1 00:00:00,280 --> 00:00:07,600 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. 2 00:00:08,240 --> 00:00:10,960 Speaker 2: I'm Sarah Holder, host of The Big Take, and I'm 3 00:00:11,039 --> 00:00:15,680 Speaker 2: Jennifer Zabasaja, host of Bloomberg's Next Africa podcast. Today, we're 4 00:00:15,680 --> 00:00:18,880 Speaker 2: bringing you a story reported by our colleagues and newsrooms 5 00:00:18,880 --> 00:00:20,560 Speaker 2: throughout Africa and Asia. 6 00:00:20,960 --> 00:00:23,800 Speaker 3: It's about how the AI arms race is playing out 7 00:00:23,880 --> 00:00:27,640 Speaker 3: in Africa as Chinese AI developers try to break into 8 00:00:27,680 --> 00:00:33,000 Speaker 3: the burgeoning Africa tech scene. Earlier this year, a group 9 00:00:33,040 --> 00:00:36,760 Speaker 3: of tech executives from all over Africa got together at 10 00:00:36,760 --> 00:00:40,760 Speaker 3: the headquarters of a Nairobi based startup to consider a 11 00:00:40,800 --> 00:00:41,880 Speaker 3: business proposition. 12 00:00:42,280 --> 00:00:46,640 Speaker 1: So it was an early breakfast meeting and it had 13 00:00:47,000 --> 00:00:50,760 Speaker 1: a whole lot of African startup founders. And then there 14 00:00:50,800 --> 00:00:53,800 Speaker 1: was also a group from Huawei with one of the 15 00:00:53,880 --> 00:00:58,800 Speaker 1: top exigs that sort of runs sub foreign Africa's cloud services. 16 00:00:59,120 --> 00:01:03,080 Speaker 3: Loney princelu is a senior Africa reporter for Bloomberg based 17 00:01:03,120 --> 00:01:07,039 Speaker 3: in Johannesburg, and she says that Huawei Cloud Exac was 18 00:01:07,040 --> 00:01:11,600 Speaker 3: there to talk about one buzzy new company. In particular, he. 19 00:01:11,520 --> 00:01:14,920 Speaker 1: Came in with quite a strong pitch for deep Sick, saying, 20 00:01:15,240 --> 00:01:17,759 Speaker 1: you know, deeptic is so hot. That was literally his words, 21 00:01:17,760 --> 00:01:20,160 Speaker 1: deeptic is so hot. Now I want to talk about 22 00:01:20,240 --> 00:01:20,960 Speaker 1: anything else. 23 00:01:21,560 --> 00:01:25,480 Speaker 2: Deep Sik the Chinese AI platform that launched a breakthrough 24 00:01:25,600 --> 00:01:30,680 Speaker 2: reasoning model in January twenty twenty five, shocking its competition. 25 00:01:31,160 --> 00:01:34,000 Speaker 1: Deep Seek. Where did this one come from? 26 00:01:34,040 --> 00:01:37,160 Speaker 4: The cheaper ALI model from Chinese starts up deep Seek 27 00:01:37,240 --> 00:01:40,360 Speaker 4: could fraten us big tech. Deep Siki is a Chinese 28 00:01:40,400 --> 00:01:44,440 Speaker 4: startup that's producing these large language models that offer very 29 00:01:44,480 --> 00:01:47,119 Speaker 4: high performance at a relatively low cost. 30 00:01:47,480 --> 00:01:51,040 Speaker 2: That's Helen Yambura, Bloomberg's East Africa bureau chief. 31 00:01:51,360 --> 00:01:55,240 Speaker 4: Deep Siki is using Wawei hardware in the ecosystem, both 32 00:01:55,320 --> 00:01:59,880 Speaker 4: cheaps and cloud, so from a political perspective, Huawei is 33 00:02:00,040 --> 00:02:04,840 Speaker 4: promoting domestic AI tools that are running on domestic hardware. 34 00:02:05,120 --> 00:02:08,480 Speaker 2: Huawei and deep Seek's parent company, high Flyer have been 35 00:02:08,520 --> 00:02:12,440 Speaker 2: collaborating since mid twenty twenty three. In addition to hosting 36 00:02:12,480 --> 00:02:15,640 Speaker 2: deep Seek on its cloud, Huawei has also started selling 37 00:02:15,680 --> 00:02:19,280 Speaker 2: its storage and computing services in a bundle with access 38 00:02:19,320 --> 00:02:23,200 Speaker 2: to deep Seek's large language model. So Huawei's exec wasn't 39 00:02:23,280 --> 00:02:26,240 Speaker 2: just hyping up how hot deep seek is. He was 40 00:02:26,280 --> 00:02:30,040 Speaker 2: trying to pitch these African startups on using deep Seek's 41 00:02:30,040 --> 00:02:34,840 Speaker 2: AI platform and accessing it through Huawei's cloud servers, and 42 00:02:34,880 --> 00:02:37,040 Speaker 2: he presented a pretty compelling offer. 43 00:02:38,520 --> 00:02:42,480 Speaker 1: Basically, if you are going onto Huawei Cloud instead of 44 00:02:42,520 --> 00:02:45,639 Speaker 1: going directly onto deep Seek every day, you get two 45 00:02:45,760 --> 00:02:49,600 Speaker 1: million tokens free. So that's sort of unheard up and 46 00:02:50,120 --> 00:02:51,480 Speaker 1: then a crack pleaser. 47 00:02:52,000 --> 00:02:54,919 Speaker 2: Tokens are the unit that deep Seek uses to bill 48 00:02:55,040 --> 00:02:58,760 Speaker 2: for its services. Two million free tokens can get you 49 00:02:58,840 --> 00:03:01,840 Speaker 2: a lot of deep Seak computing power. According to the 50 00:03:01,919 --> 00:03:05,680 Speaker 2: Huawei presentation, they would cover about three thousand pages of 51 00:03:05,760 --> 00:03:08,240 Speaker 2: new content generated by deep Seek's model. 52 00:03:08,600 --> 00:03:12,560 Speaker 3: Huawei is offering incentives like this to African tech companies 53 00:03:12,639 --> 00:03:15,840 Speaker 3: because they stand to gain a lot too. They're trying 54 00:03:15,880 --> 00:03:19,520 Speaker 3: to establish a crucial foothold on the continent early in 55 00:03:19,560 --> 00:03:21,160 Speaker 3: the AI race, and. 56 00:03:21,160 --> 00:03:23,960 Speaker 2: Some critics worry that deep Seek and Huawei's bet on 57 00:03:24,080 --> 00:03:29,920 Speaker 2: African AI infrastructure could have complex long term consequences, including 58 00:03:30,160 --> 00:03:38,160 Speaker 2: for data privacy. This is the Big Take from Bloomberg News. 59 00:03:38,360 --> 00:03:39,760 Speaker 2: I'm Sarah Holder. 60 00:03:39,880 --> 00:03:42,600 Speaker 3: And this is a special co production of The Big 61 00:03:42,640 --> 00:03:46,640 Speaker 3: Take and Bloomberg's Next Africa Podcast. I'm Jennifer's Abasaga. 62 00:03:46,920 --> 00:03:50,000 Speaker 2: Today on the show, Deep Seek and Huawei's push to 63 00:03:50,120 --> 00:03:53,560 Speaker 2: dominate the artificial intelligence market in Africa. 64 00:03:53,640 --> 00:03:56,360 Speaker 3: What it could mean for the global AI race, the 65 00:03:56,360 --> 00:04:00,320 Speaker 3: soft power balanced between the US and China, and as 66 00:04:00,360 --> 00:04:13,200 Speaker 3: efforts to influence Africa's development, industry and innovation. Africa's digital 67 00:04:13,240 --> 00:04:16,560 Speaker 3: economy is valued at about one hundred and eighty billion 68 00:04:16,600 --> 00:04:20,600 Speaker 3: dollars today, but by twenty fifty it's expected to swell 69 00:04:20,640 --> 00:04:23,400 Speaker 3: to seven hundred and twelve billion dollars. 70 00:04:25,920 --> 00:04:29,200 Speaker 2: For the past few years, while American AI companies have 71 00:04:29,320 --> 00:04:34,520 Speaker 2: experienced record levels of growth, African companies and African users 72 00:04:34,920 --> 00:04:38,680 Speaker 2: have been largely left behind. One reason for this is 73 00:04:38,720 --> 00:04:42,000 Speaker 2: that access to computing resources plays a big role in 74 00:04:42,080 --> 00:04:45,640 Speaker 2: African startups being able to develop their own AI models 75 00:04:45,760 --> 00:04:49,520 Speaker 2: and attract funding. The bulk of the eight hundred million 76 00:04:49,600 --> 00:04:53,599 Speaker 2: dollars African AI startups attracted last year went to places 77 00:04:53,640 --> 00:04:58,240 Speaker 2: on the continent that have more AI capabilities, like South Africa, Kenya, 78 00:04:58,360 --> 00:04:59,640 Speaker 2: Tunisia and Egypt. 79 00:05:00,200 --> 00:05:03,560 Speaker 3: And Huawei's pitch for deep Seek in that Nairobi conference 80 00:05:03,640 --> 00:05:07,120 Speaker 3: room catered to the broad spectrum of AI use cases 81 00:05:07,279 --> 00:05:11,799 Speaker 3: that African entities could need, from free options for smaller 82 00:05:11,839 --> 00:05:16,440 Speaker 3: startups to private cloud systems for governments to more compute 83 00:05:16,480 --> 00:05:18,839 Speaker 3: intensive options for app developers. 84 00:05:19,279 --> 00:05:22,640 Speaker 2: Bloomberg's Lonely Prince Lou says that in Africa, deepseek is 85 00:05:22,680 --> 00:05:25,800 Speaker 2: trying to position itself as a more flexible option than 86 00:05:25,800 --> 00:05:27,120 Speaker 2: its Western competitors. 87 00:05:27,920 --> 00:05:31,400 Speaker 1: When it comes to Google, Gemini and Rita Lama, those 88 00:05:31,440 --> 00:05:34,920 Speaker 1: waste and models, you have quite a lot of restrictions, 89 00:05:35,360 --> 00:05:37,680 Speaker 1: licensing restrictions and take restrictions. 90 00:05:38,000 --> 00:05:42,120 Speaker 3: AI offerings from US companies tend to be harder to customize. 91 00:05:42,240 --> 00:05:47,000 Speaker 3: They're largely not open source, but deep seek is that 92 00:05:47,200 --> 00:05:50,880 Speaker 3: means users can access the underlying code and modify the 93 00:05:50,920 --> 00:05:54,480 Speaker 3: software to suit their needs for no additional charge. 94 00:05:54,760 --> 00:05:58,919 Speaker 1: Something like that just suits the African environment much better. 95 00:06:00,000 --> 00:06:03,400 Speaker 1: Always wants the large language models, sometimes you want a 96 00:06:03,400 --> 00:06:06,640 Speaker 1: small language model for the types of adaptations that you 97 00:06:06,680 --> 00:06:07,039 Speaker 1: want to do. 98 00:06:07,120 --> 00:06:12,159 Speaker 2: In terms of AI, one reason African startups might want 99 00:06:12,160 --> 00:06:17,120 Speaker 2: a more customizable model is because many USAI models weren't 100 00:06:17,160 --> 00:06:20,599 Speaker 2: trained on African dialects and they often fail to pick 101 00:06:20,680 --> 00:06:25,080 Speaker 2: up on cultural nuances. Using them on unfamiliar words and 102 00:06:25,120 --> 00:06:29,320 Speaker 2: situations can be expensive. They require more tokens to perform 103 00:06:29,400 --> 00:06:33,560 Speaker 2: those tasks. This all makes deep Seek's open source model 104 00:06:33,680 --> 00:06:37,640 Speaker 2: more appealing, and using the model is also much cheaper. 105 00:06:37,920 --> 00:06:42,160 Speaker 1: We spoke to one sort of in Nigeria called Equalize AI, 106 00:06:42,279 --> 00:06:44,760 Speaker 1: and so basically what deep seek is charging is twenty 107 00:06:45,160 --> 00:06:48,880 Speaker 1: seven usints to press a million words for a query, 108 00:06:49,279 --> 00:06:52,039 Speaker 1: and then a dollar a team for a million words. 109 00:06:52,120 --> 00:06:54,719 Speaker 1: In terms of the response that it generates. 110 00:06:54,720 --> 00:06:58,320 Speaker 2: That's a lot less than Chat GPT, which costs more 111 00:06:58,400 --> 00:07:01,400 Speaker 2: like five dollars for a million words of processing and 112 00:07:01,520 --> 00:07:04,080 Speaker 2: fifteen dollars for a million words generated. 113 00:07:04,600 --> 00:07:08,400 Speaker 1: That is two thousand and seven hundred dollars per month 114 00:07:08,520 --> 00:07:11,440 Speaker 1: if it us deep seek, vers is twelve thousand, five 115 00:07:11,520 --> 00:07:15,480 Speaker 1: hundred dollars if it uses chat GPT four for the 116 00:07:15,520 --> 00:07:18,160 Speaker 1: same toxic So it's a massive difference. 117 00:07:18,520 --> 00:07:21,920 Speaker 2: Deep Sex's platform is four and a half times cheaper 118 00:07:22,040 --> 00:07:26,520 Speaker 2: for Equalized AI to use, which raises the obvious question. 119 00:07:27,480 --> 00:07:31,480 Speaker 3: What's the financial appeal for deep sek. What are they 120 00:07:31,520 --> 00:07:35,360 Speaker 3: seeing financially when it comes to some of these rois. 121 00:07:35,680 --> 00:07:38,760 Speaker 1: Look, they're still charging, so they must be playing more 122 00:07:38,800 --> 00:07:42,640 Speaker 1: of a volumes game. And in terms of volumes, that 123 00:07:42,760 --> 00:07:46,000 Speaker 1: is what Africa can offer. We have a massive amount 124 00:07:46,000 --> 00:07:49,040 Speaker 1: of young people on the continent. They're all interested in 125 00:07:49,080 --> 00:07:52,320 Speaker 1: what technology can do for them. There's a lot of 126 00:07:52,360 --> 00:07:57,680 Speaker 1: restrictions in terms of actual traditional infrastructure. So technology is 127 00:07:57,680 --> 00:08:01,240 Speaker 1: where everyone's sort of looking towards. So it's a longer game, 128 00:08:02,000 --> 00:08:04,840 Speaker 1: I think for deep Sick more than it is for 129 00:08:04,960 --> 00:08:08,200 Speaker 1: open Ai, who is running for profits. 130 00:08:08,320 --> 00:08:12,600 Speaker 2: Basically, open Ai didn't respond to a request for comment 131 00:08:12,680 --> 00:08:17,200 Speaker 2: on the story. Meanwhile, Deep Sik's numbers game seems to 132 00:08:17,240 --> 00:08:18,080 Speaker 2: be working. 133 00:08:18,280 --> 00:08:23,520 Speaker 1: When it comes to startups. Specifically, every African stortup we 134 00:08:23,560 --> 00:08:27,160 Speaker 1: spoke to prefer Deep Sick at this point when it 135 00:08:27,240 --> 00:08:32,040 Speaker 1: comes to training their models, adapting their models. So what 136 00:08:32,040 --> 00:08:34,800 Speaker 1: we're seeing on the ground is that they are definitely 137 00:08:34,960 --> 00:08:37,680 Speaker 1: numbers in favor for deep sic currently. 138 00:08:39,320 --> 00:08:42,760 Speaker 3: And Huawei isn't just pitching startups on deep Sek, they're 139 00:08:42,760 --> 00:08:46,120 Speaker 3: also trying to get African governments to adopt their platform. 140 00:08:46,520 --> 00:08:48,079 Speaker 3: Here's Bloomberg Talent Yamburra. 141 00:08:48,640 --> 00:08:52,480 Speaker 4: We don't have credible evidence that African governments are formally 142 00:08:52,600 --> 00:08:57,840 Speaker 4: adopting deep sick tools for their public service and official news, 143 00:08:58,280 --> 00:09:02,240 Speaker 4: but Huawei is pushing what it calls its National Government 144 00:09:02,360 --> 00:09:06,400 Speaker 4: Cloud Solution in Southern Africa. So this is platforms to 145 00:09:06,440 --> 00:09:13,080 Speaker 4: support public services and cloud infrastructure and digitization of government services. 146 00:09:13,559 --> 00:09:16,280 Speaker 3: If deep seek were to expand into the government space. 147 00:09:16,559 --> 00:09:20,040 Speaker 3: It could be handling more sensitive data, and critics at 148 00:09:20,120 --> 00:09:23,719 Speaker 3: universities and legal firms have raised concerns about how that 149 00:09:23,800 --> 00:09:26,680 Speaker 3: data is being gathered and how it could be used. 150 00:09:27,200 --> 00:09:30,760 Speaker 3: A Wall Street Journal investigation found that Huawei technicians have 151 00:09:30,840 --> 00:09:35,840 Speaker 3: provided African governments with information on their political opponents. For example, 152 00:09:36,760 --> 00:09:40,400 Speaker 3: Huawei and the governments, though deny the claims, Deep. 153 00:09:40,240 --> 00:09:43,600 Speaker 2: Seak has already been blocked in several European countries over 154 00:09:43,720 --> 00:09:47,160 Speaker 2: data privacy concerns and what regulators say is a lack 155 00:09:47,160 --> 00:09:51,240 Speaker 2: of transparency about the relationship between the Chinese government and 156 00:09:51,280 --> 00:09:53,199 Speaker 2: companies like Huawei and deep Seek. 157 00:09:54,280 --> 00:09:57,360 Speaker 3: One of the central concerns is that the Chinese government 158 00:09:57,480 --> 00:10:01,360 Speaker 3: could gain access to deep seek data store on Chinese servers. 159 00:10:01,840 --> 00:10:05,920 Speaker 3: Italy's Data Protection Authority asked for information on deep Seek's 160 00:10:05,960 --> 00:10:10,720 Speaker 3: data collection, use and storage policies, which deep Seek did 161 00:10:10,760 --> 00:10:15,080 Speaker 3: not produce. German regulators asked for evidence that German user 162 00:10:15,200 --> 00:10:19,040 Speaker 3: data sent to China was protected in line with European standards, 163 00:10:19,440 --> 00:10:21,880 Speaker 3: which Deep Seek was unable to provide. 164 00:10:22,200 --> 00:10:25,840 Speaker 2: When asked by Bloomberg about data privacy concerns, Deep Seek 165 00:10:25,880 --> 00:10:31,800 Speaker 2: and Huawei both declined to comment. Huawei's efforts in Africa 166 00:10:31,880 --> 00:10:34,720 Speaker 2: are aligned with a similar playbook that the Chinese government 167 00:10:34,760 --> 00:10:37,280 Speaker 2: has used for over a decade as a means of 168 00:10:37,320 --> 00:10:41,440 Speaker 2: gaining soft power after the break what that approach could 169 00:10:41,440 --> 00:10:45,360 Speaker 2: mean for China's influence and its position in the global 170 00:10:45,400 --> 00:10:46,120 Speaker 2: AI race. 171 00:10:56,440 --> 00:10:59,360 Speaker 3: For over a decade, the Chinese government has made a 172 00:10:59,440 --> 00:11:04,760 Speaker 3: concerted effort to invest in foreign infrastructure, increasing its influence 173 00:11:04,840 --> 00:11:09,280 Speaker 3: in developing countries. It's a strategy known as the Belt 174 00:11:09,320 --> 00:11:10,440 Speaker 3: and Road initiative. 175 00:11:11,320 --> 00:11:15,280 Speaker 4: China is going to the developing world, especially in Africa, 176 00:11:15,760 --> 00:11:20,800 Speaker 4: and you know, extending soft power through building infrastructure, but 177 00:11:21,040 --> 00:11:25,000 Speaker 4: using technology rather than you know, the hard airports and 178 00:11:25,080 --> 00:11:28,400 Speaker 4: ports and roads, Andre Luise, this now is you know, 179 00:11:28,480 --> 00:11:32,080 Speaker 4: the software to be ahead of the yules. 180 00:11:33,200 --> 00:11:36,800 Speaker 2: This new AI software initiative isn't technically a Belt and 181 00:11:36,920 --> 00:11:40,679 Speaker 2: Road project, but it takes a similar approach, and it's 182 00:11:40,720 --> 00:11:43,320 Speaker 2: one the Chinese government has also used in the past 183 00:11:43,360 --> 00:11:46,840 Speaker 2: to expand the reach of Chinese phone companies like Huawei 184 00:11:46,880 --> 00:11:48,880 Speaker 2: and Zte into Africa. 185 00:11:49,440 --> 00:11:53,080 Speaker 4: The Chinese companies Juawi and Zte were not the first 186 00:11:53,160 --> 00:11:57,400 Speaker 4: on the continent, but these companies came with a cheaper, 187 00:11:57,480 --> 00:12:01,080 Speaker 4: more cost effective solution, so it's the same thing that 188 00:12:01,120 --> 00:12:02,640 Speaker 4: we're seeing with Deep Seek. 189 00:12:02,800 --> 00:12:06,960 Speaker 3: Belt and road projects in Kenya, Ethiopia, and Djibouti gave 190 00:12:07,080 --> 00:12:12,240 Speaker 3: China economic leverage over these developing countries. Chinese companies and 191 00:12:12,320 --> 00:12:16,000 Speaker 3: the Chinese government offered cheap loans in order to roll 192 00:12:16,000 --> 00:12:22,040 Speaker 3: out infrastructure and equipment across the continent to cement their position. Ultimately, 193 00:12:22,520 --> 00:12:26,040 Speaker 3: those nations had to majorly restructure their debt in order 194 00:12:26,120 --> 00:12:27,439 Speaker 3: to repay their loans. 195 00:12:28,080 --> 00:12:30,800 Speaker 2: Other nations who weren't able to pay back their loans, 196 00:12:30,840 --> 00:12:33,800 Speaker 2: like Sri Lanka, have had to turn over control of 197 00:12:33,840 --> 00:12:37,480 Speaker 2: their infrastructure to China. When it comes to Huawei and 198 00:12:37,520 --> 00:12:41,360 Speaker 2: Deep Seek, the leverage these companies could have is access 199 00:12:41,440 --> 00:12:42,199 Speaker 2: to information. 200 00:12:42,960 --> 00:12:46,640 Speaker 4: It's all about capturing the vast amount of data that 201 00:12:46,760 --> 00:12:50,560 Speaker 4: will shape AI in the future. Some critics are worried 202 00:12:50,880 --> 00:12:54,360 Speaker 4: that this will elcho that built and road where we 203 00:12:54,520 --> 00:12:58,160 Speaker 4: saw China forcing some poor countries to handle over critical 204 00:12:58,160 --> 00:13:03,320 Speaker 4: infrastructure to pay for all those projects. So we don't 205 00:13:03,360 --> 00:13:06,400 Speaker 4: know how these might pan out for African companies and 206 00:13:06,480 --> 00:13:09,160 Speaker 4: governments in future in terms of cost. 207 00:13:10,520 --> 00:13:13,080 Speaker 2: And there are other side effects that come from relying 208 00:13:13,160 --> 00:13:17,960 Speaker 2: too heavily on one country's digital infrastructure. For example, for 209 00:13:18,040 --> 00:13:21,400 Speaker 2: the past two years to prevent cheating during China's national 210 00:13:21,520 --> 00:13:26,680 Speaker 2: university entrance exams. China has restricted certain technical capabilities of 211 00:13:26,720 --> 00:13:28,600 Speaker 2: domestic tech companies. 212 00:13:28,240 --> 00:13:32,600 Speaker 1: Ali Baba, Black Dance, Taint, Saint and Deepseek, whose service 213 00:13:32,600 --> 00:13:35,640 Speaker 1: are all located in China. They disabled things like the 214 00:13:35,679 --> 00:13:39,680 Speaker 1: image recognition and the instant Q and A features on 215 00:13:40,040 --> 00:13:43,400 Speaker 1: sort of consumer facing products to prevent cheating. 216 00:13:43,720 --> 00:13:46,719 Speaker 2: But the move didn't just impact Chinese students. 217 00:13:47,000 --> 00:13:50,680 Speaker 1: We also saw then in Lagos in Nairobi who all 218 00:13:50,720 --> 00:13:54,920 Speaker 1: experienced slowdowns in terms of service interruptions and you can't 219 00:13:54,960 --> 00:13:56,120 Speaker 1: do anything about that. 220 00:13:56,880 --> 00:14:01,200 Speaker 2: And then there are the privacy concerns. Most big Western 221 00:14:01,240 --> 00:14:04,840 Speaker 2: AI models are supposed to comply with European laws governing 222 00:14:04,880 --> 00:14:09,959 Speaker 2: transparency around data collection and processing, but deep Seek's Chapot 223 00:14:10,080 --> 00:14:14,480 Speaker 2: does not. Instead, it typically stores user data on servers 224 00:14:14,520 --> 00:14:18,480 Speaker 2: in China, which under Chinese law, could be accessed by 225 00:14:18,480 --> 00:14:22,440 Speaker 2: the Chinese government. And while several European countries have taken 226 00:14:22,480 --> 00:14:26,640 Speaker 2: steps to curb deep Seek adoption, African countries have not. 227 00:14:27,320 --> 00:14:30,320 Speaker 4: I think most countries are really you know, at the 228 00:14:30,360 --> 00:14:35,440 Speaker 4: starting stage of developing the regulation and so on, so 229 00:14:35,560 --> 00:14:39,600 Speaker 4: there's a lot of adoption without the legal background, without 230 00:14:39,640 --> 00:14:46,280 Speaker 4: the regulatory backbone to cover that, so the technology has 231 00:14:46,320 --> 00:14:53,360 Speaker 4: sort of front run the regulation, which might be a problem. 232 00:14:53,640 --> 00:14:57,960 Speaker 3: Then there's the looming geopolitical backdrop to this. Bloomberg's Helen 233 00:14:58,040 --> 00:15:01,680 Speaker 3: Yamburra told me that if Africa nations and tech companies 234 00:15:01,800 --> 00:15:05,480 Speaker 3: start relying too heavily on Chinese tech, they could get 235 00:15:05,520 --> 00:15:08,560 Speaker 3: caught in the crossfires of the US China trade war. 236 00:15:08,880 --> 00:15:12,360 Speaker 2: For instance, if the US government tries to disrupt China's 237 00:15:12,440 --> 00:15:17,440 Speaker 2: AI capabilities by limiting access to chips or ratcheting up terrace, 238 00:15:18,080 --> 00:15:21,440 Speaker 2: that could also impact Africa's AI capabilities. 239 00:15:22,000 --> 00:15:24,320 Speaker 4: The sticks are just really too high for a single 240 00:15:24,360 --> 00:15:27,560 Speaker 4: country to rely on just one country, whether it's the 241 00:15:27,720 --> 00:15:28,720 Speaker 4: US or China. 242 00:15:29,920 --> 00:15:33,400 Speaker 2: The US has tried to pursue its own tech infrastructure 243 00:15:33,440 --> 00:15:35,560 Speaker 2: projects in Africa in the past. 244 00:15:35,760 --> 00:15:39,400 Speaker 1: And so big deals being announced in thin specifically, there 245 00:15:39,480 --> 00:15:42,920 Speaker 1: was a big AI data center being announced of more 246 00:15:42,960 --> 00:15:44,320 Speaker 1: than a billion dollars. 247 00:15:44,480 --> 00:15:48,160 Speaker 2: But under the Trump administration, those efforts have stalled. 248 00:15:48,400 --> 00:15:51,560 Speaker 1: And that's opened the way again for China. China, as 249 00:15:51,560 --> 00:15:54,120 Speaker 1: we said, has been here for a long time. That've 250 00:15:54,160 --> 00:15:57,440 Speaker 1: been in wasting for twenty years, so that they do 251 00:15:57,600 --> 00:15:59,800 Speaker 1: own a lot of the equipment in our five G 252 00:16:00,720 --> 00:16:05,080 Speaker 1: in our fiber, in our data centers in the US 253 00:16:05,160 --> 00:16:08,240 Speaker 1: companies that are here. A lot of them sort of 254 00:16:08,280 --> 00:16:12,360 Speaker 1: have set up shop in South Africa and some in 255 00:16:12,520 --> 00:16:15,160 Speaker 1: Kenya and some in Nigeria, but they don't really advance 256 00:16:15,520 --> 00:16:17,960 Speaker 1: to other African countries. And as we know, there's fifty 257 00:16:17,960 --> 00:16:21,440 Speaker 1: four of them. So China has really played the game 258 00:16:21,480 --> 00:16:22,640 Speaker 1: also in smaller countries. 259 00:16:24,960 --> 00:16:28,240 Speaker 3: And in part because of that dynamic, the expansion of 260 00:16:28,320 --> 00:16:31,480 Speaker 3: Chinese AI tools in Africa hasn't been met with the 261 00:16:31,520 --> 00:16:35,240 Speaker 3: same suspicion as it has in European countries or the 262 00:16:35,360 --> 00:16:40,080 Speaker 3: United States, because Loni says, many people in Africa are 263 00:16:40,320 --> 00:16:42,600 Speaker 3: just as skeptical of US tech. 264 00:16:43,280 --> 00:16:48,040 Speaker 1: In Africa, people don't always mistrust the East versus the West. 265 00:16:48,360 --> 00:16:53,320 Speaker 1: Many also distrust the West in terms of privacy and 266 00:16:53,840 --> 00:16:57,840 Speaker 1: you know, take and all of that. So African general 267 00:16:57,880 --> 00:17:02,160 Speaker 1: has a better relationship with China than a europe for instance. 268 00:17:02,720 --> 00:17:06,600 Speaker 1: But yeah, I would just I would like to just 269 00:17:06,680 --> 00:17:10,120 Speaker 1: see whether this adoption of deep seek in the sort 270 00:17:10,160 --> 00:17:11,720 Speaker 1: of space continues. 271 00:17:12,359 --> 00:17:15,720 Speaker 3: For now, Alen says she's watching to see how Africa's 272 00:17:15,800 --> 00:17:17,520 Speaker 3: AI industry develops. 273 00:17:17,840 --> 00:17:20,520 Speaker 4: What will be interesting is to see whether Africa can 274 00:17:20,880 --> 00:17:24,600 Speaker 4: come up with its own, you know, homegrown AI industry. 275 00:17:24,880 --> 00:17:28,000 Speaker 4: There's very many hurdles to this. It doesn't have the 276 00:17:28,119 --> 00:17:30,600 Speaker 4: money that you know, China or the US will throw 277 00:17:30,720 --> 00:17:34,840 Speaker 4: at AI. It also doesn't have the skilled labor to 278 00:17:34,960 --> 00:17:38,600 Speaker 4: do this or the infrastructure. But it would be good 279 00:17:38,640 --> 00:17:41,679 Speaker 4: for Africa to be at least to try for some 280 00:17:41,880 --> 00:17:43,720 Speaker 4: independence on this front. 281 00:17:48,680 --> 00:17:50,679 Speaker 2: This is the Big Take from Bloomberg News. 282 00:17:50,920 --> 00:17:54,800 Speaker 3: I'm Sarah Holder and I'm Jennifer's Abisada with Next to Africa. 283 00:17:54,960 --> 00:17:58,399 Speaker 2: Follow The Next Africa podcast now and join them every 284 00:17:58,400 --> 00:18:03,320 Speaker 2: Friday on Apple, podcast, Spotify, iHeart, or wherever you listen. 285 00:18:03,720 --> 00:18:06,320 Speaker 3: To get more from The Big Take and unlimited access 286 00:18:06,400 --> 00:18:09,720 Speaker 3: to all of Bloomberg dot Com, subscribe today at Bloomberg 287 00:18:09,800 --> 00:18:12,240 Speaker 3: dot com slash podcast Offer. 288 00:18:12,560 --> 00:18:15,000 Speaker 2: If you liked this episode, make sure to follow and 289 00:18:15,080 --> 00:18:18,280 Speaker 2: review The Big Take or Next Africa wherever you listen 290 00:18:18,320 --> 00:18:21,040 Speaker 2: to podcasts. 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