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Annual capital spending by ten major global semiconductor companies is expected to grow 7% to USD 135 billion, the first rise in three years, driven by suppliers of advanced chips for the generative <a href="/industry/ai">artificial intelligence</a> boom, Nikkei research shows.
Six of the ten companies, including <a href="/company/tsmc">Taiwan Semiconductor Manufacturing Company</a> (TSMC), South Korea's SK Hynix, US-based Micron Technology, and China's Semiconductor Manufacturing International Corporation (SMIC), plan to spend more this fiscal year than in fiscal 2024.
TSMC, the world's largest chip foundry, plans to break ground on or start up plants in nine locations worldwide in 2025. Recent years have seen about three to five starts per year, mainly in Taiwan, but its fiscal 2025 plans extend to the US, Europe, and Japan. The company expects to spend USD 38 billion to USD 42 billion, up roughly 30% from a year earlier.
At its <a href="https://asia.nikkei.com/business/tech/semiconductors/tsmc-to-speed-up-construction-of-us-chip-plants-by-several-quarters">Arizona site</a>, TSMC plans to invest in expansion to mass produce cutting-edge chips. The company is also looking to start work on a German facility with an eye toward mass production in 2027. Construction of a second plant at its Kumamoto site in Japan is set to begin later this year.
TSMC boasts a commanding lead in cutting-edge chips for AI processing, both in performance and yield, helping it win orders from chip designers <a href="/company/nvidia">Nvidia</a> and Advanced Micro Devices (AMD). In Taiwan, the chipmaker will invest in backend processing, a bottleneck for AI chip output.
In memory chips, Micron is investing around USD 14 billion in the fiscal year ending this month, a 70% jump on the year. This includes increased spending on high-bandwidth memory for generative AI. The company is installing extreme ultraviolet lithography equipment at its Hiroshima plant in Japan, aiming to start shipping next-generation memory in 2026.
SK Hynix, the top player in <a href="https://asia.nikkei.com/business/technology/memory-chip-business-to-rely-more-on-select-customers-sk-group-chairman">high-bandwidth memory</a>, is stepping up investment in its home market, lifting capital spending to a three-year high.
The chip market is expected to enjoy AI-driven growth for the next few years. AMD expects the AI semiconductor market to more than triple in size from 2025–2030, reaching USD 500 billion. By contrast, analysts at Deloitte Tohmatsu Consulting and elsewhere see growth in the smartphone market staying in the low single digits from 2025 onward.
Meanwhile, Intel, which has logged net losses for six straight quarters, is <a href="https://asia.nikkei.com/business/tech/semiconductors/intel-cancels-european-fabs-delays-us-plant-amid-turnaround">cutting capital spending</a> by roughly 30% in 2025 to around USD 18 billion, less than half of TSMC's figure. With rivals such as Nvidia leading in sales of AI chips, Intel is putting more money into research and development instead.
Samsung is moving forward with mass production of advanced chips at a <a href="https://asia.nikkei.com/business/technology/samsung-delaying-completion-of-us-chip-plant-due-to-lack-of-customers">new Texas facility</a>, but it is paring down investment in South Korea as the memory market slumps. A South Korean brokerage expects the company to spend about USD 35 billion in 2025, on par with last year.
Power semiconductors, which regulate power usage and had been expected to benefit from rising <a href="/industry/ev">electric vehicle</a> demand, are now in a supply glut as EV sales have slowed. Switzerland's STMicroelectronics plans to invest USD 2.0–2.3 billion this year, down from USD 2.5 billion in 2024. Germany's Infineon Technologies is reducing its spending for the fiscal year ending in September.
Some of the chip investment is being driven by countries' efforts to cultivate homegrown semiconductor supply chains in response to US-China tensions and American tariffs.
US-based GlobalFoundries said in June it would invest USD 16 billion in its home country over the medium to long term, USD 3 billion more than previously planned.
SMIC, China's biggest chip foundry, plans a record USD 7.5 billion in capital spending this year.
China as a whole is poised to invest over USD 100 billion in chipmaking equipment over the next three years, according to industry group SEMI. Having imported much of this gear from Japan and the Netherlands, China is now stepping up domestic procurement in response to US export restrictions.
In total, chipmakers plan to build 108 new plants from 2025 to 2027, 30% more than in 2021 to 2023, according to industry association SEMI.
"Companies will start competing for orders, and price competition will intensify," said SMIC co-CEO Zhao Haijun.
Tomoyuki Yatabe at the Mitsubishi Research Institute said oversupply is a possibility for some types of semiconductors.
Suppliers are starting to adjust. Chipmaking equipment manufacturer Tokyo Electron has downgraded its sales forecast for the six months through next March, citing changing investment plans among some customers.
"Semiconductor demand itself hasn't decreased," Tokyo Electron president Toshiki Kawai said. "As technological innovation progresses, we can anticipate further growth."
This article first appeared on <a href="https://asia.nikkei.com/business/tech/semiconductors/semiconductor-investment-rebounds-on-ai-but-not-everyone-is-winning">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing partnership with <a href="https://www.rwegrgdf5.eu.org/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/">Nikkei</a>.

Semiconductor investment rebounds on AI, but not everyone is winning

Artificial Intelligence

Deep Tech

Semiconductors

AI Infrastructure

Japan

South Korea

China

Europe

iQiyi has launched a <a href="https://aic.iq.com/">global competition</a> inviting content creators to explore the integration of <a href="/industry/ai">artificial intelligence</a> into short-form storytelling. Titled “Beyond Tools, Toward Teammates,” the initiative challenges participants to use designated generative models to produce films in which at least 70% of the content is AI-generated.
Participants can choose between Google’s Veo 3 and Volcano Engine’s Seedance 1.0 Pro, with both tools made available for free through partnerships with Google and <a href="/company/bytedance">ByteDance</a>. Submissions are open until September 30, with finalists to be announced in mid-October and winners in November 2025.
Films submitted must run under five minutes and will be judged on creativity, technical application, artistic execution, and thematic clarity. The selection process involves a preliminary review by iQiyi’s content operations team, followed by evaluation from a panel of academic and industry experts. The company has not yet disclosed the final list of judges.
The top prize is USD 3,000, with additional awards recognizing narrative strength and creative use of AI. Selected entries will also be featured on iQiyi’s international platforms.
In a statement, Liu Wenfeng, president of iQiyi’s infrastructure and intelligent content distribution business group, said the competition is “aimed at empowering creativity through technology and reshaping industries through innovation.”
The short film initiative builds on iQiyi’s broader efforts to embed AI into production workflows. In 2019, it introduced ZoomAI, a deep learning tool that restores and enhances archival footage to high resolution. According to the company, ZoomAI has significantly improved video processing efficiency and contributed to renewed viewership for classic titles.
Another proprietary tool, iQDubbing, has been in use since January 2021. It enables a single voice actor to dub multiple characters in different languages using AI-generated voice synthesis, streamlining post-production and reducing localization costs.
Both ZoomAI and iQDubbing predate the release of ChatGPT in 2022, which is widely regarded as the start of the current AI era, highlighting iQiyi’s early recognition of AI’s potential in creative production.
As generative AI gains traction across industries, iQiyi’s initiatives illustrate how such tools might reshape creative work. The company’s latest competition offers a public view into these developments, inviting creators worldwide to experiment with new forms of storytelling built in collaboration with machines.

iQiyi invites creators to co-direct with AI in global short film contest

Video

Creative

Content

Creator Economy

… srcset="https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Workout.jpg 1920w, https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Workout-720x480.jpg 720w, https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Workout-1024x683.jpg 1024w, https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Workout-768x512.jpg 768w, https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Workout-1536x1024.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /><figcaption id="caption-attachment-156563" class="wp-caption-text">Image source: Aeke.</figcaption></figure>
<h3>A coach that adapts with you</h3>
For users without an established workout routine, two questions matter: why exercise, and how to maintain consistency?
Even with clear goals like fat loss or muscle gain, staying on track is a challenge, especially for beginners.
As smart hardware becomes more standardized, companies must focus on the psychological factors that influence behavior. Aeke designed its system with emotional and motivational cues in mind.
The traditional personal training market suffers from quality inconsistencies. Many trainers are certified through short programs, resulting in variable experiences and limited trust.
To address this, Aeke tapped artificial intelligence to build its own coaching system that delivers end-to-end guidance: before, during, and after workouts.
Before a session begins, the AI coach conducts a full assessment using Aeke’s proprietary algorithm, evaluating users’ physical and health data to enable personalized programming.
Based on this input, the system generates custom training and nutrition plans, spanning 21 days to three months. These can focus on posture correction, fat loss, or dietary improvement.
Aeke has also created original course content in-house, produced by a team of trainers, yoga instructors, and nutritionists. Each lesson costs more than RMB 20,000 (USD 2,800) to produce and is included free with the device.
During workouts, the AI coach monitors form, flags errors via voice or text, and adjusts programming based on real-time performance data.
Localization is also key. Aeke provides distinct training systems for Asia Pacific and Western markets. Programs in Asia focus on progressive basics, while Western versions emphasize intensity and functional movement.
The user interface reflects these cultural differences. In China, where 90% of users are women aged 35–50, the app features a pastel palette and smooth navigation. In overseas markets, where men in the same age group dominate, Aeke opts for an industrial look and data-centric design. In Europe, dashboards highlight real-time metrics and visualized progress charts.
“Selling a product is only the beginning,” Loong said. “We aim for zero operational burden, and that means any user in any market should be able to unpack the product and get started, with no additional support or customization needed.”
<figure id="attachment_156564" aria-describedby="caption-attachment-156564" style="width: 1920px" class="wp-caption alignnone"><img loading="lazy" decoding="async" class="size-full wp-image-156564" src="https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Gym.jpg" alt="" width="1920" height="1280" srcset="https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Gym.jpg 1920w, https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Gym-720x480.jpg 720w, https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Gym-1024x683.jpg 1024w, https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Gym-768x512.jpg 768w, https://console.rwegrgdf5.eu.org/wp-content/uploads/2025/08/Aeke-Smart-Home-Gym-K1-Gym-1536x1024.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /><figcaption id="caption-attachment-156564" class="wp-caption-text">Image source: Aeke.</figcaption></figure>
AI also powers Aeke’s international expansion.
To enter new markets, the company localizes course content into languages like German, French, Japanese, and Arabic at a fraction of traditional costs. These experiments can be executed for a few hundred thousand RMB. Deeper localization only follows successful pilots, minimizing upfront risk.
36Kr has learned that Aeke is accelerating its global push, beginning with the US. From there, it plans to expand across North America and Europe, targeting overseas revenue of more than RMB 100 million (USD 14 million) by 2025.
In the competitive landscape of hardware startups, differentiation is essential. Aeke’s focus on a niche, fast-growing segment has helped it gain early traction, and could offer a playbook for other founders.
While these verticals may involve technical complexity, they remain overlooked by major players, providing fertile ground for innovation.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3362742683010820">article</a> was written by Huang Nan for 36Kr.

With smart fitness machines, Aeke finds profit where others saw no market

Consumer Economy

When most in the industry think of Unitree Robotics, they see a company focused on building robot hardware. But at the <a href="https://rwegrgdf5.eu.org/taking-the-pulse-of-chinas-humanoid-robot-push-at-wrc-2025">World Robot Conference (WRC)</a>, founder Wang Xingxing offered a different narrative.
During his keynote at WRC, Wang dedicated a large portion of his talk to large models, algorithms, and data. It was a shift that didn’t go unnoticed. His comments sparked debate, particularly his critique of the vision-language-action (VLA) framework driving many of today’s embodied robots.
Wang didn't mince words: he called the VLA architecture “relatively dumb.”
The main problem, in his view, is data, or the lack thereof. VLA models require vast, high-quality datasets to function effectively in the real world. While the scarcity of such data is widely acknowledged, many companies have pursued brute-force methods: gathering real-world robot data, generating simulation data, or building specialized data collection infrastructure.
Wang believes that emphasis is misplaced.
“People are paying too much attention to foundational data,” he said. “What we really need to improve is the architecture of embodied models. Right now, they are neither good enough nor unified enough.”
Historically, Wang has emphasized Unitree’s strength in hardware, not in building a robot “brain.” That messaging led many to assume the company wasn’t seriously investing in <a href="/industry/ai">artificial intelligence</a>.
But speaking to 36Kr during WRC, Wang clarified: “Our model team is actually quite large, it’s just smaller compared to the big AI firms.”
Still, Wang argued that size isn’t everything.
“It doesn’t take the most money or the biggest team to build world-class technology,” Wang said. “Innovation doesn’t only happen inside tech giants. Smaller teams can develop better models, though the pressure is much higher.”
Unitree’s model strategy remains flexible. While Wang is skeptical of current VLA approaches, he noted that Unitree is also experimenting with training AI on top of VLA frameworks. His core argument is that simply feeding more data into immature models is inefficient. A well-designed embodied model, he suggested, might perform well with only a limited amount of high-quality data.
The company’s bigger bet appears to be on video-driven models. Last year, Google introduced a world model trained on video, and Wang said Unitree was exploring similar ideas around the same time.
In this approach, a video generation model creates footage of a robot completing a task, such as tidying a room. That video is then used to guide a real robot in performing the same actions.
Wang believes this method may surpass VLA-based strategies in speed and convergence. Still, it comes with tradeoffs: generating high-resolution video is GPU-intensive.
Despite the technical demands, Wang sees a path forward. He envisions low-cost, large-scale, distributed computing clusters built specifically for <a href="/industry/robotics">robotics</a>. “If you’ve got 100 robots in a factory,” he said, “it makes sense to deploy a distributed server cluster inside the plant. The robots need low-latency communication anyway.”
Unitree’s robots, known for dancing at Lunar New Year galas and performing in high-octane battle scenes at this year’s World Artificial Intelligence Conference and WRC, have gained a reputation for showmanship rather than practical utility.
Meanwhile, newer entrants are focused on putting robots to work: tightening screws, folding laundry, making beds. That contrast has led some observers to dismiss Unitree’s robots as more spectacle than substance.
Wang disagrees:
<blockquote>“Right now, putting robots to work in homes or factories isn’t very realistic. Performance and demonstrations are just more achievable at this stage.”</blockquote>
He added that the team working on practical robotics is the largest within Unitree.
So why aren’t those use cases more visible?
“Developing practical robots is a massive challenge for AI models,” Wang said. “And honestly, we’re still not where we want to be.”
Wang’s vision for useful robots extends beyond narrow tasks like folding clothes or cooking. He sees them as general-purpose and multifunctional, such as being capable of pouring tea in a factory, then performing onstage.
Asked when robotics might see a breakthrough equivalent to AI’s “ChatGPT moment,” Wang offered a timeline: “The fastest would be two to three years. Slowest, maybe three to five. But this wave of embodied intelligence won’t take more than ten.”
What might that moment look like?
Picture a venue full of humanoid robots, walking freely. You stop one, give it a command, and it gets the job done. That, Wang said, would mark the tipping point.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3420014135987845">article</a> was written by Qiu Xiaofen for 36Kr.

Unitree’s founder disputes VLA consensus, backs video-trained models for robotics

Robotics

Embodied Intelligence

Foundation and Large Models

In a factory workshop in Chongqing, rows of mini tillers, generators, and energy storage devices are packed for shipment to destinations worldwide. Behind these seemingly ordinary machines is a manufacturing hub with outsized influence: the Chongqing general-purpose machinery (GPM) industrial belt produces and sells more than 14 million units annually—half of China’s total output—with mini tillers alone accounting for two-thirds of national production. These products serve traditional markets in eastern and central Europe and are increasingly reaching Southeast Asia and South America.
Once regarded as China’s de facto capital of mini tillers, this southwestern manufacturing cluster is transforming from a low-profile OEM (original equipment manufacturer) into a global innovation center for GPM.
“In the past, we’ve always been at the bottom of the smile curve. Now we’re stretching to both ends,” said Zhao Ming, deputy general manager of the general machinery division at Loncin Motor. He referred to the familiar model illustrating the challenge for Chinese manufacturing: low value-added assembly in the middle, with high-value R&amp;D and brand marketing concentrated in foreign companies.
Chongqing’s GPM industry has progressed through four phases: building a technical foundation during the Third Front Movement, expanding through private enterprise growth, integrating foreign capital for technology upgrades, and now, pursuing smart, green manufacturing.
The city has established a complete industrial chain, from parts production to final assembly. In agricultural machinery, Chongqing produces roughly two-thirds of China’s mini tillers. In GPM overall, annual production exceeds 14 million units, or half of the nation’s This integrated chain has become a competitive advantage internationally. In 2024, Chongqing’s electromechanical exports reached RMB 454.97 billion (USD 63.7 billion), up 8.4% year-on-year, with GPM products representing a notable share.
Unlike fast-moving consumer goods, GPM products are durable industrial equipment, which makes overseas expansion more challenging. “It’s not like we can create a hit product that sells thousands a day,” Zhao said. “Unit prices are high, and customers buy out of necessity.”
After-sales service poses an even greater hurdle. “Our products require users to have a basic level of mechanical knowledge,” said Xie Fuman, head of the smart terminal division and e-commerce marketing center at Senci. Generators and portable energy storage units require oil and gasoline, as well as regular maintenance—unlike plug-and-play electronics.
“After-sales problems can be life-or-death,” Zhao stressed. “High return rates can instantly wipe out profits.” Building service networks has therefore become a strategic priority for Chongqing’s GPM exporters.
To address these challenges, companies are testing solutions such as video-based guides, secondhand resale channels, and third-party service partnerships.
In response to global industrial shifts, Chongqing firms are also upgrading products. “Generators under 2,000 watts are gradually being replaced by energy storage products,” Zhao said. These devices are quieter, emission-free, and—thanks to advances in battery and chip technology—charge faster and last longer than traditional generators.
Artificial intelligence integration is emerging as another trend. While adoption is constrained by incomplete data, many in the industry see intelligent features as inevitable. “Energy storage devices will eventually become seamless backup power for homes,” Xie said. “When a power outage happens, users won’t even notice as the supply will switch over automatically.”
Senci, one of Chongqing’s major exporters, reported Amazon sales exceeding USD 40 million in 2024, with B2B transactions up more than 20%. Loncin Motor joined Amazon in 2024 and, within about three months, recorded RMB 4 million (USD 560,000) in additional sales. B2B orders from France, Spain, and Italy accounted for more than 10%.
Looking ahead, Chongqing companies are taking a measured view. “In the next five years, there’s unlikely to be a new product that can completely disrupt the GPM market,” said Haimaitong general manager Zhao Xin. He noted that competitiveness will depend on meeting user needs and avoiding closed-off development, ensuring that market feedback drives design.
Xie sees potential in untapped niche applications that could drive future growth. She also underscored the importance of brand building: winning customer loyalty through reliable products and service so that buyers return for upgrades and accessories.
Chongqing’s GPM export story has developed gradually, built on craftsmanship, market awareness, and sustained investment in innovation. These efforts have earned the trust of customers worldwide.
As Zhao put it: “Once we truly embrace independent innovation, the products we already make will naturally find their way to the world.”
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3414071119498889">article</a> was written by Ou Xue for 36Kr.

Chongqing’s machinery makers eye global markets, push for higher-value exports

Hardware

… players can’t afford to tackle everything at once—tech giants can.
For those still in the race, the next round of eliminations may only be just beginning.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3411113687944579">article</a> was written by Zhou Xinyu for 36Kr.

China’s “AI tigers” return to the ring as the foundation model race reignites

European leaders can complain to Beijing all they want about cheap Chinese <a href="/industry/ev">electric vehicles</a> flooding the continent, but their resistance may be futile.
This summer, more and more transporters have been spotted on Germany's autobahns ferrying loads of <a href="/company/byd">BYD</a>, <a href="/company/leapmotor">Leapmotor</a>, and Great Wall Motor cars from ports to dealerships. On Swedish and British roads, <a href="/company/xpeng">Xpeng</a> and Polestar cars are also becoming more common.
Industry researcher Jato Dynamics published analysis recently showing that 5.1% of new vehicle registrations in the first half of this year were for Chinese brands in 28 European countries (including the UK), a record high and a near doubling from a year ago. To put that figure in context, new registrations for Mercedes—once a darling of luxury car owners—reached 5.2% in the first half.
BYD is a big winner, registering 70,500 electric and hybrid vehicles in that period, a whopping 311% year-on-year jump. In June, BYD was the tenth most registered new EV brand, ahead even of Ford. Industry experts across the continent told Nikkei Asia that there has been a dramatic shift in consumer perception.
"Whereas ten years ago, Chinese cars were often characterized as 'lethal' or 'dangerous' over failed crash tests, major Swedish auto magazines and newspapers are now giving Chinese EVs top marks," said Frederic Cho, China adviser and vice chair of the Sweden-China Trade Council. "Xpeng, <a href="/company/nio">Nio</a>, and <a href="/company/geely">Geely's</a> Zeekr and Polestar have established prominent concept or flagship stores in central Stockholm."
Cho expects Chinese brands to have gained 10–15% of Sweden's EV market over the next five years, despite "some lingering hesitation [that] exists among consumers due to a general negative perception of China for political reasons and concerns about personal information being sent to Beijing."
Chinese automakers may also have won some hearts in Sweden because Geely turned Volvo's fortunes around after it acquired the ailing iconic Swedish carmaker from Ford in 2010. Another factor, Cho said, is that Sweden's population is concentrated in urban areas covered by the Chinese companies' dealerships and workshops.
"This concentration means shorter distances to dealerships, unlike in Germany where a major share of the population lives in small towns that are covered by European, Korean, and Japanese brands but not by the Chinese," Cho said.
In neighboring Denmark, Jorn Gronkjaer, chair of the Danish EV Association, has also noted a progressively more positive attitude toward Chinese EV brands. The market share of Chinese cars in Denmark reached 5.5% in June, up from 4.4% at the end of 2024, according to Danish online car marketplace Bilbasen.
"Danes have traditionally shown strong solidarity towards European cars like Volvo and Volkswagen, but the availability of lower-priced EVs, notably from brands like BYD, Xpeng, and MG, has been crucial for making electric cars accessible to every family in Denmark," Gronkjaer said.
He projected that the market share for Chinese brands in Denmark could reach 20% in the next five years, particularly with innovation, quality improvements and potential acquisitions of other brands.
Even in the Swiss market that is still dominated by German brands, BYD has broken through.
"The BYD Dolphin Surf is the first Chinese car to make a splash in the Swiss media and generate interest, especially among young people who cannot afford more expensive models like the Audi e-tron and have grown up with high-quality Chinese electronics and Chinese e-commerce websites like Temu and Shein," said Holger Wahl, chair of the Electric Vehicle Club of Switzerland.
The organization estimates that the Chinese EV market share is still under 1%, but expects it to grow to 3% by the end of the decade. The Swiss, with higher disposable incomes, tend to go for Audi and VW cars.
But Wahl said that young Swiss people buy cars via apps like Autoscout 24, which levels the playing field for Chinese brands as they do not have the extensive dealership presence that European carmakers have.
With Chinese cars now increasingly a common sight on the continent and in the UK, where does this leave European carmakers? Several experts said they had confidence that European brands will hold their own over the long term.
"I'm quite trustful that some of the European brands will safeguard their large market shares," said Gronkjaer. "If you are driving on Danish roads, you will see Volkswagen's IDs, BMW i, Renault E-Tech models, and Ford Explorer much more than in many other places."
Wahl believes the luxury segment will still be dominated by European brands. "I see the Chinese potential more in the lower price range, that is, growing unit numbers with low revenue," he said.
Indeed, BYD has mass production in its sights to serve the European market. The company had set up operations in Hungary's Szeged city to avoid European Union (EU) tariffs on Chinese-made EV imports.
But Reuters reported recently that BYD was delaying mass production at Szeged to 2026 and was shifting much of the planned output to Turkey, which isn't in the EU but has a tariff-free trade agreement with the bloc.
This article first appeared on <a href="https://asia.nikkei.com/business/automobiles/electric-vehicles/cheap-and-sleek-chinese-evs-turn-european-heads">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing partnership with <a href="https://www.rwegrgdf5.eu.org/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/">Nikkei</a>.

Cheap and sleek Chinese EVs turn European heads

Transportation

Electric Vehicles

Mobility

… acquisition, and inventory management.
whereAdBanner.Uptake
<h3>Recent deals completed in China:</h3>
<ul>
<li aria-level="1">Zhendian Zhigan, a sensor tech company, has raised an eight-figure RMB sum in an angel financing round led by KylinHall Partners, with participation from Shuimu Tsinghua Alumni Seed Fund. The startup, founded this year, is developing new sensor technologies and energy harvesting platforms. Proceeds will go toward R&amp;D, test line construction, commercialization, and team growth. —<a href="https://36kr.com/p/3420889721834889">36Kr</a></li>
<li aria-level="1">BCIFlex, a life sciences company, secured over RMB 300 million (USD 42 million) in a Series funding A round co-led by a Zhongguancun fund (managed by Legend Capital Management) and IDG Capital. Other participants include Yuanbio Venture Capital, China Life Capital, Lenovo Capital, Meituan’s DragonBall Capital, and Baidu Venture. —<a href="https://36kr.com/p/3418367276437123">36Kr</a></li>
<li aria-level="1">LindenBot, based in Hefei, has closed a nine-figure RMB angel funding round for its general-purpose embodied robotics. The round was led by Oriza Hua and joined by Xunfei Ventures, PreIPO Capital, Yingke Private Equity, Tianzhi Investment, and Hefei Hi-tech VC. —<a href="https://36kr.com/p/3417090204945801">36Kr</a></li>
<li aria-level="1"><a href="https://en.szporos.com/">Porosvoc</a>, an audio tech company, has raised an eight-figure RMB in Series A funding from Hanlian Semiconductor Industry Fund. Founded in 2018, Porosvoc develops tri-core audio AI chips and algorithms for use in smart devices and toys. —<a href="https://36kr.com/p/3417773665488263">36Kr</a></li>
<li aria-level="1">Xunlu Innovation Technology, an electric bike manufacturer, has raised an eight-figure RMB in a funding round led by HongShan’s seed fund, with continued support from Shunwei Capital and other existing backers. The funds will go toward the mass production of its debut model and R&amp;D for new products. —<a href="https://36kr.com/p/3413659660160640">36Kr</a></li>
<li aria-level="1">Artificial Productivity, an AI hardware startup founded in 2024 by former 4Paradigm chief scientist Tu Weiwei, has secured a seven-figure USD sum in seed funding. Backers include Ameba Capital, SenseCapital, and 4Paradigm, with Yuanhe acting as financial advisor. The company has delivered its first companion robot and plans to launch a mass-produced smart toy for children next month. —<a href="https://36kr.com/p/3412589113527684">36Kr</a></li>
</ul>
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<h3>SG Enviro, TopView, Oncode, and more made recent headlines:</h3>
<ul>
<li aria-level="1"><a href="https://sg-enviro.com/">SG Enviro</a>, a Singapore-based wastewater engineering company, secured SGD 8 million (USD 6.2 million) in funding led by Emerald Technology Ventures.</li>
<li aria-level="1"><a href="https://www.topview.ai/">TopView</a>, a Singapore-based platform that enables brands to create product content using artificial intelligence, raised USD 8.5 million in a Series A funding round led exclusively by Kamet Capital.</li>
<li aria-level="1"><a href="https://www.oncodesc.com/">Oncode Scientific</a>, a Malaysia-based molecular diagnostics company, received an undisclosed investment from the Malaysian Technology Development Corporation (MTDC).</li>
</ul>
If there are any news or updates you'd like us to feature, get in touch with us at: <a href="mailto:hello@rwegrgdf5.eu.org">hello@rwegrgdf5.eu.org</a>.
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Deals in brief: Naluri and Prefer raise funding, Antler invests in seven AI startups, six China deals, and more

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<h3>36Kr: In your view, what still lacks consensus in robotics?</h3>
GY: Plenty. The significance of actuators, for instance. Or which use cases will land first. Even the VLA framework is still evolving rapidly. Its core architecture may be settling, but implementation details are changing all the time, and fast.
<h2>Are large-scale data collection factories worth it?</h2>
<h3>36Kr: What’s your take on robotics companies building large-scale data collection factories? Isn’t there a problem if the data can’t transfer across different robot platforms?</h3>
GY: I don’t think large-scale data collection makes much sense at this stage. Robot hardware is still evolving quickly, and changes in form factor significantly reduce the reusability of collected data. That undercuts its value.
Also, at least with our algorithm, massive data collection isn’t necessary. What matters more is high-quality pretraining. Right now, some companies have it backward. They are overinvesting in data collection and underinvesting in foundational model quality.
<h3>36Kr: Some companies use data factories as part of their business model.</h3>
GY: In the short term, sure, it can bring in revenue. In the US, labor is expensive, so AI companies often buy data instead of collecting it. But long term, it’s a shaky model, especially when cross-platform generalization hasn’t been solved yet.
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<h3>36Kr: If someone buys data that doesn’t match their robot’s hardware, is it still useful?</h3>
GY: It’s still useful, but you’re getting diminished returns.
<h3>36Kr: Many demos now focus on robots folding clothes or opening appliances. Why those tasks?</h3>
GY: Folding clothes is one of the most difficult challenges in robotics. Clothing is deformable and behaves unpredictably, so it can’t be programmed in advance. That makes it a strong benchmark as it shows how robust the model really is.
Tasks like opening fridges or washing machines are familiar household interactions. They help people envision practical use cases for robots.
<h3>36Kr: What proportion of your training data comes from the internet, and what roles do different data types play?</h3>
GY: Over 95% of our training data is sourced from the internet. This kind of data provides wide-ranging context and variability, which is ideal for pretraining. The goal is generalization: can the robot handle unfamiliar situations?
Teleoperation data connects that generalization with precise physical control. Watching isn’t enough; robots also need to practice. Teleoperation enables the kind of fine motor training they require.
<h3>36Kr: How does generalization show up in practice?</h3>
GY: Let’s say a robot trained only on iPhones encounters a foldable phone for the first time. If it can still identify the object’s shape, understand its physical properties, and manipulate it correctly, that’s generalization.
<h3>36Kr: Is the industry good at that yet?</h3>
GY: We’re still in the early days. But we’ve seen significant gains since incorporating internet video into training. Generalization rates on unfamiliar objects can improve by 60–80%. And when you layer in teleoperation data, those gains compound even further.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3413531313409670">article</a> was written by Qiu Xiaofen for 36Kr.

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