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Vivo Installs an On‑Device AI ‘Brain’ in Your Pocket—Cloud Becomes Optional

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In the era of AI agents, the evolution of large AI models is no longer measured solely by technical specifications. Increasingly, the focus is shifting toward how deeply these models understand individual users, and nowhere is this transformation more visible than on mobile devices. Edge-side AI—where models operate directly on smartphones without relying on cloud resources—is accelerating, bringing the era of truly personalized agents running in the palm of our hands closer than ever. At the 2025 vivo Developer Conference, this shift was made tangible, signaling a new chapter in the development of mobile AI.

Zhou Wei, Vice President of vivo, Vice President of OS Products, and Director of vivo AI Global Research Institute, unveiled a major milestone: vivo has developed the world’s first 3-billion-parameter model specifically designed for edge-side agents. This lightweight yet capable model surpasses traditional mobile AI in scope, boasting multimodal processing, inference capabilities, long-form text handling, and user interface (UI) agent functionality. It marks a critical transition from AI that merely responds to input toward AI that genuinely understands the individual user.

Historically, while mobile devices could run both cloud-based and on-device large models, the reality for users was limited. Most functions relied on cloud infrastructure to complete complex tasks, making AI on smartphones less perceptibly intelligent. Miniaturizing models to run independently on devices without cloud dependency has therefore become a central goal. vivo’s 3B on-device model addresses this challenge directly. By combining efficiency with comprehensive capabilities, it sets a new benchmark for edge-side AI, demonstrating exceptional performance in authoritative evaluations such as OpenCompass and SuperCLUE’s on-device tests, achieving a significant lead over other models under 10 billion parameters.

The model’s capabilities extend well beyond conventional expectations. In language processing, it enables features like on-device call summarization and creative writing assistance. Its multimodal capacity allows it to comprehend and reason about images, while its logical reasoning supports deeper analytical tasks. Remarkably, it can maintain long-term contextual memory of up to 128,000 tokens using only 2GB of RAM. In the domain of mobile agents, vivo’s team created specialized training data for UI operations, enabling the model to inherently understand smartphone interfaces and execute cross-application actions. For the first time, a 3B model is purpose-built to function as an on-device agent capable of both comprehension and action.

This represents a profound shift in AI’s role on mobile devices. Previously, the user experience often resembled a “super customer service center”: cloud-based AI could answer questions, but it lacked depth, personalization, and memory. Everyone received standardized responses. Vivo’s Blue Heart 3B device-side model changes that, moving AI from the cloud into your pocket and enabling it to function as a constant companion.

The implications are significant. First, AI gains independence and immediacy. With the model deployed directly on the phone, users can task it in offline scenarios—on planes, in subways, or even in remote areas with weak signals. It can handle local files up to 128KB, summarizing meeting recordings or drafting emails without internet access. The result is not just speed but reliability: AI becomes a companion that is always available.

Second, AI begins to “see, understand, and act.” The model is not only a conversationalist but an executor: it can interpret images, understand app interfaces, and perform complex tasks across multiple applications. For instance, a simple instruction like “Share this meeting screenshot to the work group” triggers a sequence of automated actions—taps, switches, and uploads—executed seamlessly. This elevates AI from a reactive tool to a proactive assistant, capable of understanding both context and intention.

Perhaps the most revolutionary development is vivo’s introduction of the industry’s first on-device model training engine. If embedding AI into a phone is akin to hiring a highly capable butler, the training engine equips that butler with a brain capable of learning and growth. Previously, personalized AI learning occurred exclusively in large cloud computing centers. Now, it is possible to teach the model directly on-device. Upload a few photos you’ve edited, and the model learns your unique style, applying it autonomously to future tasks. This brings us closer to truly personalized AI: digital entities that evolve alongside the user, shaping themselves to individual habits, preferences, and workflows.

However, AI’s potential is fully realized only when integrated within a broader ecosystem. Standalone intelligence, no matter how powerful, cannot seamlessly enhance daily life. vivo’s vision frames AI as a brain, but it is the ecosystem that acts as the neural network, connecting intelligence with real-world tasks. To this end, vivo has developed the BlueHeart Personal Intelligence Framework, built around four dimensions: perception, memory, planning, and execution. This framework allows models to understand user intent with unprecedented accuracy, leverage multimodal data for contextual insights, accumulate personalized information over time, and autonomously orchestrate actionable solutions. The result is AI that can anticipate needs: summarizing long documents on the subway, recalling dietary preferences when ordering, or autonomously managing travel arrangements.

The open ecosystem approach is equally significant. The BlueHeart Intelligent Open Platform extends these personalization capabilities to developers, promoting shared standards, lowering barriers, and encouraging innovation. With full MCP protocol compatibility, the introduction of the A2A protocol for agent adaptation, and extensive context engineering support, the platform enables third-party developers to integrate, adapt, and expand AI capabilities. Currently, more than 50 ecosystem partners and over 200 services participate, collectively advancing a future in which apps do more than function—they understand, adapt, and anticipate. Navigation apps learn commuting habits, note-taking apps adjust modes based on work status, and AI integrates seamlessly across devices.

This strategy reflects a broader lesson from technological evolution: innovation thrives not in isolation but in open collaboration. By embracing openness, vivo positions itself as both a leader and a facilitator, enabling specialized partners to contribute their expertise while users benefit from richer, more intelligent experiences. Developers gain lower costs and broader market opportunities, and the industry collectively moves from a race for technical supremacy to an era of ecosystem-wide advantage.

Vivo’s approach illustrates the emerging paradigm: AI that is not only intelligent but intimate, capable of understanding individual behaviors, preferences, and workflows. By combining on-device model miniaturization, personalization, proactive action, and ecosystem openness, the company demonstrates a vision of AI that is always available, always learning, and truly human-centric. 

As the framework and ecosystem mature, we are entering an era in which AI is no longer a complex tool to be mastered but a partner that intuitively adapts, assists, and evolves with the user. vivo has set the standard; the challenge now lies with the broader industry to embrace this vision and deliver AI that genuinely understands us.

Source: AI TNT, sina finance, tech ifeng, xinhuanet, vivo

ChatGPT Is Evolving into an App Hub That Could Change the Internet’s Future

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On October 6, OpenAI officially announced the integration of several well-known applications—Booking.com, Canva, Coursera, Expedia, Spotify, Figma, and Zillow—directly into ChatGPT. This development means users can now complete tasks like booking flights, designing posters, generating charts, or even creating playlists, all within a single chat interface. There’s no need to switch between tabs, open new applications, or navigate across websites. For developers, these features are built on an open standard called the Model Context Protocol (MCP). For users, ChatGPT is evolving into more than just a chatbot—it’s becoming a dynamic AI portal.

This raises a fundamental question: Will this innovation follow the path of the much-hyped but underwhelming GPT Store, or does it signal a real shift in how people interact with digital services and applications?

Looking back at the evolution of digital gateways, progress has always revolved around one goal: making access to services more direct and efficient. Early internet portals like Yahoo consolidated content, while search engines like Google and Baidu thrived by providing fast information retrieval. Later, mobile operating systems like iOS and Android became central by hosting and distributing apps, while super-apps like WeChat integrated everyday functions into one ecosystem. Each step in this evolution shortened the distance between user intention and outcome.

OpenAI now appears to be attempting to eliminate that distance altogether. With the first wave of app integrations already live—excluding the EU for regulatory reasons—users across various ChatGPT plans (Free, Go, Plus, and Pro) can invoke these applications through natural conversation. One can now simply type “Spotify, create a party playlist,” or “Zillow, find properties in New York,” and the app will appear in the same chat window with interactive features. Users can browse, make selections, complete transactions, or generate documents without ever leaving the conversation.

What makes this approach even more ambitious is ChatGPT’s proactive suggestion capability. If you’re discussing house hunting, for example, it may automatically recommend Zillow and display interactive listings on a map—all within the chat. This shift from “searching for services” to “executing intent” effectively turns conversation into an operating system. It reimagines apps as natural language interfaces embedded within contextually aware AI.

Over the coming months, more services—including Uber, DoorDash, TripAdvisor, Target, and Instacart—are expected to join. OpenAI has also released an Apps SDK (Software Development Kit), which allows developers to create applications that can connect directly to their backends for features like login, content distribution, or membership services. The company has also launched a Developer Mode to simulate these apps and provide documentation and sample libraries for early adopters. An official application submission and monetisation system is expected to roll out later this year, alongside a public app directory.

According to OpenAI, this is only the beginning of an ecosystem that aims to bring more value to users and new opportunities to developers. If successful, it could give rise to a true “AI App Store,” where applications emerge organically within conversations based on user intent. For developers, this represents a new kind of visibility and distribution model: one that requires no downloads, no app stores, and no traditional marketing channels.

OpenAI’s broader vision is to position ChatGPT not just as a chat assistant, but as a foundational service layer—an intelligent operating environment that redefines how users interact with digital tools. Within this system, applications become contextual, modular nodes, and transactions occur as natural language interactions. Much like Apple transformed mobile distribution through the App Store, OpenAI is attempting to recreate this model through conversational AI.

But this move raises strategic and competitive questions. Other tech giants also have app ecosystems—will they be willing to integrate with ChatGPT?

For companies like Google, the answer is likely no. Google’s dominance is tied to its role as a search gateway, and integrating with ChatGPT—which allows users to bypass search entirely—would erode its core business. Google is instead betting on its own AI assistant, Gemini, tightly integrating it across Gmail, Maps, YouTube, and other properties to keep users within its ecosystem.

Meta is taking a similar approach. It aims to keep user interactions inside its social platforms like Instagram and WhatsApp, where its AI agents can serve contextual functions without giving away control. Meanwhile, other major players—Microsoft, Anthropic, and Amazon—are pushing their own assistant ecosystems in a growing race to control what many now call the “AI gateway.”

With the rise of conversational AI as a new access point to services, familiar tensions around fairness and control will inevitably arise. When multiple apps serve the same function, how does ChatGPT decide which one to recommend or trigger? If ChatGPT becomes an AI-powered “app store,” how will ranking, visibility, and discovery be managed? Will app placement depend on user relevance, algorithmic optimization, strategic partnerships, or advertising bids? And if OpenAI begins taking a cut of transactions—following Apple’s 30% commission model—will it face the same scrutiny over fairness and monopolistic behavior?

OpenAI has not yet detailed its monetisation policies but has indicated that developers whose apps meet quality guidelines will be eligible for inclusion in the app directory and may be featured more prominently during relevant conversations. Monetisation mechanisms will be shared “soon,” including support for the Agentic Commerce Protocol, which would allow users to complete purchases within ChatGPT using a universal checkout experience.

Privacy and data control are also central concerns. By integrating apps like Booking.com or Spotify, ChatGPT gains access to even more personal data—further enriching what some call a “holographic replica” of the user’s life. OpenAI has emphasized that developers must adhere to strict privacy policies, collecting only what is essential and being transparent about permissions. Users will be prompted to authorise any data sharing when first connecting to an app, and more granular privacy controls are expected to roll out later this year. Nonetheless, regulatory scrutiny is almost certain to intensify, particularly in regions like the EU where data protection laws are strict.

Despite these concerns, the potential rewards are massive. Developers may find in ChatGPT a revolutionary new discovery and distribution channel, and OpenAI could reshape the structure of the internet’s service layer. Just as portals changed how we accessed content, search engines changed how we found information, and mobile platforms redefined app distribution, ChatGPT may redefine how we interact with services.

Whether AI-powered assistants become the dominant entry point into digital life depends on a host of factors—user adoption, developer trust, regulatory environment, and competitive innovation. OpenAI currently enjoys a first-mover advantage, with over 800 million users and a strong foundation of developer engagement. But the road ahead will be contested, especially by established giants who are unlikely to yield their ecosystems without a fight.

Moreover, not every app is suitable for conversation-based use. Certain applications—especially games—require rich interfaces, real-time input, and complex user feedback. It remains to be seen how or whether ChatGPT can meaningfully accommodate these kinds of interactions.

Still, the race is on. Much like the early battles over web browsers or mobile operating systems, the fight to become the dominant AI gateway may define the next era of the internet. OpenAI has made its move. The question now is: who will control the front door to the AI-powered world?

Source: ChatGPT, GeekPark, frandroid

China’s Economic Transition: Managing Property Risks and Reviving the Stock Market

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As China approaches its 76th anniversary and the final stretch of the 14th Five-Year Plan, key questions are resurfacing: How should we assess the country’s economic performance over the past five years? What direction will the property and stock markets take? And how should individuals plan their finances amid persistently low interest rates?

Professor Zhu Ning Finance at the Shanghai Advanced Institute of Finance (SAIF) at Shanghai Jiao Tong University has long warned of risks in China’s real estate sector and broader macroeconomy—insights that earned his book Rigid Bubbles the prestigious Sun Yefang Award. At the same time, his work on investor behaviour sheds light on the deeper structural issues in China’s capital markets.

In a recent conversation, Professor Zhu reflected on the past five years and shared his thoughts on two growing challenges: the future of housing as an asset class, and the need for more rational investor behaviour in a long-term bull market.

As China marks its 76th anniversary and approaches the end of the 14th Five-Year Plan, how would you assess the country’s economic progress over the past five years, particularly in the financial and property sectors?

There are three areas of notable progress.

First is the shift from a property- and debt-driven model toward innovation-led, high-quality growth. This transformation is difficult but essential, and we’ve made solid progress.

Second, China’s role in global supply chains has grown stronger. Despite external pressures, our integrated manufacturing system has proven resilient and indispensable in areas from pharmaceuticals to daily goods.

Third, financial and property sector risks are being gradually resolved. Property prices are no longer seen as guaranteed to rise, and the economy is learning to rely more on productivity and market strength rather than real estate and infrastructure.

Overall, while growth has slowed, it reflects necessary adjustments. Managing risk always comes with costs, but this transition is crucial for long-term stability.

Has rigid redemption in China’s financial system truly been dismantled?

China has made important progress, but it’s not fully dismantled yet.

In the A-share market, rigid redemption is mostly gone—investors now understand the government won’t always step in. In areas like P2P lending, real estate, and trust products, implicit guarantees have weakened. But in local government and SOE debt, many still expect state backing. Without it, some issuers would struggle to raise funds or avoid default.

Going forward, markets should price risk based on a firm’s fundamentals—not on whether it’s state-owned or private. That’s the path meaningful financial reform must follow.

In many sectors involving state capital—like infrastructure or public services—private firms often lack interest. Without implicit guarantees, wouldn’t state-owned enterprises (SOEs) struggle to access financing?

That’s a valid concern, and it’s why we’ve seen a recent shift in how SOEs are classified—into strategic monopoly sectors and competitive market-oriented ones. For sectors like infrastructure and public goods, state involvement is necessary and expected. These can be viewed separately.

However, in more competitive fields—like civil aviation or transportation—we should encourage more private capital and genuine market competition. While SOEs bear important social responsibilities, their policy advantages can also hinder efficiency and responsiveness. It’s a double-edged sword.

The next stage of reform should aim to balance two things: leveraging the state’s capacity to support and guide SOEs, while also ensuring they operate with efficiency and accountability. Government support is fine, including credit enhancements—but it mustn’t foster complacency or moral hazard. If SOEs assume the state will always bail them out, discipline and initiative decline. The challenge is to retain the strengths of “state-owned” while integrating the dynamism and efficiency of private enterprise.

Considering recent trends in real estate and economic growth, would you say we have successfully achieved a soft landing for China’s property-driven economy?

Yes. When I wrote Rigid Bubbles in 2016, the main concern was preventing a property bubble burst that could harm the economy. At its peak in 2020–2021, real estate made up nearly one-fifth of China’s GDP, with related sectors accounting for about a third—an unusually high dependence.

Over the past five years, this model has been adjusted out of necessity. No asset price can rise forever, so we needed to prepare for a correction. The bubble’s deflation has allowed for a soft landing in property prices.

While the 2021 “three red lines” policy on developers could have been more flexible for a smoother transition, breaking the long-held belief that property prices only rise required a strong market correction.

In short, China has achieved a soft landing in the property sector without major damage to overall economic growth—a significant accomplishment. This is a truly remarkable achievement.

Many cities have eased purchase restrictions, yet the property market hasn’t rebounded. Are we swinging from a “prices only rise” mindset to the opposite extreme? How long will this adjustment last?

I expect the property market adjustment to last another 3 to 5 years. Historically, major property bubbles worldwide have taken about a decade to bottom out—Japan’s lasted 17 years, the US around 8. China’s peak was around 2016-2017, so recovery by 2026-2027 seems likely.

China’s bubble was especially extreme—property prices in some cities reached levels equivalent to 100 years of rent, far surpassing global norms. This suggests our correction could be longer and deeper than usual.

Regarding purchase restrictions, they’ve been mostly administrative tools to curb bubbles. Many local governments are easing these, but core areas like Beijing and Shanghai still enforce them. Fully lifting restrictions without stable prices could further hurt confidence.

At this stage, few short-term policies can stop the decline because both prices and rents have fallen, weakening real estate’s investment appeal. The market needs a gradual, “time-for-space” adjustment to realign prices with fundamentals.

“Made in China” is known worldwide, yet why has the stock market struggled? Despite strong economic growth and a renowned manufacturing sector, China’s stock market delivers relatively low returns for investors and plays a limited role in financing the real economy. What’s your take on this?

This is a complex issue rooted deeply in the nature of China’s capital markets, shaped by three main factors.

First, the focus has historically been on financing enterprises rather than on delivering strong investment returns. The stock market was initially designed to help state-owned enterprises restructure and grow, but little attention has been given to what investors actually gain. For the market to thrive, investor confidence and returns must improve, encouraging more long-term capital commitment.

Second, while rigid government guarantees have been removed, a paternalistic regulatory mindset persists—one that tries to shield investors from losses. This limits investor responsibility and market price discovery. True market development requires investors to learn from their mistakes, cultivating maturity through experience rather than protection.

Third, China’s market remains heavily retail-driven, with relatively little participation from institutional investors and long-term capital. Retail investors are prone to behavioural biases, causing volatility and limiting market stability. Expanding mature, patient capital is essential to anchor the market.

Finally, retail investors often lack understanding of the real economy and its relationship to the stock market, making investor education a crucial long-term challenge for China’s capital markets.

Source: Guancha, the new york times

Shenzhen, China’s Industrial Capital, Opens Its Factories to Tourists

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During the recent Chinese National Day and Mid-Autumn Festival holidays, Guangdong emerged as one of China’s top tourist destinations, attracting 65.176 million visits—a year-on-year increase of 11.5%—and generating 61.32 billion yuan in tourism revenue, up 14.2% from 2024, according to preliminary estimates from the Guangdong Provincial Department of Culture and Tourism. Beyond these numbers, a deeper trend is unfolding: Guangdong cities are embracing distinctive, culturally immersive tourism projects that reflect a new phase in the province’s tourism evolution.

Shenzhen, long known as China’s industrial capital, is leading this transformation through industrial tourism. The High Great Innovation Science Popularization Research and Industrial Tourism Base in Longgang District offers visitors hands-on experiences with drone operations, laser projects, and interactive exhibitions, allowing participants to explore the production and innovation processes of a national-level enterprise. 

Established by High Great, which produces one million drones annually, the base integrates tourism, education, and interactive play, aiming to cultivate scientific literacy among youth while broadening public understanding of the low-altitude technology industry. Opened in 2023, it is expected to attract around 50,000 visitors this year, doubling last year’s numbers. This base is part of Shenzhen’s broader initiative to develop themed industrial tourism routes, including visits to high-tech manufacturers like BYD and DJI, the Daya Bay Nuclear Power Plant, and other innovative sites.

Experts note that Shenzhen’s industrial tourism offers more than sightseeing. “Industrial tourism allows visitors to engage deeply, participate directly, and experience the lifecycle of industrial products,” says Professor Li Zhou of Jinan University. This learning-oriented approach—combining exploration, creation, and observation—reflects a shift from traditional tourism to a culture of experiential learning, resonating with modern travelers seeking meaningful and interactive experiences. Shenzhen’s advantage lies not only in its industrial base, with comprehensive R&D, manufacturing, and branding chains, but also in its natural ecological environment, with mountains, parks, and sea connections that complement industrial experiences. During this summer vacation alone, Shenzhen’s major industrial tourism sites welcomed around six million visitors.

Yet industrial tourism in Shenzhen is still in its early stages, with most visitors being corporate groups or students. Authorities recognize the need to expand to wider audiences and to transition from “simple visits” to immersive experiences that showcase full product lifecycles—from R&D to testing—while leveraging enterprises with unique industrial assets. Plans are underway to connect factories, exhibition halls, heritage sites, and educational centers into premium thematic itineraries, ensuring sustainable growth and broader appeal. Companies like Gaoju Innovation are also expanding content to reflect technological advancements and collaborate nationwide, creating an ecosystem for continuous innovation and enriched visitor experiences.

Shenzhen’s story is part of a larger movement across Guangdong, where cities are reinventing cultural tourism to emphasize creativity, lifestyle, and niche experiences rather than merely relying on scenic spots or broad-based attractions. Foshan, for instance, has transformed its dragon boat culture into a citywide tourism phenomenon. This year, it established a five-district dragon boat race matrix, including the Foshan F3 Dragon Boat Super League and the region’s largest five-person dragon boat race. By combining these events with gastronomic experiences, specialty markets, and intangible cultural heritage like fire dragon dances, Foshan created immersive experiences that drew 4.5839 million visitors over the holiday, generating 4.042 billion yuan in revenue.

Similarly, Shantou has positioned its culinary heritage as a central attraction rather than a supplementary feature. Visitors to the 2025 Shantou Cultural Tourism Carnival could participate in hands-on food-making, from rice cakes to oyster omelets, while exploring more than 130 branded food stalls offering local specialties. The city welcomed 4.502 million tourists, up 17.2% from the previous year, with tourism revenue increasing 20.1% to 2.87 billion yuan. Meanwhile, Meizhou’s rural eco-tourism has captured attention through picturesque villages, countryside bookstores, taverns, and unique homestays. Long’an Village and Zhuangzhu Village attracted visitors seeking rustic charm and immersive rural experiences, contributing to 2.262 million visits and 2.128 billion yuan in tourism revenue.

Experts highlight that the success of these projects stems from a new strategy: collaboration among distinctive tourism initiatives to appeal to diverse visitor groups and expand consumption markets. Shenzhen’s industrial tourism sets a benchmark for learning and innovation, while Foshan and Shantou leverage local culture and gastronomy to enrich visitor experiences. Together, these cities embody the Greater Bay Area’s approach of “differentiated development and coordinated synergy,” offering a diverse and complementary tourism landscape.

Underlying this shift is a broader rethinking of cultural tourism. Professor Wu Zhicai of South China University of Technology observes three key trends: a move from resource dependency to creativity-driven tourism, a shift from sightseeing to lifestyle and experiential consumption, and a transition from mass marketing to precise niche targeting. The emphasis is on preserving local culture dynamically, providing interactive experiences, building sustainable cultural industries, and creating strong cultural brands. Digital technologies and online platforms further empower cities to offer immersive experiences, reach target audiences, and conduct innovative marketing.

In this competitive landscape, success depends not on resource abundance but on creativity, local knowledge, and immersive experiences. Cities are encouraged to build attractions that feel authentic, unique, and refined, engaging residents and visitors alike. Collaborative mechanisms involving governments, businesses, and local communities are essential for sustaining these projects, ensuring that tourism development enhances urban identity and drives industrial growth.

As Guangdong demonstrates, the province is no longer simply a destination for sightseeing; it has become a dynamic arena where culture, technology, and lifestyle converge. From Shenzhen’s industrial innovation and Foshan’s dragon boat extravaganzas to Shantou’s culinary immersion and Meizhou’s rural retreats, visitors can now explore a rich tapestry of experiences that blend tradition with modernity. These initiatives not only elevate Guangdong’s appeal to domestic and international travelers but also redefine what cultural tourism is—a realm where learning, play, and discovery intersect, creating memories that endure far beyond the holiday season.

Source: szdushiquan, luoohu, High Great, CGTN

China’s Evolving Yet Steadfast Nuclear Strategy: A Balance of Capability and Restraint

At the 2025 military parade, China unveiled a full display of its nuclear triad for the first time—land-based intercontinental ballistic missiles such as the Dongfeng-61, Dongfeng-5C, and Dongfeng-31BJ; nuclear-capable air-launched ballistic missile (ALBM) called JL-1; and air-launched Jinglei-1 long-range missiles. This symbolic moment highlighted not only technological advancement but also the maturity of China’s strategic nuclear posture.

Despite this enhanced visibility, China’s nuclear policy remains fundamentally stable. China’s Ministry of National Defence spokesperson Zhang Xiaogang reaffirmed that China maintains a defensive nuclear strategy, rooted in restraint and predictability. Core principles such as the no-first-use (NFU) policy, non-use against non-nuclear states, and minimum deterrence continue to define China’s approach—underscoring that its nuclear forces exist solely to ensure national security and deter aggression.

To understand how this doctrine was formed and why it remains steady, it is helpful to explore its evolution over time—from foundational thinking under Mao Zedong to the refinements made in subsequent decades.

Mao Zedong Era: Laying the Groundwork for a Defensive Nuclear Strategy

Mao Zedong viewed nuclear weapons with a distinct sense of realism. Upon the atomic bomb’s debut in 1945, he famously remarked that it was “a paper tiger used to frighten people.” But as geopolitical tensions intensified—particularly during the Korean War and the Taiwan Strait crises—Mao came to see nuclear capability as essential for safeguarding sovereignty and national dignity.

China’s decision to develop nuclear weapons in the 1950s was not driven by expansionist goals but by a desire to resist external coercion. The successful test of its first atomic bomb in 1964 symbolized China’s determination to break the nuclear monopoly and oppose nuclear blackmail.

Even then, China adopted a principled stance: it pledged never to use nuclear weapons first and never to target non-nuclear-weapon states. This foundational thinking reflected Mao’s belief that nuclear arms are tools for deterrence, not warfighting.

Deng Xiaoping’s Contributions: From Possession to Deterrence

In the decades that followed, Deng Xiaoping brought a new dimension to China’s nuclear doctrine. While fully respecting the principles established under Mao, Deng began integrating the idea of nuclear deterrence more explicitly into Chinese strategic thinking.

Deng emphasized that China’s nuclear weapons were a “deterrent force”—not for aggression, but for ensuring peace through balance. His view was straightforward: “You have them, so we must have them too.” But he also insisted on limited development, reflecting a belief that effectiveness came not from quantity but from credibility. For Deng, the possession of nuclear weapons was enough to fulfill their purpose: deterrence through assured retaliation.

Under Deng, China began modernizing its nuclear forces, focusing on developing a second-strike capability—the ability to respond to any nuclear attack with an assured counterstrike. This evolution strengthened China’s credibility while upholding its NFU policy.

Post-Cold War Period: Refinement and Stability

With the end of the Cold War, Chinese leaders like Jiang Zemin and Hu Jintao further clarified and institutionalized China’s nuclear posture.

Jiang described China’s nuclear strategy as a form of “active defence”—a doctrine that deters conflict through credible capability without initiating escalation. In this view, nuclear weapons serve not just to respond to attacks, but to prevent war from occurring in the first place.

China’s Defence White Papers from 2000 onward reaffirmed that the sole purpose of China’s nuclear weapons is to deter nuclear attacks. Unlike some nuclear-armed states that have broadened the role of nuclear weapons to include non-nuclear threats, China has consistently restricted the scope of its nuclear deterrence to nuclear-related scenarios.

Hu Jintao went further, describing China’s nuclear forces as the “core strength of strategic deterrence”, highlighting their importance in maintaining national security while reinforcing the country’s commitment to a defensive and restrained policy.

Strategic Stability Through Deterrence, Not Domination

Today, China’s nuclear deterrence doctrine stands on a foundation of clarity, continuity, and credibility. Key characteristics of this doctrine include:

No First Use (NFU): A commitment never to use nuclear weapons first, under any circumstances.

Non-use against non-nuclear states and regions: Upholding fairness and responsibility.

Minimum but effective deterrence: Avoiding arms races while maintaining credible second-strike capability.

Defensive orientation: Nuclear weapons are seen as a last resort for national survival, not tools for coercion or expansion.

Moreover, China’s nuclear doctrine reflects a unique blend of Eastern strategic culture and pragmatic adaptation to global norms. While drawing upon global deterrence theory, China has tailored these ideas to fit its own values and conditions—focusing on balance, restraint, and stability.

The 2025 military parade did not signify a shift in China’s nuclear policy—but rather, a reaffirmation of its enduring principles in a more complex security environment. By displaying the full triad, China signals that while its capabilities have grown, its intentions remain anchored in peaceful deterrence and strategic stability.

China’s nuclear strategy, carefully developed over decades and consistently upheld, offers a model of responsible nuclear policy: one that values restraint over race, credibility over coercion, and defence over dominance.

How Faraway France Seized Vietnam from the Qing Empire

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France’s conquest of Vietnam, despite being a distant European power, is a story that intertwines missionary activity, opportunistic diplomacy, and the gradual weakening of China’s traditional tributary system. For centuries, Vietnam, Korea, and the Ryukyu Kingdom were loyal tributaries of the Qing Dynasty, closely tied to the central empire and participating in its ancient diplomatic network. 

Yet by the late 19th century, all three had fallen under foreign domination: Korea and Ryukyu to Japan, and Vietnam to France. While Japan’s imperial expansion in East Asia is widely known, the mechanisms by which France, thousands of miles away, gradually seized Vietnam remain less clear, yet are equally instructive.

The roots of French influence in Vietnam can be traced as far back as the late 17th century, when French missionaries arrived in the country under the guise of spreading Catholicism. Vietnam’s economy at the time was stagnant, and the rural population endured extreme poverty. Missionaries capitalized on this vulnerability, promoting the ideals of charity and “universal love,” offering education, medical care, and social assistance. 

Their work quickly embedded them in local communities, laying the groundwork for a far broader influence. By the mid-18th century, France had identified Vietnam as a potential target in its overseas colonial strategy. Missionaries—long serving as the vanguard of French intervention—began gathering intelligence, cultivating networks among local elites, and preparing the logistical and informational groundwork for a future incursion. 

A fortuitous opportunity soon presented itself. In 1777, Vietnam descended into internal turmoil when a king was assassinated, forcing Prince Nguyễn Phúc Ánh to flee to Saigon, where he found refuge with French missionary Joseph Pétard. Recognizing the strategic opportunity, Pétard advised Nguyễn Phúc Ánh to seek French assistance to reclaim his throne. The French, eager for influence in Southeast Asia, responded swiftly. In October 1787, France and Vietnam signed a treaty in Paris—the Treaty of Versailles—where King Louis XVI pledged to assist Nguyễn Phúc Ánh in restoring his rule. In return, Vietnam agreed to lease the port of Da Nang to France, allowing French warships to dock, developing trade infrastructure, and granting exclusive rights for missionary work.

The outbreak of the French Revolution shortly thereafter disrupted these plans. With France preoccupied, Pétard personally financed a mercenary force to support Nguyễn Phúc Ánh, who, doubting French reliability, ultimately sought assistance from the Qing Dynasty. With Qing military support, Nguyễn Phúc Ánh successfully restored order by 1803, founding the Nguyễn dynasty and inaugurating the Gia Long era. While the Treaty of Versailles remained unenforced, it planted the seeds of foreign intervention, signaling to France that Vietnam was vulnerable to external influence.

By the 1860s, the global context had shifted. The Qing Dynasty, weakened by the Opium Wars and internal strife, could no longer devote attention to its tributaries. France returned to press its claims, coercing the Nguyễn dynasty into signing the Treaty of Saigon in June 1862. This treaty granted France privileges over trade, navigation, and missionary activity, setting the stage for deeper encroachment. At this time, Vietnam was internally fragile: governance was riddled with corruption, heavy taxes and forced labor oppressed peasants, and repeated military campaigns against Cambodia left the state exhausted. These weaknesses created a fertile environment for French expansion under the pretext of protecting missionaries and French nationals.

Gradually, French forces occupied Cochinchina and extended influence into Annam and the Yunnan border region. A minor incident in 1869, involving arms smuggling by French merchants, provided a pretext for further military action. France launched an offensive northward, facing local Vietnamese forces. Initially, resistance appeared strong, as Liu Yongfu’s Black Flag Army inflicted defeats on the French. However, France, though weakened by the Franco-Prussian War, remained strategically committed. The Nguyễn dynasty, overwhelmed by superior French military power, sought peace, resulting in the Second Treaty of Saigon. Under its terms, France secured protectorate rights over Vietnam and influenced its foreign policy, though nominal sovereignty was preserved.

The Qing Dynasty, however, regarded Vietnam as a critical buffer for southwest China. Prince Gong Yixin protested France’s growing influence, but the Qing, still engaged in disputes with Russia over the Ili region, lacked the capacity to resist militarily. By the early 1880s, France, sensing both its own recovery and Qing preoccupation elsewhere, pressed its claims, signaling its intent to enforce protectorate rights. Negotiations with Qing representatives, including Zeng Jize, repeatedly stalled over the question of sovereignty, leaving Vietnam’s status ambiguous and heightening tensions.

Amid this stalemate, France escalated military operations in Tonkin (northern Vietnam), prompting the Qing court to dispatch elite troops and support the Black Flag Army. Initially, Qing forces suffered repeated defeats due to unpreparedness and reactive command structures. France, under the hardline leadership of Jules Ferry, advanced with superior organization and weaponry. Nevertheless, battlefield fortunes shifted when Qing General Feng Zicai mounted a successful counterattack at Zhennan Pass, restoring some territories and inflicting serious losses on French forces. The Qing used this advantage to negotiate the Sino-French Treaty, which allowed China to avoid ceding territory or paying indemnities while granting France de facto control over Vietnam, the opening of trade ports, and privileged commercial rights.

The gradual annexation of Vietnam illustrates the collapse of China’s centuries-old tributary system. France’s conquest was not a sudden stroke of military brilliance but the result of persistent, strategic maneuvering: missionaries acted as the initial agents of influence; local civil strife created opportunities; repeated treaties codified incremental gains; and Qing inability to formulate a coherent, proactive response allowed French power to consolidate. Vietnam’s departure from the Qing tributary network marked the onset of China’s frontier and diplomatic crises, demonstrating the consequences of an outdated system in an era of modern imperial competition. The Qing court, despite recognizing Vietnam’s strategic importance, consistently reacted belatedly, and its efforts—whether through military intervention or diplomacy—merely delayed the inevitable, highlighting the structural vulnerabilities that foreign powers like France could exploit.

By the late 19th century, Vietnam had become firmly entrenched in the French colonial system. The long arc of intervention—from missionary infiltration in the 17th century to protectorate establishment in the 1880s—reveals the interplay of internal weakness, opportunistic diplomacy, and external aggression that defined colonial expansion in Southeast Asia. France’s gradual seizure of Vietnam, while geographically distant, underscores how a combination of soft power, strategic patience, and exploitation of local turmoil enabled a European power to override traditional tributary loyalties and reshape regional political order, leaving an enduring impact on China’s perception of its borders and the vulnerabilities of its historical system of regional influence.

Source: zggjls, Sohu, 163, udpweb

After China Trip, Western VCs Exit Batteries, Solar, Hydrogen and Other Hard-Tech Sectors

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In July 2025, a group of eight senior venture capitalists from leading European and American firms—such as Kompas VC, Planet A Ventures, and Extantia Capital—traveled through China’s eastern industrial belt. Unlike typical investment scouting trips, this journey was not about discovering new opportunities. It was a strategic reconnaissance mission to assess the scale, speed, and technological depth of Chinese clean-tech industries, particularly in batteries, solar, wind, and hydrogen. What they found forced a fundamental reevaluation of their investment theses.

Their visit to CATL’s massive facilities in Ningde, Fujian, delivered the first shock. The factory floors were not bustling with workers but filled with highly automated, silent production lines. Robotic arms handled feeding, welding, assembly, and inspection with a precision and efficiency far beyond what any Western firm had operationalized. This was not just manufacturing scale; it was systematized automation. Moreover, the company’s R&D arm was already presenting near-term roadmaps for solid-state and sodium-ion batteries, backed by engineering timelines and pilot lines already under construction. The gap between aspiration and execution in the West was stark. While European and American firms debated factory locations and environmental assessments, CATL had turned its next decade of battery tech into a production plan.

In Shanghai, Marvel-Tech demonstrated a multi-fuel turbine capable of operating on hydrogen, ammonia, and natural gas. What left a deeper impression, however, was the process behind the product. To modify a turbine blade’s curvature, the company required a custom alloy and machining solution. Specifications were sent to a local supplier in the Yangtze River Delta. Within three days, compliant samples were delivered at a cost that astonished the visiting VCs. In Europe, such a request would typically involve weeks of negotiation, high tooling fees, and months of lead time. In China, suppliers function not only as vendors but as collaborative, on-demand extensions of R&D. The agility and affordability of this support system exposed a structural advantage Western ecosystems lack: a manufacturing supply chain that accelerates innovation rather than slows it.

The final leg of the trip took them to Kunshan, where they visited GCL Perovskite’s solar manufacturing facilities. There, they saw perovskite solar modules already on pilot production lines. While this technology remains largely in the laboratory phase in the West, GCL was iterating prototypes on a weekly basis and moving swiftly from research to manufacturing. The speed of commercialization was driven by an unusually tolerant industrial policy environment and a massive domestic market capable of absorbing risk. New materials and processes were validated in real-world conditions within months, not years. Feedback from production was rapidly integrated into further R&D. In contrast, Western companies often face a decade-long cycle of trials, certifications, and capital-intensive scaling hurdles before a product reaches commercial viability.

Returning from the trip, the VCs convened a series of internal reviews. The conclusion was sobering. Several entire sectors were added to a confidential “non-investment list”—segments where Chinese industrial dominance was now viewed as irreversible under current Western conditions. At the top of that list was battery manufacturing and its related supply chains. With Chinese battery costs at roughly $60 per kilowatt-hour—half the production cost in Europe and the United States—competing on price and scale was deemed unrealistic. Adding to the challenge, China controls the processing of most of the world’s critical battery minerals, including lithium, cobalt, and graphite. Attempts to build a Western version of CATL would not only be cost-inefficient but structurally disadvantaged from the outset.

Solar and wind hardware followed. The photovoltaic industry had already shifted dramatically over the past decade, with China now accounting for more than 80% of global solar panel production. The next wave, driven by perovskite and other advanced materials, was clearly underway, and again, Chinese companies were leading in both R&D and industrialization. Wind turbine manufacturing showed a similar trajectory: massive domestic installations had driven down costs while reinforcing heavy industry capabilities that the West had either offshored or allowed to erode. Green hydrogen, specifically electrolyser hardware, was also crossed off the list. China’s combination of subsidies and brutal domestic competition had reduced electrolyser production costs by 30–50% compared to Western firms. For capital-intensive hardware sectors that scale primarily through cost leadership, Western start-ups were no longer considered viable investments.

What struck the investors most was not any individual company, but the collective industrial system. China had built not just factories, but a national mechanism for scaling innovation. This system seamlessly connects research institutions, SME suppliers, engineering talent, capital, and policy support. It embodies what Stanford scholar Dan Wang calls a “scale-before-profit” model, where the goal is not short-term financial return but long-term industrial supremacy. The survivors of this model—companies that endure harsh competition and massive upfront investment—emerge as global champions with unrivaled cost efficiency and execution speed.

For these VCs, the path forward is not protectionism. Tariffs and subsidies may provide temporary relief but cannot reverse the structural disadvantages in scale, speed, and supply chains. Instead, a new paradigm has begun to take shape: “Western Software, Eastern Hardware.” It represents a reallocation of capital from direct hardware competition to software and systems integration—areas where Western firms retain deep expertise and competitive advantage. The logic is straightforward. While hardware’s performance may be fixed by its physical properties, its real-world effectiveness depends on how it’s used, optimized, and embedded in broader systems.

One promising area is software that enhances hardware performance. For instance, better battery management systems can extend battery life significantly through predictive analytics and control algorithms. Another lies in services and business models—deploying Chinese-made hardware through innovative frameworks such as Battery-as-a-Service, or integrating it into intelligent energy networks that manage generation, storage, and distribution. The West can also lead in building global standards, creating platforms for green finance, or designing carbon markets that monetize the decarbonization enabled by Chinese technology. And while China is focused on scaling current technologies, the West can double down on fundamental research: quantum-enhanced materials discovery, AI-driven energy systems, high-end chips, and precision sensors—areas where barriers to entry are high and China’s industrial system has yet to dominate.

Already, capital flows are shifting. At least two European battery start-up investments were paused after the China trip, and a new fund focused on cross-border technological collaboration has been launched. The goal is not to beat China at its own game, but to become the most advanced users and integrators of Chinese hardware.

The broader lesson is that the age of single-point technological advantage is over. Innovation now depends on the systemic ability to scale and commercialize at speed. China’s model, shaped by decades of state-driven industrial policy and relentless iteration, has reached a level of maturity that many in the West had underestimated. For Western entrepreneurs and investors, the imperative is not denial or confrontation, but recalibration. For Chinese innovators, the lesson is equally urgent: hardware supremacy must be followed by leadership in software, services, standards, and global integration.

The global industrial landscape is becoming flatter, faster, and more interdependent. In this environment, neither arrogance nor isolation will succeed. Only clarity of purpose, humility in strategy, and a willingness to collaborate across national and ideological lines will offer a sustainable path forward.

Source: Bloomberg, fujian gov, marvel tech

How Chinese E-Commerce Giant JD.com Is Building an AI Ecosystem Through Real-World Applications

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From foundational large models to deep vertical applications, JD.com has demonstrated its determination to make artificial intelligence a central pillar of its long-term strategy. On 25 September, the JD Discovery-2025 JD.com Global Technology Explorer Conference was held in Beijing under the theme “Enjoy AI.” At the event, JD laid out its AI Panorama—an overarching strategic blueprint for its AI efforts—while also announcing that it would continue investing heavily in AI over the next three years to build a trillion-yuan-scale AI ecosystem across multiple industries.

Xu Ran, Vice Chairman and CEO of JD.com, emphasized during his keynote address that the company would not pursue what he termed “campaign-style AI,” focused on hype or one-off showcases. Instead, JD aims to build sustainable AI that generates tangible industrial value. He revisited a formula first introduced at the 2023 JDD Conference—”the value of large models = algorithms × computing power × data × the square of industrial depth”—and noted that through two years of active application and experimentation, this formula had evolved into a more grounded expression: “AI Value = Model × Experience × Industrial Depth².” This refinement highlights JD’s growing focus not just on technical capacity, but on meaningful deployment in industry-specific scenarios.

JD’s perspective comes at a time when global technology giants are making massive investments into AI infrastructure. In their most recent financial reports, Alphabet, Microsoft, Meta, and Amazon revealed that their combined capital expenditure this year has already exceeded $170 billion—most of it poured into AI data centers. Annual spending by these companies is projected to surpass $350 billion by the end of the year. Against this backdrop, JD.com’s decision to double down on AI investment reflects not only competitive urgency but a belief that the AI industry has entered a new phase: from a “parameter race” defined by model size, to an “implementation race” focused on value creation through scenario-based applications.

JD’s response to this transition is built on technological advancement, practical experience, and industrial integration. At the model level, JD’s updated JoyAI model suite now covers a full spectrum from small-scale 3-billion parameter models to 750-billion parameter giants. It has also developed specialized models such as JoyAI LiveTTS for voice synthesis and JoyAI LiveHuman for digital human avatars. Behind these models are algorithmic innovations including Thought Chain Synthesis and Autonomous Planning (AOT), Progressive Self-Play Hybrid Thinking (PST), and Homomorphic Variational Inference Reinforcement Learning (HVRL), which are designed to significantly improve reasoning capabilities, inference efficiency, and engineering performance.

In addition to raw model development, JD has upgraded three core AI platforms that support practical applications across its business units. The Digital Human Platform 4.0 introduced the industry’s first virtual brand ambassador, drastically reducing the cost of livestreaming—by as much as 90% compared to human hosts. The JoyAgent 3.0 platform has been fully open-sourced, and over 30,000 agents are already active across JD’s internal operations. JoyCode 2.0 integrates intelligent agents into development workflows, cutting product development time by nearly a third. These platforms signal JD’s shift away from theoretical AI and toward deployable systems with measurable outcomes.

Rather than follow a purely open-source or academic path, JD’s AI strategy centers on first building capabilities within its own proprietary systems—particularly retail, logistics, healthcare, and industrial supply chains—and then gradually opening those capabilities to partners. The newly released Jingxi App, for example, is a next-generation lifestyle portal that enables users to shop, book travel, and order meals using only voice commands. JD’s new AI assistant “He, She, It” allows users to create and personalize their own intelligent agents and even embed them into smart devices. JD also launched JoyInside, the industry’s first smart integration platform that is now compatible with products from over 30 major hardware brands and is working with more than 10 robotics firms.

In practical deployment, JD unveiled the Logistics Superbrain Model 2.0, which incorporates multimodal learning for real-time logistics optimization. Its e-commerce architecture Oxygen AI—publicly introduced for the first time—is designed to operate intelligent agents across various retail functions. In healthcare, Jingyi Qianxun 2.0 is now capable of interpreting medical records and natural-language patient descriptions. For industrial applications, JoyIndustrial functions as the first large model specifically developed for industrial supply chain optimization, combining big data and AI to significantly improve productivity and reduce operational costs.

JD’s unique competitive advantage lies in the synergy between its technological capabilities and its deep operational infrastructure, especially its supply chain network. At the conference, JD announced that it would begin to open portions of its operational data—including warehousing, sorting, delivery, and pharmaceutical logistics—to external partners in AI and robotics. These high-quality datasets and business scenarios, combined with JD Cloud’s infrastructure, aim to support the training of production-grade models and embodied intelligence systems.

JD’s overarching strategy is clearly moving from internal development to public deployment, and from technical exploration to production-ready applications. In doing so, it is aiming to secure not only technological leadership but also long-term business value through increased user engagement and monetization. With the AI industry entering a phase of scenario-based competition, JD’s approach—grounded in real business use cases and backed by a complex, vertically integrated supply chain—may allow it to build defensible advantages that extend beyond algorithmic performance.

While many firms are still navigating the transition from AI research to business execution, JD appears to be building an AI ecosystem that prioritizes value creation, operational reliability, and industrial relevance. Its formula may be unconventional, but its logic is increasingly compelling: in the next phase of AI, success won’t be determined solely by model size or compute budget, but by how effectively these capabilities are applied to real-world problems at scale. JD’s commitment to industrial depth and pragmatic deployment may be what sets it apart in the next stage of global AI development.

Source: Sina, Xinhua, Guancha, geekpark

Poland’s Border Closure Disrupts Rail Freight: China Responds with Arctic Express Route to Europe

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On 22 September, the container ship Istanbul Bridge completed loading over 1,000 TEUs at the Beilun Port Area of Ningbo‑Zhoushan Port and set sail at around 04:30 the next morning, bound for Felixstowe in the United Kingdom. Rather than follow conventional maritime routes via Suez, the vessel will traverse the Northeast Passage through the Arctic, achieving a one-way transit time of just 18 days. This voyage marks the formal inauguration of the world’s first Arctic container express route between China and Europe—a high-stakes bet on alternative logistics corridors.

That timing could hardly have been more significant. On 11 September, Poland announced it would suspend all railway border crossings with Belarus, citing escalating military activity associated with the Russia-Belarus Zapad‑2025 exercises. Because the China–Europe Railway Express depends heavily on the Belarus–Poland link—especially at the key transshipment hub of Małaszewicze—the border closure effectively halted about 90 percent of rail freight between China and Europe. 

While Poland framed the move as a defensive measure, the timing and scale suggest deeper strategic calculation. The rerouting of a flagship rail route during heightened geopolitical tensions places Warsaw in a position to exert pressure on supply chains linking China to Europe. Analysts have described the closure as a “speed bump” for the China–Europe Railway Express, warning that Warsaw risks damaging its standing as an essential transit hub if the suspension prolongs. 

From the European Commission’s perspective, the shutdown is being closely monitored. Belgium and Brussels have expressed concern that the closure disrupts a major trade artery: approximately €25 billion in goods per year may be impacted. While this accounts for only a fraction of the China–EU trade volume (over €732 billion in 2024), it underscores how much has been invested in predictable overland logistics. China has also publicly objected: its foreign ministry called the China–Europe Railway Express a “flagship project” of China–Europe cooperation and urged that Poland take effective actions to ensure safe and smooth operation. 

Within days, more than 130 freight trains were reported stranded in Brest on the Belarusian side, unable to cross into Poland. Logistics operators estimate that it may take 7 to 10 days of continuous effort to clear the backlog, assuming both Belarus and Poland run operations nonstop. Meanwhile, per-shipment delays are expected to rise modestly—in the short term, transit times may stretch by 2 to 5 days, plus additional handling and storage costs. Some shipping firms have already begun evaluating alternative routes via the Caspian Sea and through St. Petersburg or the Baltic for onward transit. 

For China, the stakes are more than logistical. The rail corridor had become a central component of the Belt and Road narrative—a faster, more reliable overland link to Europe that could rival sea freight for time-sensitive goods. As e-commerce platforms and high-value manufacturing increasingly depend on just-in-time delivery, disruptions to the rail link imperil not just costs and schedules but the credibility of China’s trade diplomacy.

In this context, the Arctic container route via the Northeast Passage becomes more than a novelty—it takes on strategic weight. While the route is subject to seasonal constraints (typically navigable between April and November) and varying ice conditions, it offers an alternative channel less vulnerable to land border disruptions. Because vessels can carry far more cargo than a single train (1,000+ TEUs vs. a rail train’s 90–120 TEU capacity), even a modest shift of freight volume can relieve pressure on congested land routes.

That said, the Arctic route is not a drop-in replacement. It operates under different dynamics—fixed schedules are harder to maintain in icy seas, icebreaker support may be required, and costs can shift unpredictably depending on ice conditions and fuel. Nonetheless, the rapid organization behind Istanbul Bridge’s voyage—completed within roughly 11 days of Poland’s announcement—demonstrates Chinese shipping firms’ ability to mobilize quickly in response to disruption. This agility is underpinned by a broader strategy: state-backed firms pioneer new corridors, validate feasibility, and private operators follow with commercial operations. 

Poland’s move underscores a deeper tension: infrastructure that enables trade is also vulnerable to geopolitical pressure. For Poland, using transport control as leverage is risky. If the suspension is prolonged, it could erode Warsaw’s reputation as a reliable transit hub—opening space for competitor routes and partners to bypass Polish linkages. Meanwhile, Chinese exporters face increased premiums, delays, and forced reliance on maritime routes or more circuitous overland paths—raising costs and reducing predictability.

At a systemic level, the incident reinforces one of logistics’ harsh truths: resilience is not about a single optimal path but redundancy. The emergence of the Arctic route, more intensive use of the southern corridor (through Central Asia, Caspian, Turkey), and potential future routes via China–Kyrgyzstan–Uzbekistan reflect a push toward network diversification. Should one node or border falter, alternatives must already be in place.

By navigating ice and circumventing borders, China is signaling its intent: it will not be held hostage to terrestrial chokepoints. For the rail network that long carried its overland dreams, the lesson is clear—flexibility may now matter more than efficiency.

Source: SCMP, Global Times, People’s Daily, defencepk, X, AFP

From a Weedy Square to the Heart of a Republic: The Decision Behind China’s Tiananmen Parade

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On a cool March afternoon in 1949, four flares streaked across the sky above Beijing’s Xiyuan Airport. Below, a modest American jeep slowly rolled into the airfield. Inside sat the most powerful men of the Chinese Communist Party—Mao Zedong, Zhou Enlai, Zhu De, Liu Shaoqi, and Ren Bishi—joined by top generals Lin Biao, Ye Jianying, and Nie Rongzhen. This was no ordinary inspection. It was the Party’s first large-scale event in Beijing after leaving their rural wartime base in Xibaipo—a quiet rehearsal, many would later say, for the birth of a new nation.

That day, Mao reviewed troops not from a grand car, but from one of the captured American jeeps taken from the Nationalist forces. He had turned down offers from high officials to use their luxury sedans. “Wouldn’t it be more meaningful to review the troops in our captured American jeeps?” he had said, smiling. A young commander named Xu He, whose regiment had fought in the decisive battle of Tashan, never forgot the moment: Mao, standing in the open jeep, waving at each unit as it passed, the wind lifting his long coat. It was the only time Mao would personally inspect troops from a vehicle. In later years, he would always watch parades from the Tiananmen rostrum.

By July, preparations for the official founding of the People’s Republic were underway. Zhou Enlai chaired the committee in charge of the ceremony, and after lengthy discussions, two locations for the grand military parade were proposed: Tiananmen Square and Xiyuan Airport. Xiyuan had the advantage of space and prior use for large-scale events, but its distance from the city center and lack of proper viewing platforms made it less than ideal. Tiananmen Square, though still a neglected wasteland with chest-high weeds and a crumbling gate tower, held a symbolic power. It was central, spacious, and, most importantly, allowed the Party to stand side by side with the people.

Zhou submitted his recommendation: the parade should be held at Tiananmen. Liu Shaoqi quietly endorsed it by circling his name. Mao and Zhu De offered no written comment but agreed after Zhou’s oral briefing.

What followed was a race against time. The Tiananmen Gate Tower was in a state of decay—walls cracked, lanterns broken, thick pigeon droppings coating the ground like a carpet. A cannonball from past battles was even discovered lodged in a doorway. Soldiers swept, reinforced, tested the viewing platform for collapse by jumping on it in shifts. Zhang Zhixiang, in charge of the layout, submitted a plan: eight red flags, two slogans, a portrait of Chairman Mao, and red lanterns. Zhou Enlai approved everything—except the flowers on Jinshui Bridge, which he dismissed as “petty.”

Meanwhile, the military trained under the burning July and August sun. Over 16,000 soldiers assembled from various units—infantry, armor, artillery, cavalry, navy, and a newly formed air force. They trained 15 hours a day. The tank unit drilled in fields west of Beijing, often repairing old Japanese tanks on the spot. With no functioning radios, commanders resorted to crude but effective communication: stepping on drivers’ shoulders from the turret to signal turns.

Cavalry troops, elegant but notoriously difficult to coordinate, faced their own challenge. Riders reorganized 1,979 horses into black, red, and white columns, adjusting reins to ensure uniform stride and posture. Riders slept near their horses, grooming them, bonding with them—learning, at last, that alignment came not through force, but through trust.

Originally, the Air Force had not been included. But in late August, Nie Rongzhen asked whether aircraft could fly over Tiananmen Square. “We can organize a small squadron,” replied Chang Qiankun. From nine planes, the formation grew to 17—Mustangs, Mosquitos, transports, and even a few trainers. Nearly the entire People’s Air Force would be on display.

Security was a constant concern. The Kuomintang still controlled parts of the south and west and had a record of bombing cities like Peking and Tianjin. To guard against an air raid, the Central Military Commission stationed alert aircraft at Nanyuan, coordinated a surveillance network across liberated regions, and cleared the city’s airspace. The 3:00 PM start time was chosen precisely because enemy bombers usually struck in the morning. In fact, the Kuomintang had planned a raid on October 1 but aborted it—whether due to weather, logistics, or fear, no one could say.

Just in case, the flyover pilots were armed—with live ammunition. When questioned later about this clear violation of international parade protocols, pilot Xing Haifan explained: “If the enemy came, there’d be no time to reload.” The day before the parade, each pilot took an oath: if something went wrong midair, they would crash away from civilians—never into the square.

On October 1, 1949, at precisely 3:00 PM, Lin Boqu opened the inauguration ceremony of the Central People’s Government. Mao Zedong stepped forward and declared the founding of the People’s Republic of China. The square, once a wasteland, now roared with the sound of celebration.

At 4:35 PM, the military parade began. Zhu De, standing in an open car with Nie Rongzhen, rolled slowly across the square, reviewing the troops. Marching in perfect formation came infantry and armor, cavalry and artillery. Overhead, 17 aircraft buzzed past in a tight formation. The crowd looked up as four fully armed P-51s screamed across the sky—a moment of awe and quiet tension. Below, horses marched six abreast, tanks rolled with deafening rhythm, and every boot that hit the pavement echoed through loudspeakers, thanks to China’s first-ever “live broadcast.”

Qi Yue and Ding Yilan narrated the event, their voices carrying the sounds of marching feet, rumbling engines, and flying planes to every corner of the country. For the first time, the people of China heard, in real-time, the birth of their new republic.

And thus, from dusty airfields and cracked towers, from the sunburnt soldiers and patched-up planes, the People’s Republic of China began not just with a declaration—but with a parade that announced its presence to the world.

Source: people, souhu, our china story, Xinhua