Chinese AI agent Manus has emerged as the latest breakthrough in artificial intelligence technology, generating a significant buzz in the global tech community for its advanced autonomous capabilities.

Developed by Tencent Holdings-backed startup Butterfly Effect, Manus claims to be the world’s first general AI agent, distinguishing itself from conventional chatbots by focusing on task completion rather than just conversation. Unlike traditional AI assistants that primarily handle dialogue, the Chinese AI agent Manus utilises multiple AI models to perform complex, multi-step tasks autonomously.

During its invitation-only online preview last week, Manus demonstrated impressive capabilities, including creating customised websites, screening résumés, and producing property recommendation reports based on specific criteria. Manus executes complex tasks from start to finish, delivering complete solutions rather than just suggestions.

“The video says the AI agent is more advanced than a chatbot because it doesn’t only generate ideas but delivers tangible results, like producing a report recommending properties to buy based on specific criteria,” reported CNN Business.

How Manus works

In a post on X, Peak Ji Yichao, co-founder and chief scientist at Butterfly Effect, stated the Chinese AI agent Manus was built using existing large language models, including Anthropic’s Claude and fine-tuned versions of Alibaba’s open-source Qwen. The multi-model approach enables more sophisticated reasoning and action capabilities.

According to MIT Technology Review, which obtained access to the platform, using Manus “feels like collaborating with a highly intelligent and efficient intern.”

The publication tested Manus on three tasks: compiling a list of journalists covering China tech, searching for property listings with specific criteria, and nominating candidates for MIT Technology Review’s Innovators Under 35 list.

“While it occasionally lacks understanding of what it’s being asked to do, makes incorrect assumptions, or cuts corners to expedite tasks, it explains its reasoning clearly, is remarkably adaptable, and can improve substantially when provided with detailed instructions or feedback,” wrote Caiwei Chen in MIT Technology Review. What differentiates Manus is “Manus’s Computer” window, which allows users to observe what the agent is doing and intervene at any point. The transparency and collaborative machine-human approach gives users greater control over the AI’s actions.

Limited access despite growing interest

Despite generating significant buzz, access to Manus remains highly restricted. Fewer than 1% of users on the wait-list have received an invite code. The platform’s Discord channel has attracted more than 186,000 members, indicating substantial interest from potential users worldwide.

According to Chinese media outlet 36Kr, Manus’s per-task cost is approximately $2, which is claimed to be one-tenth of the cost of OpenAI’s DeepResearch service. If its server infrastructure improves, this cost efficiency could position the Chinese AI agent Manus as a preferred choice for individual professionals and small teams.

The system isn’t without limitations, however. MIT Technology Review reported that Manus encountered obstacles with pay-walled content and experienced occasional crashes due to high service loads. The message “Due to the current high service load, tasks cannot be created. Please try again in a few minutes” appeared multiple times during testing.

Strategic partnership with Alibaba

Recognising the potential for growth in the Chinese market, Manus recently announced a strategic partnership with Alibaba. According to the South China Morning Post, the March 11 announcement revealed “Manus will engage in strategic cooperation with Alibaba’s Qwen team to meet the needs of Chinese users. ”

The two companies are working closely to ensure all Manus functions are available on “domestic models and computing platforms,” although no specific launch date was provided. A representative of Alibaba’s cloud computing unit confirmed the cooperation, saying both parties are collaborating on open-source models and looking forward to “working with more global AI innovators.”

Alibaba’s QwQ-32B reasoning model advances in parallel

The partnership comes when Alibaba is progressing AI development. On March 6, the company unveiled its latest reasoning model, QwQ-32B, claiming its capabilities surpass OpenAI’s o1-mini and rival DeepSeek’s R1 model. The news was impactful enough to boost Alibaba’s Hong Kong-listed shares by 8% on the announcement day.

“Alibaba touted its new model, QwQ-32B, in an online statement as delivering exceptional performance, almost entirely surpassing OpenAI-o1-mini and rivalling the strongest open-source reasoning model, DeepSeek-R1,” reported CNN Business.

What makes this development notable is the model’s efficiency – Alibaba claims QwQ-32B contains just 32 billion parameters compared to DeepSeek R1’s 671 billion, suggesting significantly lower computational requirements. The tech giant intends to invest at least 380 billion yuan ($52.4 billion) in AI and cloud computing infrastructure over the next three years, underscoring its commitment to establishing leadership in AI.

China’s AI ecosystem gains momentum

As the Chinese AI agent Manus continues to develop through its partnership with Alibaba, it symbolises a broader phenomenon. The Chinese government’s policies include promoting technological self-reliance, generous funding initiatives, and a robust pipeline of AI graduates from top Chinese universities, which together have created a fertile ecosystem for progression.

Chinese firms are now creating increasingly advanced large language models that compete directly with Western counterparts. The Chinese government’s pledge to support “emerging industries and industries of the future” with increased funding for artificial intelligence, combined with Alibaba’s massive $52.4 billion investment commitment, demonstrates the nation’s strategic prioritisation of AI development.

The centrally-coordinated approach is yielding results. The emergence of tools like Manus suggests that the global AI landscape is evolving into a genuinely multi-polar space, with Chinese innovations increasingly setting trends rather than following them.

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DeepSeek AI in Chinese EVs is quickly becoming the new battleground for automakers, with companies trying to secure their competitive edge in China’s cutthroat electric vehicle market. AI technology has emerged as a important differentiator, and Phate Zhang, founder of CnEVPost, warns that vehicles without DeepSeek integration risk being “edged out of the market” entirely.

The South China Morning Post reports that DeepSeek AI adoption in Chinese EVs has gained momentum, with over a dozen automakers announcing integration plans in recent weeks. The technology has attracted manufacturers, from EV giant BYD to emerging players like the Stellantis-backed Leapmotor.

Integrating DeepSeek AI in Chinese EVs represents a significant technological leap forward. The Hangzhou-based AI company has captured global attention with its recent release of two advanced open-source AI models: DeepSeek-V3 and DeepSeek-R1.

The models are particularly notable for their ability to operate at a fraction of the cost and computing power typically required for large language model (LLM) projects, making them an attractive option for automakers looking to enhance their vehicles’ capabilities.

BYD, China’s leading EV manufacturer, has announced plans to integrate DeepSeek with its Xuanji vehicle software. The company aims to offer preliminary self-driving capabilities in nearly all its models at no additional cost, making autonomous driving features more accessible to mainland Chinese customers.

Its strategy includes equipping at least 21 models – including the affordable Seagull hatchback, priced at 69,800 yuan (US$9,575) – with Indigenous Advanced Driver Assistance Systems (ADAS).

The widespread adoption of DeepSeek AI in Chinese EVs extends beyond BYD. Other major players in the Chinese automotive industry, including Geely, Great Wall Motor, Chery Automobile, and SAIC Motor, have also announced plans to incorporate DeepSeek’s AI into their digital cockpits, highlighting the industry-wide adoption of this technology.

According to research firm IDC, DeepSeek’s open-source model has fostered a collaborative innovation ecosystem through platforms like GitHub, where global developers participate in optimisation and security testing.

The collaborative approach is expected to significantly improve the ability to effectively deploy, train, and utilise large language models. DeepSeek AI’s market impact on Chinese EVs is expected to be substantial. Zhang Yongwei, general secretary of China EV100, projects that by 2025, approximately 15 million cars – representing two-thirds of national sales – will be equipped with preliminary autonomous driving systems.

The forecast underscores the rapid transformation of China’s automotive landscape through AI integration. The competitive pressure in China’s EV market intensifies, as evidenced by aggressive pricing strategies. The China Passenger Car Association reports that manufacturers reduced prices on 195 models between January and November last year, compared to 150 models in 2023.

In this context, DeepSeek AI integration has become a important differentiator for automakers seeking to maintain their market position. As the integration of DeepSeek AI in Chinese EVs accelerates, the technology appears to be not just a trend but a necessary evolution.

The movement potentially sets new standards for the global automotive industry.

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Chinese iPhone users may soon experience AI features powered by home-grown technology, as Apple Inc. is reportedly planning to integrate Alibaba’s Qwen AI models into its devices. The move comes as the tech giant seeks to bridge a critical gap in its Chinese market offerings, where its global Apple Intelligence features remain unavailable due to regulatory restrictions.

The potential partnership, first reported by The Information and subsequently detailed by the South China Morning Post, suggests that Apple has chosen Alibaba’s Qwen AI model to power its AI features in China. This decision reflects Apple’s pragmatic approach to maintaining its competitive edge in the world’s largest smartphone market, while also adhering to local regulations.

Strategic implications for both giants

Industry analysts view this potential collaboration as a win-win situation for both companies. For Apple, partnering with a local AI powerhouse could help navigate China’s complex regulatory landscape while ensuring its devices remain competitive in a market increasingly dominated by AI-powered smartphones.

For Alibaba, securing Apple as a flagship partner could significantly boost its credibility in the global AI race. “The partnership between Alibaba and Apple partially validates Alibaba’s capabilities in AI and Qwen 2.5 Max,” notes Morningstar’s senior equity analyst Chelsey Lam. 

“Selecting the right partner to deliver a good Apple Intelligence experience will help them reinvigorate iPhone sales in China.”

Technical Prowess and Market Timing

Alibaba’s Qwen AI model has recently gained significant recognition in the global AI community. According to the collaborative machine-learning platform Hugging Face, Qwen is powering the world’s top 10 open-source large language models (LLMs). This technical achievement likely played a crucial role in Apple’s decision to partner with Alibaba.

This development’s timing is particularly noteworthy, as Apple prepares to host its China developer conference in Shanghai on March 25. The event has sparked speculation about the possible launch of Apple Intelligence features for Chinese iPhone users, potentially powered by Alibaba’s Qwen model.

Market response and future implications

The market has responded positively to the news, with Alibaba’s stock price gaining 1.3% in the US on Tuesday, following a 7.6% increase on Monday. Apple’s stock also saw a 2.2% increase, indicating investor confidence in the potential partnership.

The collaboration could have far-reaching implications for both companies. For Apple, it represents a practical solution to maintain its premium positioning in the Chinese market while complying with local regulations. 

As industry experts indicate, this partnership could increase Alibaba’s interest from other global technology companies seeking AI partnerships in China.

Looking ahead

While neither Apple nor Alibaba has officially confirmed the partnership, the development has generated significant buzz among Chinese iOS developers. The potential integration of Qwen AI models into iPhones could open new opportunities for local developers to create AI-powered applications tailored to the Chinese market.

As the March 25 developer conference approaches, the tech community will watch closely for any official announcements regarding this partnership. If confirmed, this collaboration could set a precedent for how international technology companies adapt their AI strategies to succeed in the Chinese market while complying with local regulations.

The reported partnership underscores a growing trend of localisation in AI technology. Global companies are increasingly seeking local partners to maintain their competitive edge in specific markets.

For Apple, whose success in China has been crucial to its global growth story, this adaptation could prove essential in maintaining its market position amid rising competition from local smartphone manufacturers with integrated AI capabilities.

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A dramatic shift in open-source AI development is emerging from China, where startup DeepSeek fundamentally challenges how artificial intelligence evolves. By making its technology freely available for anyone to download, modify, and build on, DeepSeek has ignited a debate about the future of AI and global technological leadership.

The cost revolution in open-source AI development

When DeepSeek’s R1 model overtook ChatGPT as the most downloaded free app on the US Apple App Store in January 2025, it represented more than just market success – it signalled a potential shift in AI economics.

At just $5.6 million in development costs – roughly one-tenth the price of Meta’s similarly open-source Llama model – DeepSeek has demonstrated that cutting-edge AI doesn’t require massive investments. Unlike established players like OpenAI and Anthropic, whose models remain closely guarded secrets, DeepSeek opted for transparency, offering its code and technical documentation to the global developer community.

The approach to open-source AI development hasn’t compromised capability; the model demonstrates reasoning and mathematical skills comparable to more expensive rivals. The implications extend beyond finances. Traditional AI development requires massive computing resources, contributing to high electricity consumption and carbon emissions.

DeepSeek’s efficient training method could pioneer more sustainable AI scaling, which is particularly important as these technologies become ubiquitous. However, the “open-source” designation demands scrutiny. According to the Open Source Initiative (OSI), true open-source AI must provide detailed information about training data and allow unrestricted study, use, and modification of the system.

While DeepSeek has released its model weights and some technical documentation, it hasn’t fully disclosed its training data, raising questions about complete transparency.

Global impact and security concerns

The democratisation of AI through cost-effective open-source development could accelerate innovation worldwide. Smaller companies and developers in regions with limited access to cutting-edge technology can now build on established models rather than starting from scratch. The collaborative approach could catalyse more diverse applications and solutions to real-world problems.

Yet this accessibility comes with risks. Critics, particularly in the US, worry about potential misuse of open-source AI models, from developing bioweapons to spreading misinformation. The controversy intensified when OpenAI announced an investigation into whether DeepSeek may have “inappropriately distilled” its models – essentially using OpenAI’s outputs to train its competing system.

The geopolitical implications are significant. As Meta CEO Mark Zuckerberg noted, “The is a huge geopolitical competition, and China’s running at it super hard.” DeepSeek’s success has prompted reflection on the traditional American model of proprietary AI development, with some arguing that the US should embrace more open methodologies to maintain technological leadership.

Looking ahead, DeepSeek’s breakthrough, with its $5.6 million price tag, could reshape the entire AI landscape. The company has proven that efficient, cost-effective open-source AI development is possible without the massive resources typically associated with cutting-edge models.

This could lead to a more diverse and competitive AI ecosystem, with innovation emerging from unexpected quarters. However, the path forward remains complex. Regulatory frameworks are evolving as governments struggle to balance innovation with security concerns worldwide.

The Trump administration has yet to fully articulate its AI policy, though some officials have supported open-source development. What’s clear is that DeepSeek’s efficient approach to open-source AI development has challenged fundamental assumptions about the field, forcing the industry to reconsider what’s possible with limited resources and an open approach.\

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For the second time in two years, YMTC, China’s leading memory chip maker, has proven that US trade restrictions have done little to slow its technological advancement. Fresh on the heels of its 2022 breakthrough with 232-layer NAND technology, the company has pushed boundaries again in memory chip innovation. The breakthrough came to light through research firm TechInsights’ analysis. It demonstrates YMTC’s mastery of the Xtacking4.0 design in high-density 3D NAND chips, and marks another instance of Chinese semiconductor technology advancing despite Washington’s attempts to contain it.

According to TechInsights’ recent report, quoted by the South China Morning Post, YMTC’s achievement was discovered in the commercial ZhiTai TiPro9000 solid-state storage device. The device features an advanced dual-deck structure with 150 gates on the lower deck and 144 gates on the upper deck, totalling an impressive 294 gates.

The design employs sophisticated hybrid-bonding techniques to join two wafers, achieving an unprecedented storage density exceeding 20 gigabits per square millimetre.

YMTC’s journey from latecomer to industry pioneer

Since its inception in 2016, YMTC has transformed from newcomer to formidable competitor in the global flash memory industry. The company’s rapid technological advancement was first highlighted in 2022 when it produced a groundbreaking 232-layer NAND flash, surpassing the abilities of industry giants like Micron Technology, Samsung Electronics, and SK Hynix.

The achievement was particularly notable as it came just before the company was added to Washington’s export blacklist that was assembled over national security concerns. TechInsights senior analyst Jeongdong Choe emphasises the significance of this latest development, stating, “The important takeaway is that China’s YMTC has beaten the competition in the market. With the new Xtacking4.0 technology, YMTC appears to have found a way to overcome the current ban with this new chip.”

Challenging global leaders despite trade restrictions

After being blacklisted two years ago, YMTC lost access to important semiconductor equipment makers like Lam Research. However, the company adapted, strengthening its partnerships with domestic chip tool manufacturers like Naura Technology Group. YMTC’s achievements have caught the attention of global competitors, particularly in hybrid bonding technology. “YMTC is the leader in hybrid bonding technology, which is essential for higher-layered 3D NAND,” Choe explains. “That’s why Samsung and other NAND companies follow and prepare the hybrid bonding structure for the next generations.”

While YMTC maintains a modest public stance about its breakthrough, simply stating it is “committed to driving global innovation to propel the industry further forward and meet the evolving needs of our customers and partners,” the implications of its achievement are far-reaching. The company’s success demonstrates China’s growing capability to develop advanced semiconductor technology independently despite international trade restrictions.

The global memory chip landscape is competitive, with SK Hynix announcing plans to mass-produce 321-layer 4D NAND chips in the first half of this year. However, according to TrendForce, the market faces challenges from weak demand and oversupply, exacerbated by aggressive production expansion from Chinese suppliers driven by domestic substitution policies. The latest memory chip breakthrough by YMTC showcases China’s technological resilience and signals a shifting dynamic in the global semiconductor industry. As the company continues to push boundaries in memory chip innovation, it demonstrates how trade restrictions may be driving rather than hampering Chinese technological self-sufficiency.

The achievement also validates YMTC’s potential as a serious contender in the global market, supporting earlier speculation that the company was considered a potential supplier for major international technology companies, including Apple, before US trade restrictions were imposed. As global competition in NAND flash memory intensifies, YMTC’s success suggests that the landscape of semiconductor manufacturing may be evolving more rapidly than anticipated, with implications for both market dynamics and international trade policies.

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Chinese tech giant Huawei shattered market expectations on Wednesday, announcing a staggering 860 billion yuan ($118.3 billion) in revenue for 2024 – its fastest growth since 2016. The 22% surge is a direct challenge to US technology restrictions, marking a pivotal moment in the ongoing technology trade war between the world’s two largest economies.

Chairman Howard Liang Hua’s announcement at a Guangdong provincial government conference revealed that the company’s “overall operations met expectations,” powered by robust performance in its consumer business segment and rapidly-expanding smart car solutions. 

The achievement is particularly noteworthy as it represents Huawei’s second-highest revenue figure, following a 891 billion yuan peak in 2020. The strong performance in 2024 shows a remarkable recovery from the 704.2 billion yuan posted in 2023, highlighting the company’s successful adaptation to a challenging operating environment.

The significance of the growth becomes more apparent when considering the context of US sanctions imposed in May 2019. The restrictions were further tightened in August 2020, explicitly targeting Huawei’s access to advanced semiconductors that were developed or produced using US technology, regardless of their manufacturing location. 

Despite those substantial obstacles, Huawei has managed to sustain its operations and significantly expand them.

Strategic pivots and innovation 

However, the path to success has required significant investments and strategic adjustment. The company’s financial data reveals a 13.7% decline in net profit to 62.9 billion yuan for the first nine months of 2024, compared to 72.9 billion yuan in 2023. 

The reduction in profitability reflects Huawei’s aggressive investment in research and development, a crucial strategy in its quest for technological self-sufficiency. Huawei’s response to US restrictions has been multifaceted, positioning itself as a leader in China’s push for technological independence. 

Founded in 1987 by Ren Zhengfei, the company has become emblematic in China’s efforts to overcome US restrictions. The restrictions were initially imposed due to concerns about potential military applications of US core technology. The company’s recent initiatives in artificial intelligence underscore its commitment to maintaining technological leadership. 

Last week, Huawei’s cloud-computing unit made a significant move by making DeepSeek’s AI models available to end users through its Ascend cloud service. According to company statements, the performance of the models matches those running on global premium graphic processing units, demonstrating Huawei’s continued ability to compete at the highest technological levels.

Prospects and industry impact 

Liang’s comments about AI being “at an accelerated stage of development” and its application “ushering in a critical period of time” suggest Huawei’s strategic focus on emerging technologies. 

This perspective was reinforced by Guangdong Communist Party chief Huang Kunming, who praised Huawei’s “leading digital technology” and its role in empowering industries. The company’s success in 2024 has implications beyond its operations. 

As a major player in global technology markets, Huawei’s ability to grow despite restrictions challenges assumptions about the effectiveness of trade sanctions in limiting technological advancement. The company’s consumer business revival, particularly in smartphone sales, and its expansion into new areas like smart car solutions demonstrate its market adaptation and innovation capacity.

Huawei’s performance raises important questions about the future of global technology supply chains and the ongoing technology competition between the US and China. While the company faces continued challenges in accessing certain advanced technologies, its successful pivot to alternative growth strategies and focus on self-sufficiency suggests a resilient business model that can withstand significant external pressures.

The company’s ability to maintain strong revenue growth while investing heavily in research and development positions it well for future challenges. However, the impact of reduced profit margins and the ongoing need for technological self-sufficiency will likely continue to shape Huawei’s strategic decisions in the coming years.

This remarkable revenue performance in 2024 demonstrates Huawei’s resilience and highlights the complex nature of global technology competition, where innovation and adaptation can sometimes overcome even the most stringent regulatory challenges. 

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The latest escalation in the US-China trade war has sent shockwaves through global markets as Beijing unveiled a calculated series of retaliatory measures against American businesses, marking a significant intensification of economic tensions between the world’s two largest economies.

The Chinese government’s response, triggered by President Trump’s blanket 10% tariff on Chinese imports, demonstrates a sophisticated approach to economic warfare by the Chinese. Its measures target strategic sectors from technology to rare earth metals with careful calibration of their impact on domestic markets.

Strategic targeting of American business interests

Beijing has said it will introduce a 10% tariff on US agricultural machinery and a 15% charge on crude oil imports, which will likely pressure specific US sectors rather than wage all-out economic warfare.

The measured approach is particularly evident in China’s targeting of US tech giant Google through an anti-monopoly investigation, despite the company’s limited presence in the Chinese market since 2010. The energy sector measures are more noteworthy, with China imposing a 10% tax on liquefied natural gas (LNG) imports from the US. While China has been increasing its LNG imports from America, with volumes nearly doubling since 2018, the overall impact will be limited.

US imports account for just 1.7% of China’s total crude oil purchases from abroad, suggesting Beijing has chosen its targets carefully, as ones that won’t significantly disrupt domestic energy security. China’s strategic calculation is further reinforced its existing strong energy relationships with alternative supplying countries, particularly Russia, where it has secured oil at discounted rates.

Rare metals and resource control

The most significant aspect of China’s response lies in its restriction of rare metal exports, which will have far-reaching implications for global supply chains right across the technology sector. With China controlling approximately 90% of global refined rare metal output, imposing export controls on 25 important metals, such as tungsten, could affect everything from aerospace technology to consumer electronics.

The timing of President Trump’s subsequent overture to Ukraine for rare earth metals supply, in exchange for $300 billion in support, underscores the significance of this particular countermeasure.

The automotive sector has not been spared, with China implementing a 10% tariff on pick-up trucks and large cars made in the US. However, this measure’s impact may be limited given China’s relatively low import volume of American vehicles and its established automotive trade relationships with European and Japanese manufacturers.

Beijing’s strategy consistently targets sectors where alternative suppliers are readily available to it. In a move that signals Beijing’s willingness to use regulatory power as a trade weapon, the addition of PVH, owner of Calvin Klein and Tommy Hilfiger, to China’s ‘unreliable entity’ list represents a deliberate targeting of American consumer brands. The designation could lead to difficult challenges for these companies in the Chinese market, including potential fines, regulatory investigations, and complications with employee visas.

The Chinese policies mirror similar actions the US took through its entity list, highlighting the increasingly complex interplay between trade policy, regulatory oversight, and jingoism. Agricultural machinery tariffs deserve special attention. They align with China’s broader strategy of reducing dependence on foreign technology while building domestic capabilities. In recent years, China has significantly increased investments in the sector, making these tariffs more about protecting and promoting domestic industry than punishing US manufacturers.

The dual-purpose approach characterises much of Beijing’s response to US trade pressure. According to a research note by Julian Evans-Pritchard, head of China Economics at financial insight firm Capital Economics, China’s targeted measures affect approximately $20 billion worth of annual imports, representing about 12% of China’s total imports from the US. While this appears modest compared to the US’ $450 billion worth of targeted Chinese goods, Beijing’s selective response suggests a strategic approach aimed at maximising impact while maintaining economic stability.

Global implications and future outlook

The global implications of the trade dispute extend beyond bilateral relations. Restricting rare metal exports could create ripple effects throughout global supply chains, affecting industries from consumer electronics to defence manufacturing.

The global business community will watch closely as both nations prepare for potential negotiations, with Trump announcing plans to speak directly with Chinese President Xi Jinping.

The scheduled implementation of China’s measures on February 10 is a deadline that will reveal either a diplomatic breakthrough or a further deterioration in US-China trade relations. The current escalation represents more than just a trade dispute; it reflects deeper tensions between the world’s two largest economies as they navigate issues of technological supremacy, economic security, and global influence.

As this new chapter in the US-China trade war unfolds, one outcome may well be different speeds of innovation in an industry that has always used the word ‘global’ when discussing the rapid speed of technological change.

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The landscape of artificial intelligence witnessed a seismic shift in January 2025 as Chinese startup DeepSeek sent Silicon Valley into a tailspin, wiping billions off tech stock valuations and challenging the very foundations of how AI companies operate. In just 18 months since its founding, this Beijing-based company has achieved what countless others couldn’t: creating AI models that rival or surpass those from OpenAI, Google, and Anthropic while spending just a fraction of their budgets.

The startup reached new heights when its free AI assistant dethroned ChatGPT from the top spot in Apple’s US App Store, marking the first time a Chinese AI product has dominated the American market.

What makes the achievement particularly remarkable isn’t just the technological leap but how it has been accomplished – without the massive GPU farms, billion-dollar investments, or years of accumulated expertise that Silicon Valley deemed essential for AI advancement.

The immediate market response was dramatic and far-reaching. According to the South China Morning Post’s reporting, major tech stocks experienced significant declines, with industry leaders like Nvidia, Microsoft, and Meta seeing their valuations drop.

The reaction stems not just from DeepSeek’s technological achievements but also from what it implies about the billions already invested in AI infrastructure by US companies. The market’s response reflects a broader reassessment of the conventional wisdom that dominant AI development requires massive capital expenditure. While some analysts view this as a temporary market correction, others see it as a fundamental challenge to the business models of established AI companies.

What’s particularly significant is that many US tech companies have justified their soaring valuations based on assumptions that a capital-intensive approach to AI development creates an insurmountable competitive moat. However, it’s important to maintain perspective. Market volatility in the tech sector isn’t uncommon, and established players have weathered similar challenges. What makes this situation unique is the clear technological demonstration backing the market’s concerns, coupled with DeepSeek’s radically different approach to AI development and monetisation.

The technology behind the DeepSeek AI disruption

DeepSeek’s success isn’t merely about market positioning – it’s rooted in significant technical innovations detailed in The Algorithmic Bridge‘s analysis. Its approach to AI development prioritises efficiency over raw computing power, implementing several groundbreaking technical advances:

• Architecture innovations:
• Multi-head Latent Attention (MLA) significantly reduces memory bottlenecks in the transformer architecture
• Group Relative Policy Optimisation (GRPO) simplifies reinforcement learning while maintaining performance
• Elimination of complex systems like MCTS and PRM without sacrificing capability
• Optimisation strategies:
• Implementation of 8-bit precision quantisation for improved efficiency
• Strategic use of sparsity in model architecture
• Sophisticated Mixture of Experts approach that keeps only necessary parameters active during inference
• Multi-token prediction capabilities that effectively double inference speeds

Yet, it’s essential to maintain perspective. While DeepSeek has achieved impressive results with fewer resources, companies like Google and OpenAI may have unreleased advances of their own – but if so, why not release them, or at least, ‘tease’ their existence?. The Algorithmic Bridge notes that it’s challenging to know what top US labs have already trained but chosen to keep private.

Resource efficiency vs. scale

DeepSeek’s approach to resource utilisation represents a fundamental challenge to established thinking about AI development. Operating with fewer than 100,000 H100 GPUs – compared to Meta’s projected fleet of 1.3 million GPUs by late 2025 – the company has demonstrated that efficient architecture and innovative algorithms can potentially offset raw computational power.

Efficiency isn’t just about hardware. DeepSeek’s approach suggests a 10x improvement in resource utilisation compared to US labs when considering factors like development time, infrastructure costs, and model performance. However, this doesn’t necessarily invalidate the benefits of scale; instead, it suggests a more nuanced relationship between resources and results.

Open source strategy and market impact

DeepSeek’s commitment to open-source development and transparent research publication starkly contrasts the secretive approaches of major US tech companies. While this transparency has allowed the garnering of praise from venture capitalist Marc Andreessen (who called it “one of the most amazing and impressive breakthroughs”), it also raises questions about long-term competitive advantage.

Growing pains and infrastructure challenges

Despite its successes, DeepSeek faces significant challenges in scaling its operations. SCMP reports that the company’s sudden popularity led to severe infrastructure stress, resulting in server crashes and cybersecurity concerns that forced temporary registration limits. The company’s status page indicated its most extended period of outages in 90 days, coinciding with its rapid rise to prominence and the US timezones. The issues highlight the real-world challenges of scaling AI services, regardless of architectural efficiency.

While DeepSeek’s technology may be more resource-efficient, supporting a global user base requires robust infrastructure and security measures. The company’s response to these challenges, including temporary registration limits and rapid service restoration, demonstrates the difficulties of sudden scaling.

Geopolitical implications

The political dimension of DeepSeek’s rise cannot be ignored. Former US President Donald Trump’s characterisation of it as a “wake-up call” for American industry, as reported by SCMP, reflects broader concerns about technological competition between the US and China. However, the situation is more complex than simple national rivalry – it represents a fundamental challenge to established thinking about AI development.

Looking ahead

While DeepSeek’s achievements are remarkable, several questions remain unanswered. Can its efficient approach scale to meet growing demand? Will established players adapt their strategies in response? And how will this affect the broader AI industry’s development trajectory?

What’s clear is that DeepSeek has demonstrated an alternative path to AI advancement, prioritising algorithmic efficiency and open collaboration over raw computational power and secrecy. Whether this approach becomes the new paradigm or simply one of many viable strategies remains to be seen, but its impact on the industry is undeniable. The disruption may ultimately benefit the entire field, forcing a reevaluation of established practices and potentially leading to more efficient, accessible AI development methods.

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo. Explore other upcoming enterprise technology events and webinars powered by TechForge here.

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President Donald Trump has launched America’s largest-ever artificial intelligence initiative just 24 hours into his second term, announcing a $100 billion joint venture between OpenAI, Oracle, and SoftBank. The ambitious project, dubbed “Stargate,” signals a dramatic shift in US technology strategy, aiming to establish unprecedented domestic AI computing power through a massive network of advanced data centres.

The announcement from the White House’s Roosevelt Room outlined an ambitious plan that could potentially expand to $500 billion over four years. The initiative begins with ten data centres already under construction in Texas, demonstrating the project’s immediate momentum despite being announced early in Trump’s second term.

The US AI infrastructure investment comes at an important time when computing power has become a bottleneck for artificial intelligence development. This is particularly evident in OpenAI’s case, which has reportedly struggled to secure sufficient computing resources from its primary infrastructure provider, Microsoft.

At its core, Stargate represents a strategic move to bolster America’s position in the global AI race. The partnership structure reveals interesting dynamics in the tech industry. While OpenAI brings its AI expertise and growing demand for computing power, Oracle contributes its data centre capabilities, and SoftBank adds significant financial backing.

The venture will be open to additional investors, potentially expanding its scope beyond the initial $100 billion commitment. President Trump’s administration has taken several concurrent steps to facilitate the massive investment. These include:

1. Rolling back previous executive orders that imposed specific safety standards and requirements for government AI use,
2. Promising “emergency declarations” to allow Stargate to generate its electricity,
3. Appointing David Sacks, a venture capital investor, as AI adviser,
4. Pledging to remove barriers to data centre creation.

The project’s announcement has drawn attention to the complex relationship between Silicon Valley and Washington. Tech executives, including OpenAI’s Sam Altman, have shown increasing support for the administration, with several attending the presidential inauguration and occupying prominent positions at official events.

The alignment suggests tech companies’ strategic positioning to influence policy and secure favourable regulatory conditions. However, the initiative raises several questions. Not least of which is the relaxation of previous AI safety standards and accelerating development, which could create regulatory gaps.

While promising operational autonomy, the proposed “emergency declarations” for electricity generation lack specific detail about environmental impact and grid integration. The global context of this US AI infrastructure investment is particularly significant. The project directly responds to international competition, especially from China, in AI development.

However, it also highlights domestic tensions, as evidenced by the recent shift in OpenAI’s strategy from global infrastructure development to focusing on US-based facilities after concerns were raised about building infrastructure in the Middle East.

The scale of the investment also reflects the evolving understanding of AI infrastructure requirements. Modern AI systems, like OpenAI’s ChatGPT, require massive computing resources, and this investment suggests an acknowledgement that current infrastructure may be insufficient for future AI development needs.

The corporate dynamics are equally noteworthy. The agreement allowing OpenAI to seek additional data centre capacity beyond its Microsoft partnership indicates the scale of computing needs. There is also ongoing litigation between OpenAI and various content providers, including The New York Times, over the use of content in AI training.

The success of this massive US AI infrastructure investment will likely depend on several factors:

• The ability to quickly scale data centre construction and operation,
• The effectiveness of the proposed regulatory changes,
• The project’s ability to attract additional investors,
• The integration of new facilities into existing tech ecosystems,
• The management of environmental and energy concerns,
• The project’s contribution to maintaining US competitiveness in AI development.

As the initiative unfolds, it will be important to monitor its direct impacts on the environment, AI development capabilities and the broader implications for technology policy, industry relationships, and international competition in artificial intelligence.

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The dramatic 13-hour shutdown of TikTok in the US on January 19, 2025, followed by its swift restoration, has created a complex tapestry of political manoeuvring, technological implications, and national security debates that continue to shape the platform’s uncertain future in America.

The TikTok US ban reversal materialised through an unexpected champion: President-elect Donald Trump. His pledge to issue an executive order following his inauguration prompted the platform to restore service even before the formal order was signed. The development marks a striking evolution in Trump’s stance on the platform. He has transitioned from a vocal advocate for its ban during his first term to emerging as its potential saviour.

ByteDance’s challenge and Trump’s proposed solution

At the heart of the controversy lies ByteDance’s consistent reluctance to sell TikTok, notably its prized recommendation algorithm. Trump’s proposed solution – a 50-50 joint venture between ByteDance and American owners – represents a potential middle ground, although its feasibility remains questionable.

The proposal signals a significant shift in approach, attempting to balance national security concerns with the platform’s operational continuity. Multiple factors complicate the path forward. The existing law, signed by outgoing President Biden in April 2024, mandated ByteDance to sell TikTok to an owner from the US or its allies in 270 days. Trump’s executive order, while providing temporary relief, cannot unilaterally override this congressional mandate.

The legal reality is further emphasised by opposition from prominent Republican Senators Tom Cotton and Pete Ricketts, who argue against any extension of the ban’s effective date. The situation has attracted several potential buyers. A group led by billionaire Frank McCourt and Kevin O’Leary has submitted a formal bid, as has the AI search engine PerplexityAI. Reports have also suggested possible interest from Elon Musk, though he has maintained public ambiguity about any potential acquisition.

Musk’s Sunday statement opposing the TikTok ban on free speech grounds and criticising the imbalance between TikTok’s operation in America and X’s inability to operate in China adds another layer to the complex narrative.

Technical and operational challenges

The prospect of splitting TikTok’s US operations presents significant technical challenges. McCourt’s group has proposed purchasing TikTok’s US assets without the company’s algorithmic software. Historical attempts by tech giants like Meta and YouTube to replicate TikTok’s engagement mechanics have shown the difficulty of this approach. Creating an American-only version of TikTok could necessitate a new app for global users to access US content, adding further complexity to the platform’s operation.

What is understood so far is that the brief shutdown highlighted the important role of TikTok’s service providers. Despite the Biden administration’s apparent willingness to defer enforcement to the incoming Trump administration, service providers’ concerns about potential penalties – up to $5,000 per person with access to TikTok – led to the temporary cessation of services. Trump’s promise of liability protection for these providers proved important in restoring service.

Looking ahead: uncertain future

The resolution of TikTok’s US situation could unfold in several ways. The most likely scenario is a reprieve through Trump’s executive order, followed by intense negotiations over the proposed 50-50 joint venture structure. However, ByteDance’s historical resistance to selling, algorithmic complexities, and valuation challenges could complicate this path.

Alternative outcomes include a complete sale to American buyers, although this faces significant hurdles regarding algorithm ownership and operational continuity. The least likely but still possible scenario is a new legislative solution, but this would require substantial bipartisan support in a Congress that strongly backed the original ban.

Other nations grappling with similar concerns will watch the TikTok US ban reversal saga. India, which banned TikTok in 2020, maintains its firm stance, while European Union regulators continue to scrutinise the platform under their Digital Services Act.

The UK, Australia, and Canada also monitor the US situation as they consider their approaches to Chinese-owned technology platforms. In short, the eventual US resolution could serve as a template for other nations. If Trump’s joint venture model succeeds, it might offer a middle-ground solution for countries seeking to balance national security concerns with the platform’s popularity. Conversely, if the ban takes effect, it could embolden other nations to act similarly.

The situation transcends TikTok, potentially reshaping how nations approach technology platforms owned by geopolitical competitors. The outcome could establish precedents for handling foreign-owned apps, data sovereignty, and the balance between national security and digital innovation.

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