NVIDIAs

Everyone is developing chips that compete with NVIDIA’s. They are in the wrong race

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Qualcomm advertisement on Monday that it is working on AI accelerator chips, which means there will be new competition for NVIDIA. The company that dominates the AI ​​hardware landscape is seeing a large group of competitors try to erode that position, but the problem for all of these companies is not the chips, but something else. A CUDA call. what has happened. Qualcomm has announced the AI200 chip, which will begin selling in 2026, and the AI250, which will do so in 2027. Both will be able to work in rack-type systems that have liquid cooling. Qualcomm servers may have up to 72 chips based on the Hexagon NPUs of the company’s Snapdragon SoCs. Inference yes, training no. The company has revealed that its chips focus on inference (the execution of AI models) and not training. Their rack-based systems will have lower operating costs than cloud system providers, Qualcomm says. Each rack consumes 160 kW, a figure comparable to the consumption of some racks based on NVIDIA GPUs. There are no details about the price of these chips, the cards or the racks that will integrate them, nor about how many NPUs can be offered in each rack. What we do know is that Qualcomm’s accelerator cards will support up to 768 GB of memory, more than what NVIDIA or AMD offer in their current models. according to CNBC. Chips for third parties. The other important point is that Qualcomm will sell its AI chips and other components separately, allowing large AI companies to “customize” their own racks based on Qualcomm chips. It is an identical philosophy to the one they have adopted in the world of their mobile SoCs. Investors viewed the news with exceptional optimism, and Qualcomm shares rose 11% in Monday’s session. NVIDIA dominates with an iron fist. In the AI ​​chip segment, the king is NVIDIA. The company is the absolute protagonist of this market and according to CNBC it maintains a 90% market share, which has allowed it to skyrocket its valuation to 4.5 trillion dollars. That dominance could now be threatened by the avalanche of chips that are arriving from various manufacturers. All against NVIDIA. AMD has its excellent Instinct, Google has your TPUsAmazon their TrainiumMicrosoft their Maia and Huawei has your Ascend. All of them make really striking proposals for NVIDIA chips, and little by little these solutions are being integrated into more and more data centers. But the real problem is not in the hardware, but in the software. The great challenge is to defeat CUDA. The de facto standard in the AI ​​industry that developers use It’s CUDAa platform that allows you to take full advantage of the capabilities of NVIDIA chips in the field of artificial intelligence. This hardware+software combination is much more mature than that of its competitors, who have the hardware part resolved (or are on the right track) but do not have a platform comparable to CUDA. AMD has ROCmwhich is especially interesting because it is Open Source, but at the moment its features still do not reach those of CUDA. Reinvent the wheel? CUDA has been on the market for almost two decades, which means that the majority of academic research and pioneering models—such as ImageNet—were written for CUDA. It is not a language, it is a vast collection of libraries, optimized frameworks (like cuDNN), debugging tools and a huge community. Developing a competitor is basically like reinventing the wheel, and migrations are expensive and companies and startups will not have an easy time assuming it. China is also in the fight. And of course, if there is another great protagonist in this race, it is China. The Asian giant, previously dependent on NVIDIA, is seeking to get rid of this manufacturer, and along with the development of advanced AI chips they are also trying to have its own AI software to surpass CUDA. In Xataka | AI is the best thing happening to nuclear fusion. The construction of ITER is already accelerating

Huawei already has his best strategy to end Nvidia’s domain in China

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In early 2025 NVIDIA had a fee in the Chinese chip market for artificial intelligence (AI) of nothing less than 95%. However, during the last weeks has dropped to 50%. This abrupt decrease is largely due to the export restrictions of chips for the The US government has imposedalthough it is also caused by the development of competition within China. Despite this unfavorable Nvidia scenario, it has something very important in its favor: CUDA (Compute Unified Device Architecture). Most of the AI projects that are currently being developed are implemented on CUDA. This technology brings together the compiler and development tools used by programmers to develop their software for NVIDIA GPUs, and replace it with another option in the projects that are already underway it is a problem. Huawei, who aspires to an important portion From this market in China, it has Cann (Compute Architecture for Neural Networks), which is its alternative to CUDA, but for the moment CUDA dominates the market. Huawei is going to position Cann as an open source tool kit This declaration of Li Guojie, a computer scientist from the Chinese Academy of Sciences that is considered an authority in China, Express clearly The important thing that are the tools that I have just mentioned in the ECOsystem of AI models: “China must develop an alternative system to achieve self -sufficiency in AI (…) Deepseek has had an impact on the CUDA ecosystem, but it has not overcome it completely because barriers persist. In the long term we need to establish a set of software tool systems for the controllables that exceed CUDA.” Xu Zhijun does not mention it expressly, but what his strategy pursues is to increase the competitiveness of the Huawei’s ecosystem This is undoubtedly one of the great challenges that China faces in this area, and probably its best option is Cann. During the last five months Huawei has launched two GPU for Ia Very competitive and is about to take a very important step: Cann will position as An open source tool kit. Its purpose is, According to Eric Xu ZhijunRotary President of Huawei, “to accelerate the innovation of developers and get the chips of the Asce Family to be easier to use.” Xu Zhijun does not mention it expressly, but what his strategy pursues in the background is to increase the competitiveness of the Huawei ecosystem attacking Nvidia where he is stronger. In addition, it has already begun to discuss with the main actors of the China’s AI industry, as well as with its commercial partners, universities and research institutions how Huawei should build their open source ecosystem. If this initiative thrives, and presumably will, it will represent a very important step forward on the road to China’s technological independence. Image | Hiilicon More information | SCMP In Xataka | Nvidia has to deal with the absolute distrust of several US legislators. His plan in China is in danger In Xataka | The US wants to end the chips for the Chinese that are sold abroad. And China knows how to defend oneself

Intel pull the towel with the chips for ia. Its general director acknowledges that Nvidia’s advantage is insurmountable

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“I think it is too late for us (to achieve the position of Nvidia in the field of artificial intelligence), Although we have other opportunities in this market (…) twenty or thirty years ago we were leaders. Now the world has changed. We are not among the ten main semiconductor companies. We have to be humble. “These words of Lip-Bu Tan, the Director General of Intel, have been collected by The Oregonian And they are aimed at company employees in a clear attempt to expose what challenges they face. The challenges with Those who are dealing Intel They exceed the other challenges that he has faced during his more than half a century of history. The leadership that has sustained for decades in the manufacturing industry of integrated circuits is in the hands of The Taiwanese company TSMC Since the mid -2000s. In addition, the stagnation during the last years of the PC market and the slowness with which Intel has participated in the AI industry have placed it in a very compromised position. In July 2024, the company that at that time led Pat Gelsinger gave a tremendous batacazo in the stock market. Their actions fell 30% in a few days and stabilized in the value they had in 2011. In addition, Intel lost $ 1.6 billion During the second quarter of 2024 and its year -on -year income fell by 1%. These circumstances triggered a crisis that still persists. Today China is a crucial support for Intel. Dram memories will be tomorrow Shortly after his arrival It was leaked that lip-bu so He planned to launch a new cut of the Intel template in a clear attempt to reduce their operating expenses, among which personnel costs or marketing expenses are counted. The figure that the company shuffled on this occasion amounted to 20% of its workforce, which in practice implied to dispense with approximately 20,000 workers. These people join the more than 15,000 employees of which Intel has dispensed with during the last months of 2024. In addition, since June 18 and throughout the month of July they will be forced to leave their jobs Between 8,000 and 10,900 workers Of the factories that this company has spread throughout the planet. However, presumably the most affected plant will be the largest of all: that of Oregon (USA). It is evident that Intel is going through a very difficult stage, although he still has some solid pillars to hold on. One of them is China. During the fiscal year of 2024, 29% of Intel’s turnover came from China, compared to the 24% of the US This Asian country is the largest market in which Intel is present. During the fiscal year of 2024 29% of its turnover He came from Chinacompared to 24% of the US. And is that of the 53,100 million dollars that This company entered Last year no less than 15,400 million arrived from China. These figures reflect very clearly how important the country led by Xi Jinping for Intel is. And also how sensitive it is to the geopolitical context. An important part of the Intel business is supported by the commercialization of relatively old integrated circuits that come from their mature lithography nodes. They are not at all avant -garde semiconductors, but they are still necessary. At the current tension situation between the US and China for this last country These mature integrated circuits are crucial. Chinese chip designers and manufacturers are capable of supply your own market With the mature chips needed by appliances, telecommunications or cars equipment, among other industries. However, many users, research centers and universities in China continue to use software for X86 and X86-64 processors, so at the moment they cannot do without the CPUs designed to execute it. Intel is currently benefiting from this need, although he is preparing another bet. An a priori accurate bet. And this American company has founded the Japanese investment group SoftBank A company specialized in the design and manufacture of memory chips. His name is Saimemory and he was born expressly to compete from you to you with SK Hynix, Samsung and Micron Technology. Your plan consists in developing A new type of dram memory Stacked high from some patents prepared by Intel and several Japanese research centers, among which is the University of Tokyo. Intel and Softbank have proposed to complete the development of a prototype and evaluate its viability from a technical point of view by 2027. Image | Intel More information | The Oregonian In Xataka | Intel has confirmed that the 20A node will be skipped to reduce expenses. The 18A node will enter production in 2025

NVIDIA’s story is that of a survivor when all its competitors disappeared or were bought

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In 1998 NVIDIA was on the verge of go bankrupt. The rivalry that graphics chip manufacturers sustained during the 90s of the last century and the first decade of the current one killed many of them. In fact, as Tae Kim explains to us in the highly recommended essay book ‘The NVIDIA Way’only the company led by Jensen Huang survived in a saturated industry that still suffered from obvious immaturity. During the second half of the 1990s, between 80 and 100 companies competed in the PC graphics market, as Kim confirms in his work. Some of them were well known to users, such as Matrox, 3dfx Interactive, S3 Graphics, ATI Technologies, Hercules, Cirrus Logic, Intel, Trident, Number Nine Visual Technology or Rendition, while others were fighting to make their way in a market whose size It was at that time much smaller than today. Tae Kim argues that only NVIDIA has survived for one reason: it is the only company of all those I have mentioned so far in this article that remains as it was at that time. Most of them no longer exist, and those that remain have either been bought by other companies, such as ATI Technologies, or have had an unstable presence in the PC graphics hardware market and have made a living from other businesses, such as Intel. Jensen Huang is where he is thanks to his perseverance and intuition In his book Tae Kim assures that NVIDIA has overcome the critical moments it has faced thanks to Jensen Huang. Many of the decisions this executive has made during his career have been guided by ‘The innovators’ dilemma’one of his favorite books. Its author, American university professor Clayton M. Christensen, maintains that not dedicating the resources necessary for innovation It leaves the way free to do so for other companies that can afford to risk and bet everything on innovation with the purpose of consolidating themselves in the market. Jensen Huang has always been attentive to both talent coming from universities and strengthening his competitors. Christensen’s teachings have inspired Jensen Huang and helped him define NVIDIA’s business strategy, but, according to Kim, the company is still competing today thanks to two qualities of Huang: his perseverance and his intuition. In 1998, TSMC, which already then manufactured NVIDIA chipsran into a production problem. The latter company was running out of money, but Jensen Huang reacted and convinced three of the PC graphics card manufacturers he worked with. “Our technology is good. We will give you a 10% discount on the IPO when we go public. You just have to give us some money now,” Huang promised them. And it worked. His conviction and firm belief in the potential of his products got NVIDIA out of the quagmire, but the recipe for his success has other ingredients that we cannot ignore: his intuition and his good eye when it comes to recruiting talent. Huang has always been attentive to both talent coming from universities and strengthening his competitors. The signing of Dwight Diercks proves it. Jensen Huang followed Scott Sellers closely before he co-founded 3dfx Interactive. When the latter company went bankrupt in 2000 and was bought by NVIDIA, Huang questioned Sellers: “Which engineers are really good among all those who have been part of your team? Who are the stars?“Sellers did not hesitate to praise Dwight Diercks. And he ended up at NVIDIA. Jensen Huang is the alma mater of his company, but it is clear that he is fully aware of how essential the people he works with are. The Nvidia Way: Jensen Huang and the Making of a Tech Giant (English Edition) *Some prices may have changed since the last review Image | NVIDIA Bibliography | ‘The NVIDIA Way’by Tae Kim In Xataka | We can forget about AI without hallucinations for now. NVIDIA CEO explains why

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