In short: Nvidia CEO Jensen Huang warned on the Dwarkesh Podcast that DeepSeek optimising its AI models for Huawei\u2019s Ascend chips instead of American hardware would be \u201ca horrible outcome\u201d for the United States, as the Chinese AI lab prepares to launch its V4 foundation model on Huawei\u2019s Ascend 950PR processor. The migration from Nvidia\u2019s CUDA to Huawei\u2019s CANN framework threatens to break the software-hardware dependency underpinning American AI dominance, even as US lawmakers push to place DeepSeek on the entity list for export control.<\/p>\n
Nvidia CEO Jensen Huang said on the Dwarkesh Podcast on Wednesday that if DeepSeek optimised its new AI models to run on Huawei chips rather than American hardware, it would be \u201ca horrible outcome\u201d for the United States. The warning frames the emerging partnership between China\u2019s most capable AI lab and its most advanced chipmaker as a direct threat to the technological leverage that has underpinned American AI dominance for the past decade.<\/p>\n
\u201cIf future AI models are optimised in a very different way than the American tech stack,\u201d Huang said, and as \u201cAI diffuses out into the rest of the world\u201d with Chinese standards and technology, China \u201cwill become superior to\u201d the US. The statement is notable because it comes from the CEO of the company that has benefited most from the current arrangement, in which virtually every frontier AI model in the world is trained on Nvidia GPUs using Nvidia\u2019s CUDA software framework.<\/p>\n
What DeepSeek is building<\/p>\n
DeepSeek is preparing to launch V4, a multimodal foundation model expected later this month. The Information reported earlier in April that V4 would run on Huawei\u2019s latest Ascend 950PR processor, while a separate Reuters report suggested the model had been trained on Nvidia\u2019s Blackwell chips, which would constitute a violation of US export controls. The two claims are not necessarily contradictory: a model can be trained on one set of hardware and deployed for inference on another.<\/p>\n
What makes the Huawei integration significant is the software migration behind it. DeepSeek has spent months rewriting its core code to work with Huawei\u2019s CANN framework, moving away from the CUDA ecosystem that Nvidia has spent two decades building into the foundation of AI development. CUDA\u2019s dominance has functioned as a second layer of American control over AI, beyond the chips themselves. Export restrictions can limit which Nvidia hardware reaches China, but as long as Chinese labs wrote their software for CUDA, they remained dependent on the Nvidia ecosystem even when using alternative processors. DeepSeek\u2019s move to CANN breaks that dependency.<\/p>\n
<\/p>\n TNW City Coworking space – Where your best work happens<\/p>\n A workspace designed for growth, collaboration, and endless networking opportunities in the heart of tech.<\/p>\n <\/a><\/p>\n DeepSeek\u2019s V3 model, launched in late 2024, was trained on 2,048 Nvidia H800 GPUs, a chip tailor-made for the Chinese market that was itself banned from sale to China in 2023. The company has already demonstrated that it can produce\u00a0frontier-competitive models<\/a>\u00a0with fewer resources than its American rivals. Its R1 reasoning model matched or exceeded the performance of models that cost orders of magnitude more to train. V4 would extend that approach by proving the company can do it without American hardware at all.<\/p>\n The hardware gap and why it may not matter<\/p>\n On raw performance, Huawei\u2019s chips are not competitive with Nvidia\u2019s best. The Ascend 910C, the predecessor to the 950PR, delivers roughly 60% of the inference performance of Nvidia\u2019s H100, a chip that is itself two generations behind Nvidia\u2019s current best. American chips are approximately five times more powerful than their Chinese equivalents today, and that gap is projected to widen to 17 times by 2027. Huawei is targeting 750,000 AI chip shipments in 2026, but its total production represents only 3 to 5% of Nvidia\u2019s aggregate computing power.<\/p>\n But Huang\u2019s concern is not about the current performance gap. He said on the podcast that even if China had inferior chips, it could still catch up with the US in AI development given its \u201cabundant energy\u201d and \u201clarge pool of AI researchers.\u201d The implication is that raw hardware performance is only one variable, and that software optimisation, researcher talent, and energy availability can compensate for silicon disadvantages. If V4 performs well on Ascend chips, it validates an alternative path for AI development that does not depend on Nvidia at any point in the supply chain.<\/p>\n The export control paradox<\/p>\n The situation exposes a tension at the centre of American chip export policy. Nvidia restarted production of the H200, a more powerful chip, for sale in China, as Huang confirmed in March. But China has been blocking H200 imports to protect Huawei\u2019s domestic chip business, and Nvidia\u2019s CFO has said the company has recorded no revenue from China H200 sales. The controls designed to limit China\u2019s AI capabilities are instead accelerating the development of a Chinese alternative.<\/p>\n DeepSeek\u2019s experience with its R2 model illustrates both the promise and the limits of the Huawei path. R2 was repeatedly delayed because of training failures on Huawei hardware. Chinese authorities had urged DeepSeek to train on domestic chips, but the company encountered stability issues that forced it to revert to Nvidia GPUs for training while using Huawei chips only for inference. The distinction matters: training is the most compute-intensive phase of AI development, and the fact that Huawei chips could not handle it reliably suggests the hardware gap is real. But inference, the phase where models serve users, is where commercial value is generated, and Huawei\u2019s chips appear adequate for that purpose.<\/p>\n Meanwhile, US lawmakers are pushing to tighten restrictions further. On Thursday, lawmakers and experts accused China of buying \u201cwhat they can\u201d and stealing \u201cwhat they cannot\u201d in the AI industry, and called for the government to evaluate placing DeepSeek, Moonshot AI, and MiniMax on the entity list for export control.<\/p>\n What Huang is really warning about<\/p>\n Huang\u2019s warning is ultimately about software-hardware co-design. Nvidia\u2019s dominance rests not just on making the fastest chips but on CUDA\u2019s position as the default development environment for AI. When researchers write code, they write it for CUDA. When startups build products, they build them on CUDA. When governments invest in AI infrastructure, they buy Nvidia GPUs because that is what the software requires. DeepSeek\u2019s migration to CANN threatens to create a parallel ecosystem in which none of that applies.<\/p>\n The\u00a0scale of Nvidia\u2019s business<\/a>\u00a0makes the stakes concrete. The company\u2019s market capitalisation exceeds $3 trillion. Its data centre revenue grew 93% year over year in its most recent quarter. Its chips power the training runs for virtually every major AI model outside China. If the most capable Chinese AI lab demonstrates that competitive models can be built without Nvidia, the argument for maintaining export controls weakens, the argument for buying Nvidia weakens, and the\u00a0geopolitical assumptions<\/a>\u00a0that have shaped AI policy for the past three years come under pressure.<\/p>\n None of this means Huawei is about to overtake Nvidia. The performance gap is large and growing. The R2 training failures demonstrate that Chinese hardware is not yet ready for the most demanding AI workloads. But Huang is not warning about today. He is warning about a trajectory in which DeepSeek proves the concept, other labs follow, and the CUDA moat that has made Nvidia the most\u00a0valuable company<\/a>\u00a0in the AI supply chain begins to erode.<\/p>\n The fact that the CEO of Nvidia is the one making this argument publicly suggests he believes the risk is no longer theoretical. DeepSeek\u2019s V4 will be the first major test. If a multimodal foundation model runs competitively on Huawei silicon, the warning Huang issued on Wednesday will look less like corporate lobbying and more like\u00a0the most consequential forecast<\/a>\u00a0in the AI chip war so far.<\/p>\n","protected":false},"excerpt":{"rendered":"In short: Nvidia CEO Jensen Huang warned on the Dwarkesh Podcast that DeepSeek optimising its AI models for…\n","protected":false},"author":2,"featured_media":399024,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[345,343,344,85,46,125],"class_list":{"0":"post-399023","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-artificial-intelligence","8":"tag-ai","9":"tag-artificial-intelligence","10":"tag-artificialintelligence","11":"tag-il","12":"tag-israel","13":"tag-technology"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/399023","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/comments?post=399023"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/posts\/399023\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media\/399024"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/media?parent=399023"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/categories?post=399023"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/il\/wp-json\/wp\/v2\/tags?post=399023"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}