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<a href="/company/baidu">Baidu</a> is rolling out trials of its Apollo Go robotaxis in Switzerland, with further tests planned in the UK and Germany next year, as the Chinese tech giant looks to take on its US peer Waymo in Europe.
Apollo Go has expanded its global reach after trialing robotaxis in Dubai in March, but this will be the first time its vehicles are on European roads.
The test runs in Switzerland, in partnership with PostBus, will use a pilot fleet for mapping trips without passengers and with safety drivers on board.
The company hopes to open its doors to a "select group of users" in the first half of 2026, still with a safety driver onboard, before driverless trials kick off later in the year. It expects to be fully operational in the first quarter of 2027.
The trials come after Baidu announced an agreement in August with ride-hailing platform Lyft to supply self-driving cars in Germany and the UK next year. The European fleet is expected to grow to thousands of vehicles in the following years.
"We are working closely with all relevant stakeholders, including our local partners in the UK and Germany, to advance our plans for market entry and ensure full compliance with local safety and regulatory requirements," Zhang Liang, managing director of Europe, the Middle East and Asia at Baidu Apollo, told Nikkei Asia, although he declined to reveal the timeline.
In October, a few months after Baidu's announcement, US rival Waymo—backed by Google parent Alphabet—also said it would trial robotaxis in London next year with a "small fleet of vehicles," and will look to grow over time.
"We intend to welcome our first public riders next year, contingent on government approvals, and look forward to expanding to more cities around the world in the future," a Waymo spokesperson said.
This makes the British capital the first city where US and Chinese robotaxis will be battling it out. The two giants will also face competition from domestic company Wayve, which is planning to launch pilot trips in London from the spring in partnership with Uber.
Robotaxis have been much slower to take off in Europe than in either the US or China, but BloombergNEF forecasts that there could be as many as 17,000 across Europe by 2030, mostly in the UK and Germany, which are each seen to have over 6,000.
The European market is expected to grow at a compound annual rate of 72.7% to reach USD 8.6 billion by the end of the decade, according to <a href="https://www.grandviewresearch.com/horizon/outlook/robotaxi-market/europe">Grand View Research</a>.
But analysts note that historic European cities could pose a novel set of challenges for Apollo Go and Waymo.
"Street patterns, narrower roads, and, in the case of the UK, driving on the other side of the road to most of the robotaxi development are all challenges for robotaxi developers, but they are not insurmountable," said Andrew Grant, head of intelligent mobility at BloombergNEF, which provides research about clean energy and technologies.
Baidu Apollo's Zhang said he was confident that Apollo Go's experience around the world would enable it to adjust to the specific characteristics of European cities.
"In particular, our expanding test operations in Hong Kong, one of the world's most complex right-hand drive cities, will provide valuable real-world experience that supports a smoother entry into the UK market," he said.
Waymo also said London's winding streets would not pose too much of a problem to its technology. "We are confident in our technology's ability to generalize to new environments like London," the company's spokesperson said.
Robotaxis could face greater competition from public transport in Europe, where many countries have prioritized the development of robobuses over driverless taxis, encouraging some companies to adjust their focus.
<a href="/company/weride">WeRide</a>, another Chinese autonomous vehicle developer, launched new robobus trials in Belgium in September, building off successful runs in France, Spain, and Switzerland.
"Robobuses face lower technical barriers and fit more easily into European transit, especially in dense urban corridors and short 'last-mile' routes connecting transit hubs to final destinations," analysts at S&amp;P said in a recent report.
The looming European competition between Apollo Go and Waymo marks another front in the struggle for technological supremacy between the US and China.
Last month, Apollo Go revealed that the average number of weekly riders surpassed 250,000 in October, a milestone Waymo reached in April.
Waymo has the most fully operational robotaxi services globally, said BloombergNEF's Grant, but all of them are in the US "2026 could be when we see fully operational robotaxi services outside the US and China," he said.
This article first appeared on <a href="https://asia.nikkei.com/business/transportation/uk-europe-emerge-as-robotaxi-battleground-for-baidu-and-waymo">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing partnership with <a href="https://www.0722vps.aieehr01.top/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/">Nikkei</a>.

UK, Europe emerge as robotaxi battleground for Baidu and Waymo

Baidu

East Asia

China

Transportation

Autonomous Vehicles

Mobility

Europe

… December 4, StairMed unveiled its second-generation high-throughput wireless invasive BCI system. The new version increases the electrode channel count to 256 and expands applications beyond motor control to include speech reconstruction.
<h3>36Kr: StairMed seems to place great emphasis on single-cell brain datasets. Why? Can this be seen as a key part of a data flywheel for brain science?</h3>
ZZ: Exactly. We often describe the BCI ecosystem as an inverted pyramid. At the bottom are the neural interfaces, above that is full-system development, then clinical accessibility, and at the top is neuroscience, which represents the understanding of the brain itself. The degree to which we understand the brain determines how far we can develop BCIs.
The foundational interface system makes clinical data collection possible, and these single-cell datasets are the key to advancing cognitive science. In turn, that deeper understanding helps us design better products and discover new applications.
For any BCI platform, the company that accumulates the largest and richest brain datasets will be best positioned to define the next wave of applications and technologies.
For example, the long-running US BCI project BrainGate has implanted systems in about 40 to 50 patients, generating limited but highly valuable data. That data has already powered research breakthroughs in thought-based typing and speech decoding. Now imagine scaling that from dozens to thousands or even tens of thousands of implantations.
<h3>36Kr: What role do AI and algorithms play in this process?</h3>
ZZ: Once a large dataset is accumulated for a specific brain region and task, we can train a foundation model using those brain signals, similar to how large language models are trained. This model can then be applied to new patients, giving them stronger baseline decoding and control performance.
Neural network algorithms are well-suited for processing complex data. At the moment, the control signals we decode are relatively simple, say, a two-dimensional cursor movement or a few degrees of motion control. That means smaller models, such as recurrent neural networks with around 100,000 parameters, are sufficient.
In the future, as we scale to higher throughput and more complex controls, both model complexity and parameter counts will rise. I believe AI’s current progress is more than sufficient to meet BCI needs for now.
AI is also valuable on the application side. For instance, in language decoding, we don’t need to decode entire words. If we can extract a few dozen morpheme categories from neural signals, large language models can use context to predict intended words, greatly improving communication efficiency.
Ultimately, the relationship between BCIs, humans, and agentic AI will be dynamic and collaborative. Sometimes we will issue high-level commands through brain signals and let the AI agent execute them, while in other cases, we will fine-tune actions ourselves for greater precision.
<h3>36Kr: Based on the performance of existing implant recipients, do you think BCIs could eventually give humans capabilities beyond the ordinary?</h3>
LX: That's actually what motivated us to pursue this technology in the first place. We’ve always envisioned consumer-grade applications. We started with medical use because it's a necessary path: it meets urgent clinical needs and forces us to perfect the technology.
Our hope is not just to restore motor or sensory function, but also to push the boundaries of human control. In the past, we controlled limbs with our brains. In the future, we might control external devices via BCIs, potentially surpassing normal human limits.
For example, Neuralink once released a mini game to measure cursor control speed and accuracy. Ordinary users can reach eight to ten bits per second (BPS), but paralyzed patients using BCIs achieved 9.5 BPS after training, which is faster than most healthy users. That shows BCIs can already confer comparative advantages in specific tasks.
Another idea: today, all device control remains constrained by path dependency. To move a cursor from one corner of the screen to another, you must physically drag it. In the future, by decoding spatial memory signals from the hippocampus, we could “teleport” the cursor instead, which is impossible with current technology.
Similarly, conventional controllers or voice commands are crude tools for manipulating robotic arms with multiple degrees of freedom. BCIs, however, can encode far more nuanced neural information, allowing users to control robotic limbs as naturally as their own. Research in leading journals has already shown that trained BCI users can operate robotic arms with smooth, coordinated motion.
<h3>36Kr: With AI evolving so rapidly, many experts worry about its impact on human education, employment, and even existence. Do you think human-machine fusion is inevitable?</h3>
LX: AI is meant to serve humans, and human intent should always remain central. But we cannot rule out the possibility that AI may one day develop self-awareness.
To prevent humans from losing agency or relevance, deep integration between humans and machines is, in my view, inevitable. The key to that integration is the bridge, and that is exactly what BCIs represent: a channel for information exchange between humans and machines.
Without that bridge, silicon-based AI and carbon-based humans could drift apart. But if AI becomes part of us, or we become part of it, we could achieve a harmonious coexistence, one without communication barriers.
Think of autonomous driving: you can tell the car to go from point A to point B, and it will plan and navigate independently, yet you can always take the wheel. That is controlled evolution. What we must avoid is a future where AI or robots operate entirely beyond human control. Deep human-machine integration may be the safer, more balanced path forward.
<h3>36Kr: If BCIs become fully mature, would you personally get implanted?</h3>
LX: We've talked about it before. I'd love to try it myself, just to experience what it actually feels like.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3569598798543750">article</a> was written by Hai Ruojing for 36Kr.

How far are brain-computer interfaces from restoring and extending human ability?

Medtech

Deep Tech

… added that it expects to be the first in China to mass produce and deliver automotive-grade Level 4 autonomous logistics vehicles.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3597598153785352">article</a> was written by Xu Caiyu for 36Kr.

Rino.ai raises new funding to accelerate toward mass production of autonomous cargo vans

Logistics

<a href="/company/li-auto">Li Auto</a> is setting up an <a href="/industry/ai">artificial intelligence</a> R&amp;D center in Silicon Valley, 36Kr has learned from multiple sources. The center will focus on smart driving technologies, and recruitment has been underway for several months.
According to a person familiar with the matter, Li Auto has long maintained a lean North American R&amp;D team supporting chip development and other intelligent systems. “This time, the plan is to upgrade the Silicon Valley team into a full-fledged R&amp;D center,” the source said.
36Kr understands that the new center will primarily focus on autonomous and assisted driving, with Li Auto seeking senior algorithm engineers with experience in advanced AI research.
Since October, Li Auto has completed channel and product rollouts in four overseas markets, including Egypt and Kazakhstan. Its global expansion strategy places similar emphasis on research. The company already operates R&amp;D centers in Germany and the US.
With the addition of the Silicon Valley facility, Li Auto will run four R&amp;D hubs worldwide. Its first overseas R&amp;D center, in Munich, Germany, opened in January 2024 and focuses on advanced design, power semiconductors, chassis systems, and electric drive technologies. Domestically, the company operates R&amp;D centers in Beijing and Shanghai, which are responsible for core technology development and vehicle engineering.
Home to <a href="/company/tesla">Tesla</a>, Waymo, <a href="/company/openai">OpenAI</a>, and <a href="/company/nvidia">Nvidia</a>, Silicon Valley remains one of the world’s densest concentrations of AI talent. For Chinese automotive companies, a presence in the region offers closer proximity to frontier research and experienced engineers.
Among China’s newer <a href="/industry/ev">electric vehicle</a> manufacturers, <a href="/company/nio">Nio</a> and <a href="/company/xpeng">Xpeng</a> established Silicon Valley operations earlier, Nio in 2014 and Xpeng in 2018. Li Auto’s later entry, with a focus on autonomous driving, reflects intensifying competition among Chinese automakers, as industry executives increasingly point to smart driving as a core area of focus next year.
That competitive pressure is rising across the industry. This year, <a href="/company/huawei">Huawei</a> launched ADS 4.0, its Level 3 autonomous driving solution for highway scenarios. Vehicles including the Maextro S800 and Aito M8 are now equipped with hardware capable of supporting Level 3 functions.
In March, Li Auto introduced its vision-language-action (VLA) model, which jointly models visual, linguistic, and motion data. By incorporating language modeling and reasoning chains, the system is designed to interpret complex driving environments, infer causality, and make decisions with less reliance on rule-based logic, potentially improving performance in unfamiliar scenarios.
On September 10, Li Auto began a broad rollout of the VLA model to users. CEO Li Xiang said on social media that the released version was a lite edition, with several key functions not yet activated.
Integrating large models into autonomous driving systems remains technically challenging. While the potential benefits are clear, reliable real-world performance depends on continued advances in algorithms, computing power, and data, validated through large-scale road testing.
China’s limited pool of engineers with experience spanning both large models and autonomous driving has made overseas hiring increasingly attractive. Against that backdrop, Li Auto’s move into Silicon Valley could prove strategically significant.
whereRelatedArticle
Xpeng, whose core strength lies in assisted driving, has operated R&amp;D centers in North America since 2018. Its teams in Silicon Valley and San Diego together number about 100 people. Even during periods of cost control, when hiring was restricted, the company retained the group.
That North American team has since become central to Xpeng’s driving technology development, handling algorithm work while China-based teams focus on requirements definition and testing.
In September, CEO He Xiaopeng allocated additional computing resources to the North American team to accelerate deployment of the company’s foundation model, which is being developed for in-vehicle use within the year.
The project is led by Liu Xianming, an executive Xpeng recruited from Cruise. According to company disclosures, the cloud-based foundation model has 72 billion parameters, is trained in the cloud, and is designed to transfer knowledge to a smaller model optimized for in-vehicle chips.
“The car-side model will likely have around seven to eight billion parameters, and internal expectations are high,” one person familiar with the project told 36Kr. By comparison, Li Auto’s deployed VLA model operates with roughly four billion parameters.
Xpeng’s sustained investment in North America has extended beyond vehicles. The company also operates a robotics team of about 20 people in the region. When Xpeng unveiled its first humanoid robot, Iron, in November, its share price rose, reflecting investor interest in its broader strategy.
At the start of 2025, Li Xiang outlined an updated corporate vision, saying Li Auto aims to become an “AI company” over the next decade. Business units have since reevaluated their operations through an AI-first framework. The VLA model marks an initial step, while the Silicon Valley center signals a deeper commitment.
Xpeng CEO He has said publicly that multimodal learning, world modeling, and long-horizon planning, capabilities often associated with artificial general intelligence (AGI), remain underdeveloped and may take years to mature or require fundamental breakthroughs.
As the smart vehicle framework continues to evolve, automakers face a narrowing margin for error. The ability to identify, absorb, and deploy new technologies may increasingly determine long-term competitiveness. That dynamic may help explain why China’s leading EV companies are converging on Silicon Valley, positioning themselves closer to one of the world’s most concentrated sources of AI innovation.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3466903693399680">article</a> was written by Xu Caiyu for 36Kr.

Li Auto builds Silicon Valley lab to chase Xpeng and others in smart driving

Electric Vehicles

… Happily Ever After. That’s a rare practice in the industry.
Jia Fei, however, understands how to build lasting IP. In 2016, he created Little Monk Yichan, a viral character that amassed 150 million fans across platforms.
That experience now shapes his approach to developing Liu’s persona. A year ago, Liu appeared for only five minutes in Affectionate Seduction, yet viewers responded strongly to him. Sensing potential, Jia Fei quickly edited a fan video spotlighting Liu’s scenes and posted it online, drawing the first wave of fans.
Over the following year, the team continued to create short skits around the same character archetype—disciplined, restrained, and quietly affectionate—traits that mirrored Liu himself. “He’s a traditional Shandong man,” Jia Fei said. “That self-restraint and integrity just radiate from him.”
So when Summer Rose premiered, fans’ emotions were primed to erupt, creating a perfect storm of connection that turned Liu into the next big star.
His breakout also marks a new chapter for the industry. The days of waiting for luck and miracles are over. Now, short drama makers are trying to engineer virality, to understand how to make the next Zhao Kechun or Liu Xiaoxu.
At the Weibo TV &amp; Internet Video Summit in early November, the red carpet featured major celebrities like Yang Mi and Wang Hedi, alongside short drama sensations such as Zhao, Yu Yin, and Yican Media’s own Wang Gege. Jia Fei splurged on a top-tier makeup artist and photographer, each charging tens of thousands of RMB per day. “Expensive,” he said, “but Gege deserves it.”
Hema Xingchi went the opposite route, branding Liu Boyang as “short drama’s number one bad boyfriend,” playing on his string of “repentant ex-lover” roles. Though Liu was hesitant at first, he agreed, realizing that the bigger risk was blending into the crowd.
Still, shadows linger over these shining stars.
Turnover is brutal. In just over a year, first-generation icons like Xu Yizhen and Sun Yue have faded from the spotlight. On Hongguo, the popularity rankings shift almost every month.
Industry veterans and viewers alike say part of short drama stars’ appeal lies in their relatability, a contrast to the carefully curated personas of traditional celebrities. Yet as commercialization deepens, that down-to-earth charm is eroding.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3586384697703553">article</a> was written by Lan Jie for 36Kr.

How short dramas are turning everyday actors into China’s newest idols

Entertainment

Video

Creative

Content

… user experience, you end up with clunky interactions, and that makes it hard for users to build emotional bonds with your brand,” Tong said.
Whether serving pets or people, Enabot’s mission has stayed consistent: to refine and deepen value in specific scenarios. This philosophy reflects a new generation of hardware companies focused on doing one thing exceptionally well rather than attempting everything at once.
<figure id="attachment_159003" aria-describedby="caption-attachment-159003" style="width: 480px" class="wp-caption aligncenter"><img loading="lazy" decoding="async" class="wp-image-159003" src="https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Production-Facility.jpg" alt="Photo shows Enabot’s production facility." width="480" height="480" srcset="https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Production-Facility.jpg 1080w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Production-Facility-720x720.jpg 720w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Production-Facility-1024x1024.jpg 1024w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Production-Facility-360x360.jpg 360w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Production-Facility-768x768.jpg 768w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Production-Facility-600x600.jpg 600w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Production-Facility-300x300.jpg 300w" sizes="(max-width: 480px) 100vw, 480px" /><figcaption id="caption-attachment-159003" class="wp-caption-text">Enabot’s production facility. Photo source: Enabot.</figcaption></figure>
<h3>Digital friends</h3>
In the post-pandemic era, the <a href="https://www.mckinsey.com/featured-insights/asia-pacific/five-fifty-the-lonely-economy">“loneliness economy”</a> is growing faster than ever. From young professionals living alone to self-reliant seniors and overworked office employees seeking emotional relief, companion robots are emerging as a new form of connection.
As these robots reach global markets, cultural context increasingly shapes how users perceive and interact with them.
In East Asia, and particularly China, companion robots often serve as emotional bridges within families, extending beyond the role of smart devices.
This reflects regional family structures and emotional norms. Enabot’s research shows that its core users include dual-income families and those with members living apart. Their primary need is for “remote co-presence,” or a sense of emotional connection across distance.
To meet that need, Enabot added features imbued with ritual and warmth. On a family member’s birthday, users can remotely adjust the robot’s eye light to display celebratory images. Its customizable facial expressions allow playful messages or emotive animations, fitting the East Asian preference for frequent, close family interaction.
<figure id="attachment_159002" aria-describedby="caption-attachment-159002" style="width: 1920px" class="wp-caption alignnone"><img loading="lazy" decoding="async" class="size-full wp-image-159002" src="https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Companionship.jpg" alt="" width="1920" height="1280" srcset="https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Companionship.jpg 1920w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Companionship-720x480.jpg 720w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Companionship-1024x683.jpg 1024w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Companionship-768x512.jpg 768w, https://console.0722vps.aieehr01.top/wp-content/uploads/2025/12/Enabot-Companionship-1536x1024.jpg 1536w" sizes="(max-width: 1920px) 100vw, 1920px" /><figcaption id="caption-attachment-159002" class="wp-caption-text">Photo source: Enabot.</figcaption></figure>
In contrast, users in Europe and the US prefer robots with humanlike empathy but lower intrusion. “Foreign users tend to want companionship that’s less intrusive,” Tong told 36Kr. “They appreciate a robot’s presence but do not want to be constantly interrupted.”
This preference reflects the Western emphasis on personal space and the independence typical of smaller family structures.
In practice, Enabot’s robots often function as discreet yet capable assistants. For security, they serve as mobile guards that monitor environmental changes and alert users to anomalies, offering an advantage over fixed cameras.
In companionship scenarios, users expect the robots to remember preferences, adapt to personal routines, and collaborate creatively, whether brainstorming story ideas or designing simple interactive games.
Western users also place high value on autonomy. When a device malfunctions, they expect it to self-diagnose and attempt repairs before sending logs to a server, reducing human intervention and safeguarding privacy through closed-loop data handling.
Ultimately, companion robots are the physical embodiment of human relationships. Across markets, they extend family bonds in some cultures and preserve personal boundaries in others. The contrast reveals a shared truth: understanding emotional reality is the foundation of meaningful connection.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3541396662431875">article</a> was written by Huang Nan for 36Kr.

Inside Enabot’s quest to build companion robots first for pets, then for people

Robotics

… humanoid robot form, according to Sharon Shih, an analyst with Morgan Stanley.
While optimism about physical AI is running high—buoyed by statements from figures such as SoftBank founder Masayoshi Son, who has called it the next big wave in tech—others are more cautious. <a title="https://asia.nikkei.com/editor-s-picks/interview/pat-gelsinger-deeper-taiwan-japan-ties-vital-for-next-gen-computing" href="https://asia.nikkei.com/editor-s-picks/interview/pat-gelsinger-deeper-taiwan-japan-ties-vital-for-next-gen-computing" target="_blank" rel="noopener">Former Intel CEO Pat Gelsinger</a> said humanoid robots still have many technological challenges to overcome and that progress could go through up-and-down cycles.
"The biggest challenge for humanoid robots today is having humanoids safe in the presence of humans," Gelsinger told Nikkei Asia. "Consumer humanoid robots are not going to happen [any time soon]."
This article first appeared on <a href="https://asia.nikkei.com/business/china-tech/china-s-humanoid-robot-makers-ramp-up-production-despite-tech-hurdles">Nikkei Asia</a>. It has been republished here as part of 36Kr’s ongoing partnership with <a href="https://www.0722vps.aieehr01.top/nikkei-teams-up-with-36kr-in-asia-tech-news-coverage/">Nikkei</a>.

China's humanoid robot makers ramp up production despite tech hurdles

Agibot

Embodied Intelligence

… industrial and logistics applications. —<a href="https://36kr.com/p/3585414578633604">36Kr</a></li>
</ul>
whereRelatedArticle
<h3>Airwallex, Granite Asia, RockFlow, and more made recent headlines:</h3>
<ul>
<li aria-level="1">Airwallex, a global fintech company specializing in cross-border payments, raised USD 330 million in a Series G round at a valuation of USD 8 billion.</li>
<li aria-level="1">Granite Asia, a multi-asset investment firm focused on the Asia Pacific region, completed a USD 350 million first close for its Libra Hybrid Fund, which targets USD 500 million in total commitments. The fund is anchored by Temasek’s Aranda Principal Strategies, Khazanah Nasional, and the Indonesia Investment Authority.</li>
<li aria-level="1">RockFlow, a Singapore-based fintech company, raised an eight-figure USD sum in a new round led by Ant Group, with participation from Monolith Management and existing investors Lanchi Ventures, Forwest Capital, and Evergreen.</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@0722vps.aieehr01.top">hello@0722vps.aieehr01.top</a>.
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Deals in brief: Pyxis hits first close of SGD 18 million round, BBVA leads Olea’s Series A funding, latest China investments, and more

Venture Capital

Private Equity

Investment

Merger &amp; Acquisition

Singapore

Vietnam

Hong Kong

Southeast Asia

… brake-by-wire technologies, including EMB.
According to 36Kr, companies at various growth stages—including Li Auto, Xpeng, GWM, and Chery—are racing to bring EMB-equipped models to market. Both Bethel and Orient Motion have secured initial customers.
Although regulatory clarity has opened the door for EMB commercialization, many technical standards remain to be finalized. The first companies to achieve mass production are expected to influence future industry benchmarks and gain a competitive edge. For startups, early mass production also validates technical capabilities and strengthens fundraising prospects.
“Orient Motion’s arrival has shaken up the market,” one industry insider told 36Kr. “It has driven EMB prices to the floor.”
EMB technology changes the structure of braking systems and raises technical requirements for certain components, making R&amp;D and testing costly in the early stages. When produced at a scale of around 100,000 vehicles, each EMB unit still costs roughly RMB 1,000–1,500 (USD 140–210) more than a traditional hydraulic system.
“From giants like ZF to local players such as Bethel, everyone takes EMB very seriously,” the insider added. “Developing this technology requires major investment, so early quotes were naturally high, but Orient Motion has pushed prices to a new low.”
An R&amp;D engineer at an OEM told 36Kr that most EMB solutions developed in China are technically comparable, with no clear leader in performance or safety.
Even as price wars appear to have cooled, OEMs continue to pressure suppliers to cut costs, and competitive pricing remains critical to winning new business.
Another source revealed that Orient Motion plans to begin mass production of its EMB systems in the first quarter of next year. Its aggressive pricing and timeline have already attracted attention from several automakers. “There’s no question that Orient Motion and Bethel are competing head-to-head for customers,” the source said.
The dispute between Bethel and Orient Motion captures the competitive dynamics shaping China’s rapidly evolving automotive technology sector. As the industry shifts from mechanical systems to software-defined vehicles, traditional supply chain boundaries are breaking down, creating new opportunities for startups to claim market share.
In this transitional moment, both established and emerging players are fighting to secure their place. Regardless of the lawsuit’s outcome, EMB’s arrival appears inevitable, and the dispute reflects the ambition and rivalry propelling China’s automotive supply chain beyond import substitution and toward setting global standards.
KrASIA Connection features translated and adapted content that was originally published by 36Kr. This <a href="https://36kr.com/p/3580832429177731">article</a> was written by Xu Caiyu for 36Kr.

China’s automakers gear up for EMB mass production, and its first major patent battle