --> 00:22:11.069 deliberations going on to review how these extreme, these outside 394 00:22:11.130 --> 00:22:14.309 readings can also be taken into account or if there 395 00:22:14.349 --> 00:22:17.789 has to be any updations. So that is underway, the 396 00:22:17.849 --> 00:22:21.450 whole methodology of, you know, calculating AQI and how to 397 00:22:21.539 --> 00:22:25.740 incorporate these readings that come up or show outwardly to 398 00:22:25.759 --> 00:22:29.220 be missing. those discussions are going on is what CPCB 399 00:22:29.359 --> 00:22:33.059 has claimed but apart from that on the time being 400 00:22:33.099 --> 00:22:39.140 what are the concerns basically because CPCB calculates the day's 401 00:22:39.279 --> 00:22:44.049 AQI official AQI based on a certain number of like 402 00:22:44.109 --> 00:22:49.869 it takes into account eight different pollutants and Then it calculates, 403 00:22:50.190 --> 00:22:53.200 you know, if a pollutant, all of these have a 404 00:22:53.240 --> 00:22:57.720 certain number of hourly readings, only then it will take 405 00:22:57.819 --> 00:23:02.049 that pollutant into account for its final calculation because otherwise 406 00:23:02.069 --> 00:23:06.230 it will show insufficient data. So if the data itself 407 00:23:06.369 --> 00:23:09.630 is not hourly reading itself is not taken into account, 408 00:23:09.710 --> 00:23:12.970 then there is a risk that the final AQI will 409 00:23:13.009 --> 00:23:16.849 then take that particular station's data to be insufficient and 410 00:23:16.930 --> 00:23:19.650 then the final AQI could be undercounted. 411 00:23:19.690 --> 00:23:21.450 So that risk is there. 412 00:23:22.059 --> 00:23:22.279 Right. 413 00:23:22.470 --> 00:23:25.140 And you also had the opportunity of talking to some 414 00:23:25.160 --> 00:23:27.140 experts regarding pollution levels. 415 00:23:27.599 --> 00:23:28.859 So what did they have to say? 416 00:23:30.170 --> 00:23:34.750 So for reporting, I spoke to two main experts who 417 00:23:34.789 --> 00:23:38.519 are pollution analysts and who've been tracking Delhi's air quality 418 00:23:38.559 --> 00:23:41.740 for some time now, not only Delhi, but overall India. 419 00:23:41.900 --> 00:23:45.829 So one of them is Sunil Dahia. He's a founder 420 00:23:45.910 --> 00:23:49.970 and lead analyst at this think tank. EnviroCatalyst, he said 421 00:23:50.089 --> 00:23:53.269 that it was very evident as per the data that 422 00:23:53.369 --> 00:23:58.170 firecrackers drove most of the spike because sulfur dioxide emissions 423 00:23:58.470 --> 00:24:03.200 nearly quadrupled and most of the rise was observed after 424 00:24:03.259 --> 00:24:07.099 the 10 p.m. Supreme Court deadline. So he said that 425 00:24:07.140 --> 00:24:11.880 there were, you know, open violations. And even at a.m. 426 00:24:11.920 --> 00:24:16.220 the next morning, post Diwali, the PM 2.5 remained very high. 427 00:24:16.279 --> 00:24:19.559 It was close to 350 microgram per cubic meter. And 428 00:24:19.940 --> 00:24:25.380 what he said was the meteorological conditions were also not favorable. 429 00:24:25.420 --> 00:24:29.099 Like the wind speed was very, you know, close to negligible. 430 00:24:29.200 --> 00:24:32.740 There were calm winds. And so it did not help 431 00:24:32.849 --> 00:24:36.950 the pollutants to get dispersed properly. He said that, you know, 432 00:24:36.970 --> 00:24:41.470 it's a classic example that When meteorological conditions are also 433 00:24:41.509 --> 00:24:44.630 not favorable and then you add to that, there is 434 00:24:44.690 --> 00:24:48.490 already a pollution baseline that is already high because of 435 00:24:48.650 --> 00:24:49.559 other sources also. 436 00:24:49.579 --> 00:24:52.119 It's not just firecrackers, industries. 437 00:24:52.200 --> 00:24:56.480 Vehicular emissions, road dust, construction dust, all of that is 438 00:24:56.599 --> 00:25:00.900 already there in Delhi and other neighboring areas. So adding 439 00:25:00.940 --> 00:25:05.930 to that, this firecracker emissions just increased the pollution load 440 00:25:05.970 --> 00:25:09.930 a lot. Then Manoj Kumar, he is from CREA, another 441 00:25:09.970 --> 00:25:10.650 think tank. 442 00:25:10.789 --> 00:25:11.490 He is a lead. 443 00:25:11.349 --> 00:25:14.839 Pollution analyst there. He said that he also flagged that 444 00:25:15.099 --> 00:25:20.099 they had stopped reporting. And, you know, these readings, he 445 00:25:20.180 --> 00:25:22.940 explicitly said that, you know, they should not be treated 446 00:25:23.049 --> 00:25:27.769 as any ordinary missing data because it could lead to underestimation. 447 00:25:28.109 --> 00:25:31.890 And it means that the extreme, you know, the high 448 00:25:31.970 --> 00:25:36.910 peak pollution concentrations are not getting properly represented in what 449 00:25:36.950 --> 00:25:38.109 the final figures are. 450
00:25:38.650 --> 00:25:42.150 And Sophia, we understand that a massive number of farm 451 00:25:42.210 --> 00:25:45.779 fires took place in Punjab around the same time as Diwali. 452 00:25:46.480 --> 00:25:48.160 Did that make the situation worse? 453 00:25:48.539 --> 00:25:49.180 Tell us about that. 454 00:25:50.109 --> 00:25:54.049 So, what happened before Diwali was that, like a few 455 00:25:54.109 --> 00:25:59.539 days before Diwali, by November 5, predominant contributor was farm 456 00:25:59.599 --> 00:26:04.299 fires and transport emissions. We moved closer to Diwali by 457 00:26:04.359 --> 00:26:07.599 November 6 and November 7, we saw a dip. We 458 00:26:07.640 --> 00:26:13.289 saw that firecracker contribution, which had considerably increased. So, Now 459 00:26:13.349 --> 00:26:17.950 for the first time also, IATM has started showing how 460 00:26:18.009 --> 00:26:24.109 much is the exact contribution of firecrackers to Delhi's pollution, PM2. 5. 461 00:26:23.450 --> 00:26:31.380 So they clearly showed that slightly more than 71% of PM2. 5 462 00:26:30.430 --> 00:26:34.700 in Delhi was directly due to firecrackers bursting. And so 463 00:26:35.019 --> 00:26:40.619 by that time, by November 8, FarmFi's contribution had dipped significantly. 464 00:26:41.079 --> 00:26:44.680 And so, like I said, it's also because of wind direction. 465 00:26:44.839 --> 00:26:47.549 It's also dependent on that. So, it's a very, you know, 466 00:26:47.609 --> 00:26:50.130 it's a episodic pollutant. 467 00:26:50.829 --> 00:26:51.069 Right. 468 00:26:51.309 --> 00:26:54.190 So, what's the current situation of the AQI in the 469 00:26:54.230 --> 00:26:58.440 Delhi NCR region? And what has the meteorological department predicted 470 00:26:58.599 --> 00:26:59.680 for the upcoming days? 471 00:27:00.509 --> 00:27:03.950 So right now, the AQI trend is that it's going 472 00:27:03.990 --> 00:27:07.519 to turn to severe category, which is AQI that is 473 00:27:07.640 --> 00:27:13.230 above 400. So IATM has said that roughly from November 474 00:27:13.230 --> 00:27:16.390 12 to 13, the AQI is going to be like 475 00:27:16.490 --> 00:27:19.670 above 400. So that is the forecast for now. And 476 00:27:19.750 --> 00:27:22.130 why is this so? One of the main factors is 477 00:27:22.210 --> 00:27:26.319 also wind condition. Wind speed is expected to, you know, 478 00:27:26.339 --> 00:27:29.519 keep on varying. So some days it could be like 479 00:27:29.519 --> 00:27:33.700 5 to 10 kmph and it could also increase to 480 00:27:33.700 --> 00:27:36.900 15 kmph. But that's the limit. It's not going to be, 481 00:27:37.049 --> 00:27:41.529 it's not forecast above 15 kmph. And also, the temperature 482 00:27:41.750 --> 00:27:44.470 is also going to dip in the coming days. So 483 00:27:44.569 --> 00:27:48.549 both a dip in temperature and low wind speeds have 484 00:27:48.569 --> 00:27:53.720 a direct impact, apart from all the sources, the baseline 485 00:27:53.759 --> 00:27:55.519 pollution that is there in Delhi. 486 00:27:56.019 --> 00:27:59.420 So, Sophia, keeping all of this in mind, are there 487 00:27:59.440 --> 00:28:03.339 any guidelines regarding what people can do to keep themselves 488 00:28:03.599 --> 00:28:05.900 safe from the pollution-related health issues? 489 00:28:06.660 --> 00:28:11.670 So, CQM in its advisory says only for GRAP4, mind you, 490 00:28:11.990 --> 00:28:18.450 specifically about health-related advisory under GRAP4, which is imposed when 491 00:28:18.609 --> 00:28:23.190 AQI is expected to be in severe category 450 plus 492 00:28:23.259 --> 00:28:27.299 and all. So, CQM says that it advises citizens to, 493 00:28:27.539 --> 00:28:31.599 first of all, limit their outdoor exposure. Any kind of, 494 00:28:31.660 --> 00:28:36.359 you know, non-essential outdoor activity should be limited. And especially 495 00:28:36.380 --> 00:28:43.170 it advises children, pregnant women, elderly and those with respiratory ailments, 496 00:28:43.369 --> 00:28:48.589 cardiovascular issues, cerebrovascular issues or any other chronic diseases to 497 00:28:48.829 --> 00:28:51.430 avoid outdoor activities and to stay indoors. 498 00:28:51.789 --> 00:28:53.589 So this is an advisory that they have. 499 00:28:53.750 --> 00:28:57.430 And they also say that if, you know, it's required 500 00:28:57.470 --> 00:29:01.269 to move outdoors, then they have an advisory to wear mask. 501 00:29:02.069 --> 00:29:06.269 So this is what CQM has said but now AQI 502 00:29:06.849 --> 00:29:10.549 is also an indicative scale based on you know it's 503 00:29:10.650 --> 00:29:14.269 directly correlated to the health impact that may be caused 504 00:29:14.390 --> 00:29:17.710 when a pollution level is under a certain category. In 505 00:29:17.769 --> 00:29:21.910 severe category it says that all people including healthy people 506 00:29:22.069 --> 00:29:27.099 and people especially with serious ailments those with existing diseases. 507 00:29:26.839 --> 00:29:27.700 Are in danger. 508 00:29:28.240 --> 00:29:31.759 And yeah, so that was the whole, even the AQI 509 00:29:31.799 --> 00:29:35.589 scale is kind of associated with the health impact. But 510 00:29:36.029 --> 00:29:39.490 so CPCB has also highlighted this in its latest statement 511 00:29:39.529 --> 00:29:43.079 saying that which is why they have set it to 512 00:29:43.079 --> 00:29:46.799 500 because beyond 500, it would mean the same thing. 513 00:29:46.880 --> 00:29:51.099 The last threshold that they have kept 401 to 500. 514 00:29:51.099 --> 00:29:54.990 If it crosses 500, they are claiming that the health 515 00:29:55.250 --> 00:29:59.230 impact rate is anyway for all the entire population. So 516 00:29:59.250 --> 00:30:01.230 it's going to remain the same. So which is why 517 00:30:01.250 --> 00:30:04.180 they have kept it to 500. 518 00:30:07.730 --> 00:30:10.470 And finally, we turn to an attack in South Kashmir's 519 00:30:10.569 --> 00:30:15.380 Kulgam
district where three CRPF personnel were injured after suspected 520 00:30:15.440 --> 00:30:20.119 terrorists opened fire at a security checkpoint in Akhran area 521 00:30:20.200 --> 00:30:23.279 near Mir Bazar on Wednesday. This is the third terror 522 00:30:23.339 --> 00:30:26.650 attack in Jammu and Kashmir since July and the second 523 00:30:26.750 --> 00:30:29.930 targeting security personnel. The attack took place on a day 524 00:30:29.970 --> 00:30:33.690 when Lieutenant Governor Manoj Sinha was visiting Kulgam to inaugurate 525 00:30:33.769 --> 00:30:36.869 a festival. Security had been stepped up for his visit 526 00:30:36.930 --> 00:30:40.480 to a government degree college around 16 kilometres from the 527 00:30:40.519 --> 00:30:44.140 site of the attack. The Indian Express's Basharat Masood reports 528 00:30:44.220 --> 00:30:48.180 that the investigators are examining the possibility that the attackers 529 00:30:48.380 --> 00:30:52.680 belong to a Lashkar-e-Taiba module operating in South Kashmir. At 530 00:30:52.720 --> 00:30:56.869 least three suspected overground workers of the outfit are being questioned, 531 00:30:57.180 --> 00:31:01.250 with investigators looking into whether they provided logistical support and 532 00:31:01.329 --> 00:31:04.990 shelter to the attackers. Police officers told Masood that as 533 00:31:05.029 --> 00:31:09.390 per preliminary investigations, at least three terrorists were involved. two 534 00:31:09.450 --> 00:31:13.250 of whom appear to be foreign nationals. The attackers reportedly 535 00:31:13.309 --> 00:31:16.269 approached the checkpoint on foot from a marshy area around 536 00:31:16.269 --> 00:31:20.319 50 metres away, opened fire and escaped through nearby trees 537 00:31:20.440 --> 00:31:24.059 and bushes. Security forces have cordoned off the area and 538 00:31:24.099 --> 00:31:27.380 launched a search operation. The CRPF said that the attack 539 00:31:27.400 --> 00:31:30.940 took place around 2.15pm and one of the injured personnel 540 00:31:30.980 --> 00:31:34.460 sustained bullet injuries to his abdomen and spine and was 541 00:31:34.549 --> 00:31:37.490 undergoing surgery, while the other two were injured in their 542 00:31:37.549 --> 00:31:41.170 legs and arms. Basharat also reports that the attack has 543 00:31:41.250 --> 00:31:45.130 raised concerns within the security establishment about the ability of 544 00:31:45.230 --> 00:31:48.890 small groups of foreign terrorists to carry out targeted strikes 545 00:31:48.990 --> 00:31:52.420 with the help of local support networks despite a decline 546 00:31:52.559 --> 00:31:56.680 in local recruitment. There had been general intelligence inputs, warning 547 00:31:56.720 --> 00:32:00.880 of possible hit-and-run attacks around Diwali, following which security forces 548 00:32:01.019 --> 00:32:04.750 across Shamu and Kashmir were alerted. However, officers say such 549 00:32:04.769 --> 00:32:08.769 attacks are difficult to prevent without specific intelligence. The period 550 00:32:08.789 --> 00:32:13.319 before winter is also considered particularly vulnerable as terrorists move 551 00:32:13.359 --> 00:32:16.480 from higher reaches of the Pir Panjal mountains to lower 552 00:32:16.559 --> 00:32:23.390 elevations before snowfall restricts movement. You were listening to Three 553 00:32:23.450 --> 00:32:26.509 Things by the Indian Express. Today's show was edited and 554 00:32:26.569 --> 00:32:30.210 mixed by Suresh Pawar and produced by Shashank Bhargav and me, 555 00:32:30.230 --> 00:32:33.289 Niharika Nanda. If you like the show, then do subscribe 556 00:32:33.329 --> 00:32:35.900 to us wherever you get your podcasts. You can also 557 00:32:35.940 --> 00:32:38.130 recommend the show to someone you think will like it. 558 00:32:38.480 --> 00:32:40.519 Share it with a friend or someone in your family. 559 00:32:40.539 --> 00:32:42.859 It's the best way for people to get to know 560 00:32:42.900 --> 00:32:46.160 about us. You can also tweet us at Express Audio 561 00:32:46.380 --> 00:32:49.569 and write to us at podcasts at indianexpress.com.
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