ТРАНСКРИПЦИЯ 🔗
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
Load full transcript
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.