- Alibaba stock surges on AI ambitions: Shares of Alibaba jumped about 8–10% to a four-year high after the company unveiled plans to boost its investment in artificial intelligence beyond an already massive $50+ billion budget, coupled with news of a partnership with Nvidia [1] [2]. Investors cheered the move, sending Hong Kong-listed shares up nearly 10% and U.S. ADRs sharply higher as well [3].
- CEO signals bigger AI spend: Alibaba CEO Eddie Wu said the pace of AI development “far exceeded our expectations” and pledged to increase AI spending even further [4]. Earlier this year Alibaba had earmarked ¥380 billion (≈$53 billion) over three years for AI infrastructure, and it now plans to top that figure to keep up in the global tech race [5].
- Nvidia partnership to power “physical” AI: Alibaba announced a strategic alliance with Nvidia to integrate the U.S. chipmaker’s cutting-edge AI development tools (for robotics, autonomous driving and more) into Alibaba Cloud [6]. Through the deal, Alibaba will offer Nvidia’s “Physical AI” software – which creates 3D digital environments to generate synthetic training data – to its cloud customers, accelerating AI model training for real-world applications [7]. Financial terms weren’t disclosed, but the tie-up brings together the world’s leading AI chip supplier and a major cloud/AI player [8].
- Global cloud expansion and new AI models: To support its AI push, Alibaba is opening new data centers in Brazil, France and the Netherlands (a first for those regions) with more centers planned across Asia and the Middle East in the coming year [9]. Its cloud unit just debuted Qwen3-Max, a colossal AI language model with over 1 trillion parameters touted as Alibaba’s most powerful yet [10]. Qwen3-Max is optimized for coding and “autonomous agent” tasks, and Alibaba claims it outperformed rival models like Anthropic’s Claude on certain benchmarks [11] [12]. The company also rolled out Qwen3-Omni, a multimodal AI system for immersive AR/VR applications (e.g. smart glasses and in-car assistants) [13].
- Nvidia on a deal spree (OpenAI and Intel): The Alibaba pact comes just days after Nvidia’s own blockbuster moves. The Silicon Valley firm agreed to invest up to $100 billion in OpenAI (maker of ChatGPT) and supply it with advanced data-center chips, in a partnership to build out what CEO Jensen Huang calls the “biggest AI infrastructure project in history” [14] [15]. Nvidia also took a $5 billion stake in Intel, making it one of Intel’s largest shareholders, as part of a plan to co-develop next-generation PC and data-center chips [16] [17]. These deals underscore Nvidia’s determination to dominate AI computing – and they briefly sent Nvidia’s stock to record highs (shares jumped ~4% on the OpenAI news) [18].
- Rising tide lifts AI players: Alibaba’s and Nvidia’s bold moves reflect a global AI arms race among tech giants. Alibaba’s expanded AI budget aligns with a broader surge of investment – its CEO predicts $4 trillion will be spent on AI worldwide over the next five years [19]. In China, Alibaba is racing against rivals like Tencent and upstart lab DeepSeek in a fierce competition to build the best AI platforms [20]. Internationally, companies like Microsoft, Google, and Amazon are pouring billions into AI as well (Microsoft’s multibillion-dollar OpenAI stake and massive “Stargate” AI data centers project with partners is one example [21]). Investors have taken notice: Alibaba is now viewed as an attractive “AI play” with a relatively modest valuation (around 20× forward earnings) compared to Nvidia’s richer multiples [22]. Notably, star tech investor Cathie Wood’s ARK funds bought Alibaba stock for the first time in 4 years amid the AI optimism, scooping up over $16 million of shares as the stock surged to multiyear highs [23].
Alibaba Stock Soars on Massive AI Spending Plan
Alibaba’s latest pivot to artificial intelligence has ignited its stock and signaled to the market that the Chinese tech giant is “all in” on AI. At its annual Apsara Conference (Sep 2025), CEO Eddie Wu underscored that AI industry growth “far exceeded our expectations”, with demand for AI infrastructure outpacing what Alibaba had anticipated [24]. In response, Wu announced Alibaba will boost its investment in AI beyond the hefty ¥380 billion (about $53 billion) three-year budget it set earlier this year [25]. While he didn’t put a new number on the commitment, the message was clear: Alibaba sees AI as a core priority alongside its e-commerce empire [26], and it’s prepared to spend big to stay competitive.
The market reacted swiftly. Alibaba’s Hong Kong–listed shares soared nearly 10% on the announcements, hitting their highest level in almost four years [27]. U.S.-listed shares of Alibaba (ticker: BABA) similarly leapt in New York trading, as investors welcomed the company’s aggressive stance on AI after a period of relative stagnation. The rally has been fueled by optimism that Alibaba’s AI push can re-energize growth – a sentiment echoed by high-profile investors. Cathie Wood’s ARK Invest, for example, just reopened positions in Alibaba after a four-year hiatus, buying over $16 million worth of shares as the stock surged on the AI news [28]. Ark’s move is seen as a vote of confidence that Alibaba’s AI foray could unlock significant upside, especially given the stock’s prior underperformance and attractive valuation.
Alibaba’s strategic shift comes amid intense competition in China’s tech sector. The company has been locked in an AI race with local peers including social media/gaming titan Tencent and a fast-rising AI research shop called DeepSeek [29]. Both rivals have been investing heavily in AI research and products, pressuring Alibaba to accelerate its own efforts. (DeepSeek, in particular, gained prominence with its advanced AI models and has operated somewhat like an independent research lab, though Alibaba’s latest model releases aim to leapfrog DeepSeek’s technology [30].) By dramatically increasing its AI budget and resources now, Alibaba is signaling it won’t cede ground to these competitors. As Eddie Wu put it, the company must “keep up” with the blistering pace of AI development – a point driven home by his projection that global AI investment could hit $4 trillion over the next five years [31].
Critically, Alibaba’s bet on AI isn’t just talk – it’s already showing up in its business metrics. The company’s cloud division (Alibaba Cloud) recently posted a 26% surge in revenue, helping drive strong quarterly results on the back of new AI services [32]. This suggests Alibaba’s heavy spending on AI R&D and infrastructure is beginning to pay off in commercial terms, monetizing via cloud customers and enterprise clients adopting its AI solutions. The stock market’s enthusiastic reaction reflects a belief that AI could be Alibaba’s next growth engine, balancing its maturing e-commerce segment with new momentum in cloud and tech services.
Inside Alibaba’s Alliance with Nvidia
A centerpiece of Alibaba’s AI announcement was a new partnership with Nvidia, the U.S. chipmaker whose GPUs are effectively the “brains” of most advanced AI systems. This collaboration is focused on what Alibaba calls “physical AI” capabilities – essentially the tools and environments needed to train and deploy AI models for real-world applications like robotics, autonomous vehicles, and smart factories. Concretely, Alibaba will integrate Nvidia’s AI development software into its cloud platform [33]. That includes Nvidia’s cutting-edge robotics and simulation toolkits and its Physical AI software stack, which can construct lifelike 3D replicas of real-world environments to generate synthetic data for training AI models [34]. In practice, this means an Alibaba Cloud customer building, say, a warehouse robot or a self-driving car algorithm could use Nvidia’s virtual world simulations (via Alibaba’s platform) to train their AI systems more efficiently, before testing them in the physical world.
The significance of the Nvidia tie-up is twofold. First, it pairs Alibaba with the world’s premier AI chip and tools provider, ensuring Alibaba and its clients have access to top-tier technology as they build out AI applications. Nvidia’s GPUs and software libraries are considered essential for heavy AI workloads, so this partnership helps Alibaba attract AI developers to its cloud ecosystem with the promise of world-class infrastructure. Second, it’s a notable collaboration amid U.S.–China tech tensions. While the U.S. government has restricted exports of Nvidia’s most advanced chips to China, here we see an American tech giant working closely with a Chinese firm in the AI arena (albeit on the software side). Alibaba did not specify if its new data centers will use Nvidia chips directly [35], likely mindful of export rules. But by leveraging Nvidia’s software and know-how, Alibaba can still benefit from Nvidia’s expertise even as it develops its own AI chips domestically.
Indeed, Alibaba has been pursuing a dual strategy: partner where it can, but build its own capabilities where it must. In response to chip export curbs, Alibaba’s in-house semiconductor unit (T-Head) has been designing AI chips for its data centers. Those homegrown chips reportedly rival Nvidia’s in performance – comparable to Nvidia’s top-tier GPUs – and now account for the majority of AI silicon used in China’s data centers [36]. This means Alibaba is becoming more self-reliant for core hardware. Still, Nvidia’s software tools remain invaluable, and the partnership suggests both companies see mutual benefit. “Alibaba’s 2025 Apsara Conference demonstrated strong results from years of AI investment,” observed Lian Jye Su, chief analyst at Omdia, adding that the new overseas data centers and Nvidia alliance will broaden Alibaba’s reach among global AI developers and enterprise users [37] [38].
Alongside the Nvidia deal, Alibaba detailed a sweeping cloud infrastructure expansion. It will open new data centers in Brazil, France, and the Netherlands – the first time Alibaba Cloud enters those countries – with more facilities planned in Mexico, Japan, South Korea, Malaysia and Dubai over the next year [39]. This expansion will grow Alibaba’s footprint beyond its current 91 data centers across 29 regions [40], marking a significant global push. The timing is strategic: Alibaba clearly wants to court international AI business, positioning itself as a global cloud contender against the likes of Amazon AWS, Microsoft Azure, and Google Cloud. By planting data centers worldwide (often necessary to serve local customers with low latency and comply with data regulations) and partnering with Nvidia, Alibaba is strengthening the appeal of its platform to a broader audience of AI startups, research labs, and multinational companies.
Finally, Alibaba unveiled the fruits of its AI research with new products like Qwen3-Max, its largest-ever large language model. With over 1 trillion parameters, Qwen3-Max leaps into an elite club of ultra-large AI models [41]. Alibaba’s CTO Zhou Jingren highlighted that this model excels at code generation and features “autonomous agent” capabilities – meaning it can make decisions and take actions toward a user-defined goal with minimal human prompts [42]. Notably, Alibaba claims Qwen3-Max outperforms rival models (including Anthropic’s Claude and DeepSeek’s latest system) on certain benchmark tests [43]. If accurate, that’s a significant achievement, signaling Alibaba’s AI labs can keep up with (or beat) some of the best in the field. Beyond Qwen3-Max, Alibaba also rolled out Qwen3-Omni, a multimodal AI model designed for augmented and virtual reality scenarios – think smart glasses, VR headsets, or “intelligent cockpit” systems in cars [44]. This suggests Alibaba is exploring AI applications beyond text/chatbots, venturing into AI that can interpret images, sensor data, and real-world context. All together, the Nvidia partnership plus Alibaba’s own AI models and new data centers form a coherent strategy: build top-notch AI capabilities and deliver them at global scale.
Nvidia’s Latest Moves: From OpenAI to Intel
Alibaba isn’t the only one in the spotlight – its new partner Nvidia has been on an extraordinary deal-making streak that underlines just how central the company has become in the AI era. Often called the “brains of AI”, Nvidia’s chips power the vast majority of AI model training and deployment worldwide [45]. But Nvidia is now leveraging its dominance to do more than sell chips; it’s forging alliances that blur the line between chipmaker and AI platform provider.
Just days before the Alibaba tie-up, Nvidia announced a landmark partnership with OpenAI, the famed creator of ChatGPT. In late September, Nvidia said it will invest up to $100 billion in OpenAI and concurrently serve as OpenAI’s key supplier of advanced GPUs for building out new AI supercomputers [46]. The deal involves Nvidia taking non-voting equity in OpenAI and OpenAI committing to purchase enormous quantities of Nvidia’s hardware – at least 10 gigawatts of GPU capacity in the coming years [47]. (For context, that’s a computing power equivalent to what millions of high-end PCs would provide, and it requires electricity on the scale of powering ~8 million U.S. homes [48].) Nvidia’s CEO Jensen Huang hailed the arrangement as enabling OpenAI to undertake the “biggest AI infrastructure project in history,” and investors applauded – Nvidia’s stock jumped over 4%, hitting a record high on the announcement [49]. The tie-up marries the most valuable AI hardware company with one of the most influential AI software companies, in a symbiotic relationship: OpenAI gains guaranteed access to cutting-edge Nvidia chips (plus a massive cash infusion), while Nvidia secures a long-term customer and a stake in AI’s frontier. Some analysts have noted concerns about the “circular” nature of the deal – essentially Nvidia investing money that largely comes back to it via chip sales [50] – and it’s true such a close partnership between a supplier and buyer could invite antitrust scrutiny [51]. But both firms argue the alliance will accelerate innovation and infrastructure at a scale neither could achieve alone.
Around the same time, Nvidia made waves with a bold move in the semiconductor industry: taking a $5 billion stake in Intel. In mid-September, Nvidia agreed to buy roughly 4% of Intel’s shares (through newly issued stock), instantly becoming one of Intel’s largest shareholders [52] [53]. The deal was part of a broader collaboration to develop new chips, aiming to combine Nvidia’s strengths in graphics and AI processors with Intel’s expertise in PC and server CPUs. Importantly, the partnership stops short of Nvidia outsourcing its GPU manufacturing to Intel’s factories – a step many had speculated about – but it does involve the two companies co-designing “multiple generations” of future chips for data centers and personal computing [54] [55]. For Intel, which has struggled in recent years to regain its technological edge, Nvidia’s backing was a monumental confidence boost: Intel’s stock skyrocketed 23% on the news of Nvidia’s investment [56]. One analyst called it a “massive game-changer for Intel,” potentially revitalizing the one-time industry leader by plugging it into the AI boom [57]. For Nvidia, the strategic rationale is twofold: it shores up a potential manufacturing ally (Nvidia could someday leverage Intel’s chip fabs to diversify beyond TSMC in Taiwan [58]), and it ensures a key player in the computing ecosystem remains viable and aligned with Nvidia’s AI-centric roadmap. In essence, Nvidia is betting that a stronger Intel (under its influence) will further cement Nvidia’s own dominance – a move almost unthinkable a few years ago, given the historical rivalry between the two Silicon Valley icons.
Between the OpenAI and Intel deals, Nvidia has signaled that it intends to be indispensable across the AI landscape. The company is flush with cash from booming GPU sales and a sky-high market capitalization (over $1 trillion), and it’s reinvesting that into securing its future. Whether it’s by vertically integrating with AI software leaders (OpenAI) or horizontally strengthening the chip supply chain (Intel), Nvidia is ensuring that wherever massive AI workloads are running, Nvidia is at the center of the action. Little wonder then that Alibaba chose to partner with Nvidia – the chipmaker is effectively becoming the platform upon which much of the AI world is being built, from West to East.
AI Arms Race: Big Tech Bets and Competitive Landscape
Alibaba’s AI escalation and Nvidia’s maneuvers are part of a much larger picture – a veritable arms race in artificial intelligence unfolding globally. In this race, scale and speed are king: companies are pouring unprecedented sums of money to develop AI models, acquire data center capacity, and secure scarce talent. Eddie Wu’s $4 trillion estimate for worldwide AI investment over five years [59] may sound astronomical, but when you tally up the commitments from the biggest players, it starts to look plausible.
In the United States, Microsoft has invested billions into OpenAI (reportedly about $13 billion for a stake and cloud credits) and is partnering with it to deploy AI capabilities across Microsoft’s Azure cloud and software products. Microsoft, along with partners like Oracle and SoftBank, even unveiled plans for a $500 billion initiative dubbed “Project Stargate” to build cutting-edge AI data centers around the world [60] – highlighting the gargantuan scale of cloud infrastructure needed for the next generation of AI. Google, not to be outdone, has been developing its own AI supercomputers and proprietary AI chips (TPUs) to power systems like its PaLM language model and Bard chatbot. Google’s strategy mixes in-house R&D (it famously invented the “Transformer” AI architecture that spawned modern language models) with acquisitions and hefty spending to maintain its AI leadership in search and cloud services. Amazon is likewise in the fray: its AWS cloud division offers AI services and custom AI chips (Inferentia and Trainium), and Amazon has invested in AI startups (like a $4 billion stake in Anthropic in 2023) to augment its capabilities. Even social media giant Meta (Facebook) open-sourced a 70 billion-parameter model (LLaMA) and is reportedly building new AI chips, underscoring that every tech titan sees AI as critical to their future.
Crucially, this AI competition is not confined to the West. In China, beyond Alibaba’s efforts, Baidu – often called China’s Google – has developed its ERNIE large language models and is integrating AI into search, cloud, and autonomous driving. Tencent has ramped up investment in AI research (from recommendation algorithms in its apps to foundational models) and offers cloud AI solutions, while also backing startups in the space. And then there are specialized AI firms like DeepSeek, which emerged as an early leader in Chinese large language models by operating more like an independent research outfit. DeepSeek’s models at one point were said to dominate usage in China, though Alibaba and others are now fast-challenging it [61]. The Chinese government, for its part, is pushing an agenda of self-sufficiency in key technologies, AI included – which means companies like Alibaba not only have market incentives but also policy support to develop domestic AI tech (especially given U.S. export restrictions on high-end chips).
One twist in this East-West tech race is the interplay of competition and collaboration. We see Chinese firms racing to match or beat Western AI capabilities (Alibaba’s Qwen models vs. OpenAI’s GPT or Anthropic’s Claude, for example), yet we also see collaboration across borders – such as Alibaba using Nvidia’s tools, or global research benchmarks where Chinese and Western models vie for the top spots. Geopolitical tensions (like U.S. sanctions on Chinese chip imports) have certainly shaped these dynamics; Alibaba accelerating its chip R&D to replace banned Nvidia chips is one direct result [62]. But the Nvidia-Alibaba partnership also shows a pragmatic streak: both sides stand to gain commercially by working together, politics notwithstanding. In the long run, the “AI arms race” is not a zero-sum game – advancements in AI by one player often spur others to step up, potentially accelerating the overall progress. The challenge for every company involved is balancing cooperation and competition, all while navigating regulatory scrutiny (e.g. antitrust concerns for Nvidia’s deals, or government oversight of AI algorithms) and ethical considerations in AI development.
From a high level, what’s clear is that no major tech company wants to be left behind. AI is viewed as the transformative technology of this era – akin to how the internet or mobile computing were in prior decades – and it’s driving a cycle of ever-growing investment. Alibaba’s $50+ billion pledge, Microsoft and Nvidia’s mega-deals, Google’s and Amazon’s internal spendings, startups raising billions for AI ventures – these all feed into each other. As AI systems become more capable, new applications (and revenue opportunities) emerge, which then justify further investment. It’s a self-reinforcing loop, and the stakes (and price tag) keep rising. For businesses and consumers, this arms race promises breakthroughs from advanced AI assistants and autonomous vehicles to smart cities and biotech discoveries. But it also means the industry could concentrate around a few platforms (like Nvidia’s hardware or OpenAI’s models), raising questions about openness and competition. We’re witnessing the rapid remaking of the tech landscape around AI, and companies like Alibaba and Nvidia are determined to secure their place at the top.
Outlook: Two Stocks, One AI Future?
For investors, the recent developments underscore two different ways to ride the AI wave – exemplified by Alibaba and Nvidia. Alibaba’s stock (BABA) now offers a compelling “AI value” narrative: it’s a company undergoing an AI-driven transformation, with a huge user base (in e-commerce, cloud, logistics, etc.) on which to deploy AI, and a stock trading at a relatively modest valuation. In fact, some analysts point out that Alibaba’s forward price-to-earnings ratio, around the low 20s, looks low compared to pure-play U.S. AI companies – making it a potentially underpriced AI contender [63]. The recent rally suggests the market is starting to rerate Alibaba as not just an e-commerce giant but as a serious AI infrastructure and cloud player. If Alibaba successfully executes on its plans – e.g. rolling out competitive AI services, filling its new data centers with paying customers, and maybe even exporting Chinese AI innovations globally – there could be further upside. However, Alibaba will need to prove that its massive spending actually yields world-class AI products and doesn’t just burn cash. The company faces formidable rivals (Tencent, Baidu, etc.) at home and will encounter entrenched competitors abroad. There’s also the macro backdrop: China’s regulatory environment and U.S.–China trade tensions add uncertainty to any Chinese tech investment. Still, as Cathie Wood’s recent bet highlights, some see Alibaba’s risk/reward as attractive now that it’s all-in on AI – especially relative to the sky-high expectations (and valuations) riding on U.S. AI leaders.
Nvidia’s stock (NVDA), meanwhile, has been the undisputed poster child of the AI boom. It surged over 200% in the past couple of years to a trillion-dollar market cap as Nvidia’s earnings exploded (driven by insatiable demand for its AI chips). Owning Nvidia has so far been akin to owning the “picks and shovels” of the AI gold rush – as long as AI model training and deployment keep growing, Nvidia keeps selling more GPUs. The recent strategic deals (OpenAI, Intel, Alibaba, and others) aim to extend Nvidia’s dominance for years to come, which is a bullish sign. Nvidia is not resting on the laurels of current-generation chips; it’s knitting itself into the very fabric of future AI ecosystems. That said, much of this optimism is already reflected in the stock’s rich valuation. Nvidia trades at a triple-digit P/E, pricing in years of rapid growth ahead. Any hiccup – whether it’s a supply constraint, a competitor’s breakthrough (AMD is pushing its own AI chips; startups are exploring novel AI accelerators), or regulators throwing wrenches into Nvidia’s deals – could introduce volatility. Moreover, by taking on roles beyond chip supplier (as an investor and partner in other companies), Nvidia assumes new kinds of risk. For instance, the OpenAI investment ties part of Nvidia’s fortunes to one AI lab’s success (and OpenAI itself faces intense competition from Google, Meta, Anthropic, etc.). Still, most analysts see Nvidia as uniquely positioned to benefit from the AI secular trend, and the company’s recent actions only reinforce that view. In the words of one market observer, Alibaba’s burgeoning AI momentum “contrast[s] with Nvidia’s much richer multiple” – implying that Alibaba might have more room to run [64] – but it’s Nvidia’s technology that in many ways makes all these AI ambitions possible.
In sum, the Alibaba-Nvidia partnership captures the spirit of this moment in tech: collaboration between a software/cloud giant and a hardware powerhouse to push the frontier of AI. Each company brings something to the table – Alibaba its global cloud platform and huge datasets, Nvidia its unparalleled chips and AI toolchain. Together, they hope to create new value (and new revenue) in an AI-driven economy. For the public and businesses, the developments are largely positive: faster advances in AI capabilities and more widespread access via cloud services. We may soon see Alibaba Cloud offering sophisticated AI-as-a-service globally, powered by Nvidia’s tech – giving businesses alternatives beyond the Western cloud providers. And as Alibaba refocuses on innovation (after a few challenging years of regulatory crackdowns in China), it could emerge as a more modern, diversified tech leader.
From a broader lens, the fact that Alibaba is partnering with an American company like Nvidia also suggests that, at least in the corporate realm, the pursuit of AI transcends geopolitical rivalries to some extent. Despite trade wars and tech export bans, companies find ways to work together when incentives align. The ultimate driver here is that AI is poised to transform industries and generate enormous economic value – no one wants to fall behind. Alibaba’s stock soaring on its AI news, and Nvidia’s stock soaring on its deals, both send the same message: the market rewards those who aim big in AI. Going forward, we can expect more landmark partnerships, bigger investment pledges, and probably more eye-popping market reactions as the AI revolution continues to unfold. Investors and observers should brace for rapid developments, because as Alibaba’s CEO noted, the speed of the AI industry has exceeded all expectations – and it’s only speeding up [65].
Sources:
- Reuters – “Alibaba shares leap on Nvidia partnership, data center plans” (Liam Mo & Eduardo Baptista) [66] [67] [68] [69] [70]
- Reuters – “Nvidia to invest up to $100 billion in OpenAI, linking two AI titans” (Deepa Seetharaman & Akash Sriram) [71] [72] [73]
- Reuters – “Nvidia takes $5 billion stake in Intel, offers chip tech in new lifeline” (Stephen Nellis et al.) [74] [75] [76]
- TechCrunch – “Alibaba to offer Nvidia’s physical AI development tools in its AI platform” (Ram Iyer) [77]
- Nasdaq/RTT News – “Nvidia Strikes Alibaba Deal As AI Race Heats Up” [78] [79] [80]
- Bloomberg – “Cathie Wood Buys Alibaba After Four Years in China Comeback” (Henry Ren) [81]
- Bloomberg – “Alibaba Shares Soar After Hiking AI Budget Past $50 Billion” (Luz Ding) [82]
- Reuters – “Alibaba shares leap… (continued)” [83] [84] [85] (Omdia analyst quote and product details)
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