China Decode: China’s Renewable Energy Dominance in the AI Race

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0:02:07 The Earth only has a few days left.
0:02:13 Roscoe Cadulian and the rest of the Phoenix Colony have to re-upload their minds into the quantum computer.
0:02:18 But a new threat has arisen that could destroy their stored consciousness forever.
0:02:27 Listen to Oscar-winner Brendan Fraser reprise his role as Roscoe Cadulian in this follow-up to the Audible original blockbuster, The Downloaded.
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0:03:02 It’s inside these data centers that the machines that train artificial intelligence actually work.
0:03:08 Without big data centers, you can’t train your AI algorithms to get better and better.
0:03:12 And data centers, as you mentioned, are really power-hungry.
0:03:16 And they also need a lot of air conditioning, and they need a lot of water.
0:03:25 And so the race between the U.S. and China on artificial intelligence, to a large extent, comes down to these data centers.
0:03:32 Welcome to China Decode. I’m Alice Han.
0:03:33 And I’m James King.
0:03:39 In today’s episode of China Decode, we are discussing the build-out of AI data centers,
0:03:42 how the U.S. and China are taking different approaches,
0:03:45 the Chinese Navy’s debut of a new aircraft carrier,
0:03:47 and what that means for tensions in the region,
0:03:49 and the dream of flying taxis.
0:03:52 It might be closer than you think.
0:03:53 Where are you today, Alice?
0:03:58 Well, I am in Sicily, and this is actually going to amuse you, James.
0:04:02 I just came back from climbing Mount Etna to talk about dancing on a volcano.
0:04:07 And hopefully you can’t hear the wailing sirens on the street.
0:04:09 It’s fairly noisy here.
0:04:11 I’ll keep an ear out for them as the podcast goes on.
0:04:12 Thanks, James.
0:04:15 All right, James, let’s get straight into it.
0:04:19 In this great race that’s developing over capable AI tools,
0:04:22 both China and the U.S. are building out massive data centers.
0:04:27 Generative AI models lean on a massive amount of powerful GPUs,
0:04:32 which need both a lot of electricity to perform and a great deal of water to stay cool.
0:04:36 So given the high cost and the vast energy implications of these data centers,
0:04:40 let’s talk a little bit about how these things are getting paid for
0:04:44 and getting power in both the Chinese and the American context.
0:04:50 So, James, I think, you know, now that we’ve turned the page on the trade conflict
0:04:53 and it seems that we’re back into a detente period,
0:04:57 what struck me over the last week as being quite interesting was the Jensen Huang piece in the FT,
0:05:01 where you used to work, in which he says that China is, quote-unquote,
0:05:04 nanoseconds behind America in the AI race,
0:05:11 primarily because electricity generation is so much more abundant in China and a great deal cheaper.
0:05:18 And so he, I think, has issued a clarin call within the American context to showcase to Americans
0:05:23 that China actually has some tools in its toolkit in this broader AI competition.
0:05:29 And, you know, I would love to get into the minutiae of it in terms of the comparison.
0:05:34 But what struck me as interesting is the fact that the U.S., when you look at CapEx cycle,
0:05:40 there’s clearly orders of magnitude ahead, not only in terms of just raw CapEx that we’ve seen
0:05:44 by the big tech companies, the big AI frontier labs and the tech companies,
0:05:49 but also in the fact that you have, from a policy standpoint, the U.S. Stargate project,
0:05:53 which is $500 billion deployed over four years.
0:05:57 I think the Chinese equivalent Stargate, which was announced by Alibaba this year,
0:05:59 is only $53 billion over three years.
0:06:04 But I think this is going to incite a reaction from China,
0:06:08 probably in the next March NPC when the five-year plan is unveiled,
0:06:12 to really, I think, increase the amount of expenditure for data centers.
0:06:18 And again, as I’ve alluded to, China is a country that leads in power generation.
0:06:22 It basically produces 10,000 terawatts per hour in terms of energy.
0:06:25 That’s more than double what the U.S. produces.
0:06:30 But certainly it has, as we’ve talked about in previous podcast episodes,
0:06:35 a semiconductor disadvantage in the sense that it doesn’t have access to the energy-efficient,
0:06:40 cutting-edge, leading-edge semiconductors that are produced, say, for instance, by NVIDIA.
0:06:44 But James, what’s your take on this AI competition that is ballooning?
0:06:49 Well, as you say, Alice, I think the key point is around these data centers,
0:06:54 because it’s in data centers, you know, which you wouldn’t really look twice at.
0:06:57 I mean, they’re sort of big square buildings on the side of the road.
0:07:05 But it’s inside these data centers that the machines that train artificial intelligence models
0:07:06 actually work.
0:07:13 And so without big data centers, you can’t train your AI algorithms to get better and better.
0:07:18 So that’s the key aspect of why data centers are important.
0:07:22 And data centers, as you mentioned, are really power-hungry.
0:07:26 And they also need a lot of air conditioning, and they need a lot of water.
0:07:31 And so the race between the U.S. and China on artificial intelligence,
0:07:34 to a large extent, comes down to these data centers.
0:07:40 And as you said at the beginning, I think it’s really interesting that Jensen Huang,
0:07:47 the CEO of NVIDIA, said this month that he thought that China will win the AI race.
0:07:53 Then he slightly backpedaled and said, oh, well, China’s only nanoseconds behind.
0:08:01 But I think this allows us to really look into the constituent parts of who is likely to win the AI race.
0:08:04 Because, of course, the stakes are enormous.
0:08:07 AI is going to power all kinds of applications.
0:08:10 It’s going to power all kinds of technologies.
0:08:11 And it already is.
0:08:16 So the question of who wins is really crucial to the technology economy.
0:08:21 Now, as you mentioned, Alice, each country has different assets.
0:08:28 The first thing to be said is that at the moment, the U.S. is way ahead in terms of the number of data centers it has.
0:08:33 The U.S. has got well over 5,000 data centers as things stand.
0:08:39 And China, according to statistics that I’ve been able to find, has only about 450.
0:08:42 But this might not stay that way.
0:08:46 And we also need to look at the cost structures involved.
0:08:50 The remarkable thing about China’s data centers is where they’re located.
0:08:54 They tend to be in the deserts in the far north of China.
0:08:59 Some of them are in a desert called the Taklamakan, which actually I’ve been to.
0:09:01 I went through it on a bus.
0:09:03 I wish I could say I went on a camel.
0:09:06 But on a bus, it took four days to cross.
0:09:10 And the name of the Taklamakan actually means if you go in,
0:09:11 you never come out.
0:09:15 And it is one of the most inhospitable places on Earth.
0:09:22 The temperature is often nudging 50 degrees Celsius, about 120 degrees Fahrenheit.
0:09:31 But the reason it’s there and the reason that China’s putting so many of these data centers in deserts is because the sun beats down.
0:09:46 And the power that China is generating through these solar panels is actually the cheapest power anywhere in the world.
0:09:51 It costs about two cents, two US cents per kilowatt hour.
0:09:59 Just to give an example, that is about one-fifth of the cheapest cost of electricity generated in the UK through coal.
0:10:06 So China’s got this natural advantage in terms of building data centers in the desert.
0:10:13 But it also has a couple of other strategies, one of which is big subsidies by the government,
0:10:19 subsidies in terms of the energy bills that the data centers have to pay.
0:10:28 The government is subsidizing that so that it means that a lot of these data centers in China are paying just half of what you would normally pay for the data centers.
0:10:34 And the other big advantage that China has is called super clusters.
0:10:45 I won’t go into this in great detail, but just suffice it to say that the US is far ahead when it comes to the power of individual computer chips.
0:10:50 So the Blackwell chip is far more powerful than anything that China has.
0:11:00 But China is perfecting a way of putting lots and lots of its own indigenous chips, mostly made by Huawei, into what’s called a super cluster.
0:11:04 Some of these super clusters have like 380 chips in them.
0:11:07 But China wants to go much, much bigger than that.
0:11:11 It wants to have a super cluster of more than 8,000 chips.
0:11:16 And so it hopes that it can increase the compute power by using many, many more chips.
0:11:21 So I think that’s the contours of the competition that we see.
0:11:22 What are you hearing, Alice?
0:11:27 I mean, do you think China can make it or do you think the US is just in an unassailable lead?
0:11:38 So the way that I think about this is that if you recall during the Biden administration, there were a great amount of export controls in Chinese chips, or rather Chinese imports of chips coming out of America and elsewhere.
0:11:42 And the consensus at the time was that China is screwed.
0:11:44 China will not be able to find an option.
0:11:50 AI will severely be impaired in terms of its development in China as a result of this hardware constraint.
0:11:53 That consensus has shifted a great deal.
0:11:59 And I sense that the consensus around AI has also shifted in the sense that people no longer think that China is down and out.
0:12:05 China has, as you alluded to and referenced, James, its own distinct advantages and disadvantages.
0:12:17 The way that I think about the future is that whereas a lot of the internet revolution was about bytes, I think in some respects we’re returning to the world of atoms.
0:12:23 And China has been very good at indigenizing and securitizing its energy supply chains.
0:12:27 As I referenced, it is the world’s biggest producer of electricity.
0:12:35 And it has even more projects that it’s going to bring online, like the hydroelectric dam in Tibet, which could put even more energy on the grid.
0:12:43 I think that this is something that people are starting to realize is an important aspect, this energy aspect in the AI competition.
0:12:45 It’s not just about chips.
0:12:53 It’s not just about, you know, the trillions of CapEx that the U.S. seems to be dedicating over the next few years in terms of CapEx outlays for AI data centers.
0:12:57 It’s also about energy production and energy efficiency.
0:13:00 So on the production front, China is leading in energy.
0:13:05 On the efficiency front, as you alluded to, James, there’s interesting ways in which they can cluster.
0:13:21 But even the tech companies themselves, when they design their LLMs, which we could get into, they are designing more energy efficient LLMs that in theory could lead to an 82% drop in the number of NVIDIA GPUs that they would require to power the AI models.
0:13:33 And so just to give people a sense of the numbers, what would normally take 1,192 GPUs, apparently the researchers at Alibaba are able to do with just 213 NVIDIA H20 GPUs.
0:13:40 That’s the difference between spending $2.5 million on NVIDIA GPUs and spending way over $14 million.
0:13:47 And again, if you think about it from an energy perspective, the power savings could also be massive as well.
0:13:54 So I think there’s an interesting thing that’s happening on the energy production front and the energy efficiency front that I think people are starting to cotton on to.
0:14:01 Yeah, I mean, I think we kind of got to bring it back to why Jensen Huang is saying that China will win.
0:14:13 And I think a lot of the reasons are the ones you just cited, plus the fact that China has gone for an open source model in all of these large language models that it’s coming out with.
0:14:22 So as of October, nine of the 10 top open source artificial intelligence models are Chinese.
0:14:30 This is in contrast to many of the American models, such as OpenAI’s ChatGPT, which is not open source.
0:14:35 So China’s going really a quite a different route from the US.
0:14:51 China’s going cheap power, super clusters of semiconductors, fewer data centers, but probably cheaper, cheaper to build, and then trying to make the artificial intelligence models that it brings out open source,
0:15:02 so that a lot of companies in China can then start to build their applications based on those models and start to make money by deploying AI in the economy.
0:15:04 I think that’s China’s approach.
0:15:10 It still doesn’t quite explain to me why Jensen Huang would say that he thinks China will win.
0:15:19 Because if you look at the US, they’ve got better chips, far more powerful chips, and they’ve got many more data centers to train the AI models.
0:15:21 So I don’t know.
0:15:24 I don’t know which side of this I come down on, actually, to tell you the truth, Alice.
0:15:27 I think the US is a formidable competitor.
0:15:29 Yeah, I still agree.
0:15:30 It’s too early to tell.
0:15:36 And as we’ve been saying in previous podcasts, China’s going to do AI with Chinese characteristics.
0:15:37 No doubt about it.
0:15:40 It’s going to do it in a way that’s quite different from the US.
0:15:54 And as we were talking about in previous episodes, the US is chasing AGI areas that might be more compute intensive, whereas China is not just making energy cheap in the support of AI models, but it’s also making models cheap.
0:16:01 I mean, I was looking at some of the numbers, the DeepSeq chat model, the cost per million output tokens is only $1.10.
0:16:04 QN Plus from Alibaba, it’s $1.20.
0:16:08 And for reference, GPT-5 from OpenAI, it’s $10.
0:16:11 Claude Sonnet from Anthropic, Claude Sonnet 4.5 is $15.
0:16:15 So they are making these LLMs cheaper along with energy.
0:16:22 And I think with massive implications when we think about the AI competition, in many ways, they are competing for different things, is my conclusion.
0:16:26 Okay, we’ll be back with more after a quick break, so stay with us.
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0:18:50 Last week, China revealed that it had commissioned a massive new aircraft carrier, the Fujian,
0:18:53 and it’s the first one that it designed and built all by itself.
0:18:59 This comes a short time after Chinese President Xi Jinping’s massive military parade in September
0:19:05 for the 80th anniversary, which drew a lot of attention on how recent advancements in homegrown
0:19:11 Chinese hardware have raised the capabilities of China’s military, inching closer to parity with
0:19:12 the U.S.
0:19:17 James, you’re more of an expert in this area, so I really want to listen to what you have
0:19:17 to say.
0:19:21 But I was actually in Beijing during the week of the military parade.
0:19:27 And what was interesting, not only was the patriotism around it, but the fact that China
0:19:30 really was, so to speak, bringing out the big guns.
0:19:38 It was showing a new nuclear triad in terms of equipment, military drones, new ICBMs, intercontinental
0:19:41 ballistic missiles, hypersonic missiles, you name it.
0:19:48 But it was very clear to me watching this that this was a big sign to Washington and the
0:19:53 region that China had key deterrence capabilities when it comes to its military hardware and equipment.
0:19:55 James, you’re very close to this.
0:19:57 How big of a deal is this Fujian carry?
0:20:00 And what does it mean for China’s broader military goals?
0:20:07 I think it’s a big deal because it helps us to kind of understand the military balance between
0:20:09 the U.S. and China.
0:20:12 There’s no question that China is catching up the U.S.
0:20:19 And this is part of a bigger topic of the geopolitics between the two superpowers.
0:20:24 And it particularly relates to potential theatres of warfare.
0:20:31 I use the word potential underlined and stressed because I’m not predicting any kind of a conflagration
0:20:32 between the U.S. and China.
0:20:37 But let’s say around Taiwan, also the South China Sea.
0:20:43 And there are other areas where the U.S. and China kind of contest each other already in a
0:20:44 geopolitical sense.
0:20:51 So, the emergence of China’s third aircraft carrier, which, as you mentioned, was designed
0:20:54 and built entirely by China, that is important.
0:21:02 The big picture for China is that China wants to build what it calls a modernized military force
0:21:04 by 2035.
0:21:05 So, that’s 10 years from now.
0:21:12 And it wants to build what it calls a world-class military force by 2050.
0:21:18 And what people understand by the words world-class means that by that time, it hopes to be able
0:21:21 to take on the U.S. if it needs to.
0:21:27 As things stand, purely in terms of aircraft carriers, China is a long way behind the U.S.
0:21:32 Now that China has three aircraft carriers, the U.S. has 11.
0:21:37 So, China has the second largest number of aircraft carriers of any country in the world.
0:21:40 But clearly, it’s still far behind.
0:21:47 And I think it’s true to say that the technology of the U.S. carriers is far superior to those
0:21:48 in China.
0:21:54 For instance, the U.S. carriers are nuclear-powered, whereas the Chinese carriers at the moment all
0:21:56 run on diesel.
0:22:00 And, of course, nuclear power is much more self-sustaining than diesel.
0:22:07 However, when we look at other aspects of the military balance, you know, China is already
0:22:08 a formidable competitor.
0:22:13 The Chinese Navy is now far larger than that of the U.S.
0:22:19 They’re projected to have about 50% more ships than the U.S. by 2030.
0:22:27 So, already, I think we can’t sort of underestimate what China can do in terms of military projection.
0:22:32 Just coming back to this aircraft carrier itself, I mean, it’s absolutely enormous.
0:22:36 It’s more than 300 meters long.
0:22:39 I mean, the scale of these things is just incredible.
0:22:47 That means it can carry about 60 aircraft, and it costs well over $6 billion U.S. to make.
0:22:50 So, you know, it’s a pretty amazing thing, I must say.
0:22:54 What did you think when you saw pictures of this carrier, Alice?
0:22:58 Well, firstly, I mean, they definitely were putting their best foot forward.
0:23:02 Everything that came out on the parade was extremely, extremely impressive.
0:23:07 But at the end of the day, you know, these images are Potemkin villages in a way.
0:23:09 They’re not battle-tested and battle-ready.
0:23:13 And that, I think, has been the enduring concern about the PLA’s capabilities.
0:23:18 It’s one thing to have cutting-edge equipment and parity with the U.S., but it’s another thing
0:23:21 to have the battle experience that, say, Russia is having in Ukraine.
0:23:27 And I think that one of the big concerns for Xi Jinping, especially after the Russia-Ukraine
0:23:34 conflict emerged, is whether or not the PLA has the ability and battle readiness to take
0:23:40 a stance on Taiwan to either launch an amphibious assault or a salami slicer through a quarantine
0:23:41 and blockade.
0:23:43 And I’m not so sure.
0:23:47 And people have different views on whether or not these military equipment are designed
0:23:54 to deter the U.S. from aggression in the Asia-Pacific or to help launch Xi Jinping’s ambitions
0:23:59 when it comes to what he would call a reunification of China, taking Taiwan into the fault.
0:24:04 But when I think about this, I think a lot about both capabilities and intentions.
0:24:09 And it’s not clear to me, especially after the military purges that we saw at the fourth
0:24:13 plenum, whether or not Xi Jinping feels that he is ready for prime time when it comes to
0:24:16 using these carriers for a Taiwan showdown.
0:24:21 Yeah, I mean, you know, the whole question of Taiwan and whether or not China would make a move
0:24:28 to try to retake Taiwan is one of those things that China experts spend a long time thinking
0:24:29 about and talking about.
0:24:31 And, you know, everybody has their own opinion.
0:24:34 There really is no evidence.
0:24:39 That’s why you find such a diversity of opinion among people of our trade, Alice.
0:24:46 But my own take on this is that China wants to build up a military that is so forbiddingly
0:24:54 huge that the U.S. would think twice or think more than twice about ever taking China on in
0:24:55 any kind of a military theater.
0:25:03 And my sense on Taiwan particularly is that China would very much like to reabsorb Taiwan
0:25:04 without fighting.
0:25:10 It knows that if it was to launch a military adventure against Taiwan, there would be catastrophic
0:25:13 consequences for the global economy.
0:25:14 And that would include China.
0:25:21 So I think its aim is probably to build up its military force by showing off new hardware,
0:25:27 such as this huge new aircraft carrier, such as the military parade in Beijing that you mentioned,
0:25:33 and then hope that everybody is kind of cowed and overawed.
0:25:37 And Taiwan meekly returns to the motherland at some point in the future.
0:25:41 That’s my sort of summary of what I think China is aiming at.
0:25:44 Well, when you were talking, I was thinking of two things.
0:25:49 The first is the fact that this aircraft carrier is run on diesel, not nuclear.
0:25:55 The U.S. is still at the state of supremacy when it comes to nuclear-powered submarines and
0:25:56 operational nuclear warheads.
0:25:58 The figure is quite stunning.
0:26:02 China has 600 operational nuclear warheads.
0:26:05 And you compare to the U.S. with well over 5,000.
0:26:07 The U.S. is leading.
0:26:10 In fact, I think the second largest stockpile is held by Russia.
0:26:14 That gives you a sense of how much China needs to do to catch up.
0:26:17 It’s projected they’ll reach 1,000 warheads, China, by 2030.
0:26:24 Its stockpile of ICBMs, the Intercontinental Ballistic Missiles, is roughly on parity with the
0:26:29 U.S. But there are certain key areas, and I’ve heard from military experts in the realm
0:26:35 of submarine technology, especially where China is a great degree behind the U.S.
0:26:41 But the second point I wanted to make, and to quote my boss and mentor Neil Ferguson, he has
0:26:48 this law called Ferguson’s Law in which any country that spends more on debt servicing rather than
0:26:52 the military as throughout history has been on a downturn trajectory.
0:26:55 It loses its superpower status.
0:26:58 And the U.S. hit that threshold a few years ago.
0:27:05 I think that that is quite material when we think about the superpower struggle between China and the U.S.
0:27:11 China is increasing its military spending, massively ramping up its military arsenal at a time when the U.S.
0:27:13 is doing it in the opposite direction.
0:27:18 That’s, I think, quite material when we think about the future of U.S.-China in the region.
0:27:19 Oh, that’s great.
0:27:21 I hadn’t heard of Ferguson’s Law before.
0:27:22 I really like that.
0:27:27 I guess the problem with China is, though, that China keeps its military spending deeply secret.
0:27:30 I mean, it does come out with figures, but nobody trusts them.
0:27:37 So we don’t really know whether China is spending more or less on debt servicing than on its military.
0:27:38 That’s a very fair point.
0:27:40 But that’s a great metric.
0:27:41 I really like that.
0:27:42 Yeah.
0:27:53 And we’ll have to see in the March NPC what they say, because every year in the March NPC in the government work report, they will issue a statement about how much they want to increase military spending by.
0:27:56 To your point, James, there’s so much of this is smoke and mirrors.
0:28:00 We don’t know what is actually being spent and where it’s being spent.
0:28:05 And I think Ukraine is a great example of the fact that money isn’t everything.
0:28:13 You’ve got to be able to tactically deploy it well and spend it on the right things and use, for instance, drones in an operational manner.
0:28:15 Ukrainians have been very lean, but very successful.
0:28:17 So that’s something to keep in mind as well.
0:28:19 Well, let’s take a quick break.
0:28:20 So stay with us.
0:28:56 To me, it’s now funny to dress in a more kind of kinky way, because I think I’m more associated with like dungarees and smock tops.
0:28:59 It’s in a slightly more sexless, tomboyish vibe.
0:29:05 Find Fashion Neurosis on YouTube or wherever you get your podcasts.
0:29:08 Welcome back.
0:29:18 When you imagine the future, if you imagine flying around in a car-sized flying vessel, then much of the 21st century must have been very, very disappointing to you.
0:29:22 As flying cars, I mean, I watch Back to the Future.
0:29:25 I don’t know if you have, James, but they have proved still very much elusive.
0:29:28 That is until now, perhaps.
0:29:33 The company Yeheng, based in Guangzhou, China, says it has developed a flying air taxi.
0:29:36 It is battery-powered and completely autonomous.
0:29:39 It flies without a pilot inside.
0:29:47 Yeheng says it plans to deploy these unmanned EVTOLs, that stands for Electric Vertical Takeoff and Landing, it’s a mouthful,
0:29:51 between airports and some cities in China within three years.
0:29:58 And they say that flights will be offered cheap, only 200 to 300 yuan, or about the equivalent of 30 to 40 US dollars.
0:30:04 James, when I came across this story, thanks to you, I was very much surprised.
0:30:06 Is this for real or is it all hype?
0:30:08 Well, it’s definitely for real.
0:30:11 I’ve been following these guys for a few years, actually.
0:30:16 But I must say, Alice, when it comes to this kind of thing, I’m personally a complete wimp.
0:30:19 You know, I have a friend, for instance, who has a helicopter.
0:30:24 He’s been badgering me for years to get into it, and I’ve only ever caved in once.
0:30:27 I’m kind of terrified by these things, personally.
0:30:33 But I’m really interested in Yeheng and, as you say, the EVTOL.
0:30:36 It sort of looks a bit like a doodlebug, you know.
0:30:40 It’s got a small cabin, enough room for maybe two people.
0:30:45 And then it’s got these drone-like rotor blades that sort of spin round.
0:30:52 And the really scary aspect of these EVTOLs is that they’re autonomously driven.
0:30:53 So there is no pilot.
0:31:00 So you’re sitting there, and you’re completely at the mercy of the AI algorithm that takes
0:31:02 you from A to B.
0:31:06 And I must say, I would find that very scary indeed.
0:31:10 I have been in autonomously driven cars.
0:31:12 I was in one in Shenzhen last year.
0:31:16 I was slightly nervous about that, but it was totally fine.
0:31:23 Getting into an oversized drone and sitting in it and trusting this thing to take you from
0:31:27 A to B without crashing to me is a totally different kettle of fish.
0:31:37 But as you say, this has got a license now from the Chinese authorities, and they reckon that they’re going to be working commercially within about three years.
0:31:55 And given that these types of projections in China are always padded out, they normally happen quicker than is projected, I reckon, you know, we could be seeing these vehicles in use a couple of years from now, maybe in certain areas.
0:32:15 And I’m very interested to read that Morgan Stanley, the investment bank, reckons that the market for these vehicles, these EVTOLs, could reach about a trillion US dollars by 2040 and even nine trillion by 2050.
0:32:17 So obviously, Morgan Stanley is impressed.
0:32:21 They reckon that this is going to become a big part of the way we get around.
0:32:23 So maybe it will happen.
0:32:28 The last thing I’d say is that China’s clearly imbibed this.
0:32:34 They’ve clearly decided that this is going to be something that the future revolves around.
0:32:37 And they’ve come up with a name for this type of technology.
0:32:40 They call it the low altitude economy.
0:32:44 So maybe the low altitude economy is going to be a big deal.
0:32:54 Yeah, when I first saw the image of this, I just thought this looks like a giant version of a drone and something that I’d imagine Tom Cruise in Mission Impossible to sit into.
0:32:57 Hopefully that it doesn’t get tapped into by an enemy agent.
0:32:59 But it seems very futuristic.
0:33:07 And it points to the fact that I think people in China are so ready for tech adoption that I think a lot more daring when it comes to these newfangled technologies.
0:33:14 My, I guess, concern would be, as you go into different airspaces, what are going to be the rules of the road?
0:33:16 And how are you going to regulate this?
0:33:25 I think the government is happy for this to be another way in which Chinese manufacturing capacity can be exported to the rest of the world in the future.
0:33:34 But I think technology is moving, as often is the case, much more quickly than the regulation can keep up or even regulators can conceive of regulating it.
0:33:42 So it’s not clear to me how Chinese local governments or the central government will think about regulating this space when it really becomes viable.
0:33:50 But I was reading that one of these taxi vehicles that Ihang is rolling at can fly over 100 miles on a single charge.
0:33:56 And it’s taken a cumulative 40,000 flights in 19 countries to date.
0:34:04 So it seems viable for now, but it’s going to be interesting to see how this unveils in China as, you know, adoption becomes more widespread.
0:34:09 But I haven’t seen anything, I don’t know if you have, James, in the U.S. context that’s comparable.
0:34:13 I don’t think they have truly autonomous flying cars.
0:34:13 Have you heard of this?
0:34:15 Yeah, this is what I was just about to say.
0:34:20 I spent a bit of time Googling various countries in Europe and the U.S.
0:34:26 to see whether or not they’ve got a licensing process for these EVTOLs.
0:34:27 And I couldn’t find any.
0:34:38 But the fact, as you mentioned, that Ihang has had flights in 19 different countries to date suggests to me that they’re trying to convince the authorities,
0:34:47 no doubt in Europe and the U.S. and elsewhere, that this is a viable technology, that these flying vehicles are not just going to drop from the sky.
0:34:55 And so maybe they will prevail in certain areas and maybe they’ll be licensed in other countries as well.
0:34:59 I guess it’s all a matter of safety, really.
0:35:04 If Ihang can prove that these are safe, then, well, why not, you know?
0:35:08 Yeah, this is definitely going to change the way that we move around.
0:35:16 I wonder what the first use cases will be, if it’s people doing this for fun or if they’re actually using it to commute or if they’re using it to send packages.
0:35:20 I think it’ll be really interesting to see how they quickly commercialize this.
0:35:22 And so definitely watch this space.
0:35:27 But at least I think they should change the name because it’s a mouthful, E-V-T-O-L, as an acronym.
0:35:29 So we’re going to have to find a different one.
0:35:31 You’re definitely right there.
0:35:33 Okay, James, it is prediction time.
0:35:37 What’s your prediction for the future as you look into your crystal ball?
0:35:41 Okay, well, I’m going to stay with the low-altitude economy.
0:35:45 I’m not talking about these flying taxis.
0:35:57 I’m talking now about drones because the other thing that’s happening in China in the low-altitude economy is that the drone delivery market is really taking off.
0:36:09 And it looks like this year, maybe there could be more than 5 million packages delivered by drone in China.
0:36:14 That would be up from 2.7 million packages delivered last year.
0:36:25 The important thing about this is that, as I’m sure you’re aware, Alice, the key thing about delivering packages is that it’s quite costly in what they call the last mile.
0:36:38 So, you know, the last stage of the delivery process where the delivery person has to find your house and then post your package through your letterbox, or if you’re not there or you don’t have a letterbox, do something else.
0:36:41 That’s the costly bit of delivery.
0:36:49 So having a drone that can literally come to your front door and just drop the package on your doorstep is going to be a lot cheaper.
0:36:56 And that’s why we’re seeing such a big uptick in the drone delivery market in China.
0:37:02 So my prediction is 5 million packages delivered this year in China by drone.
0:37:04 It sounds like we’re going to have a lot of drone overcapacity.
0:37:06 There’s going to be drones everywhere.
0:37:16 So, James, my prediction is more left field, and it’s centered in France, where the French fraud watchdog has suspended Sheen from operating in France.
0:37:20 Now, Sheen, as many will recall, is China’s fast fashion retailer platform.
0:37:30 And apparently, it seems that on the Sheen platform, there were illegal sales of these sex dolls that resembled children.
0:37:35 These listings have been taken off of Sheen, as Sheen has confirmed this.
0:37:44 But I think this is symptomatic of a larger issue that is rising between the EU and China, which centers around trade and technology.
0:37:50 Whereas in previous episodes, we discussed a great deal of tension between Washington and Beijing.
0:37:57 I think what we are starting to see is more storm clouds emerging between Brussels and China.
0:38:08 My own sense in talking to people from Europe is that they were very unhappy with the way in which China had basically used the rarest export controls, even though China has since walked that back.
0:38:15 And I think that that move engendered a great deal of mistrust from the policymakers in Europe.
0:38:24 So my sense is that there’s going to be more investigations in the next few months on Chinese goods, not just the ones that they’ve listed, for instance, on Chinese tires.
0:38:34 And there may be more, I think, sanctions on Chinese companies in Europe, in addition to what we’re seeing with Nixperia, for instance, the Chinese semiconductor company based in the Netherlands.
0:38:43 This, I think, is a tide that is ultimately symptomatic of worsening trade relations between Europe and China.
0:38:44 A very interesting call.
0:38:46 I have a hunch that you’re right about that.
0:38:48 I think that Europe may well get a bit tougher.
0:38:49 All right.
0:38:50 That’s all for this episode.
0:38:53 Thank you so much for listening to China Decode.
0:38:55 This is a production of Prof G Media.
0:38:58 Our producer is David Toledo.
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