NVIDIA

Nvidia, TSMC and SK Hynix are the most powerful chip companies on the planet. None can allow any of the others to fall

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Nvidia dominates the global chips market for artificial intelligence (AI) with a fee that during the last three years has oscillated between 80 and 94%, according to Fourweekmba. Your leadership is supported by A very competitive hardware and a software ecosystem in which CUDA (Compute Unified Device Architecture) It has an essential role. This technology brings together the compiler and development tools used by programmers to develop their software for NVIDIA GPUs. However, the company led by Jensen Huang has a fundamental partner: TSMC. Nvidia designs the chips for AI and this manufacturer of Taiwanese semiconductors, the eldest of the planet with A global quota close to 60%it produces them. Its iron leadership is the result of Its peak technology and its titanic production capacity. TSMC has many important clients, such as AMD, Qualcomm, MediaTak or Broadcom, among many others, but thanks to the AI ​​NVIDIA, it has established itself as Your second best customer Only behind Apple. Presumably TSMC is about to start MANUFACT 2 NM GPU For Nvidia, but this is not the only thing that this chips manufacturer is going to do for one of its best customers. And this Taiwanese company has decided to start An expansion plan for five years of its manufacturing capacity of integrated circuits using its advanced cowos packaging technology (Chip-on-Wafer-on-Substrate). According to Beth Kindigof the I/O Fund consultant, this technology will monopolize between 50 and 60% of the market in 2025 compared to 15% it supported during 2024. The synergy of these companies is indisputable The high demand for GPUs for AI with Blackwell MicroAritectura de Nvidia is largely responsible for the implementation of this plan. The company led by Jensen Huang can respond better to the needs of its customers and will see how its competitiveness is increased in a phase in which Depseek and other Chinese companies represent a challenge. In March 2024 TSMC officially announced which was building two cowos packaging plants in the town of Chiayi, housed in southern Taiwan. However, this is not all. He also shuffled the option to put a plant more specialized in this advanced packaging technology in Japan, presumably on the island of Kyushu, in which this company is currently building two semiconductor production plants of avant -garde. In any case, there is something else. And it is that Chiayi plants will be trained to work, in addition to the packaging cowos, With advanced Info and Soic technologies (System on Integrated Chips). Nvidia and TSMC synergy is indisputable, but this recipe requires a third ingredient: SK Hynix It is evident that TSMC wants to cover your back well and look to the future to prevent its production capacity from being threatened by a bottleneck. An interesting note: currently the Cowos packaging is being used with the AMD Instinct Mi250 chips and with the A100, H100, H200, B100 and B200 NVIDIA GPUs, as well as in its derivatives. The review used in these last two chips, the B100 and B200, is known as Cowos-L. Before the TSMC ends this year, you will be able to process no less than 60,000 wafers per month using its advanced packaging technology. The synergy of Nvidia and TSMC is indisputable, but this recipe requires a third ingredient: SK Hynix. This South Korean manufacturer of memory chips leads the HBM memories market (High Bandwidth Memory) that work side by side with the GPUs for ia with a shocking authority. Your market share Broken 70%so that the remaining 30% are distributed by Samsung and Micron Technology. After them, Chinese manufacturers of Yangtze Memory Technologies Co. (YMTC) and CXMT (Changxin Memory Technologies). At the end of 2024 SK Hynix took advantage of the celebration of an innovation forum organized by TSMC to publicize its mastery of the manufacture of HBM memories. According to SK Hynix itself Its MR-MUF process, which, in broad strokes, is a technology that makes possible a faster punch of the DRAM compared to the TC-NCF process that other companies use, has allowed it to achieve an efficiency 8.8 times higher than that of Samsung and Micron. This simply means that it manufactures its HBM chips much faster than its main competitors. SK Hynix is ​​manufacturing 12 -layer HBM3E memories on a large scale while Samsung and Micron have problems with their production As we can intuit, the speed at which a company that is dedicated to manufacturing semiconductors is capable of producing its integrated circuits deeply condition its competitiveness. It is evident that greater efficiency will allow you supply more guarantees to your customersespecially in an upward market like that of HBM memories. In addition, SK Hynix is ​​manufacturing 12 -layer HBM3e memories on a large scale while Samsung and Micron have problems with their production. In any case, both Samsung and SK Hynix are already working on the development of HBM4 memories with the purpose of catapulting their competitiveness. Here it is precisely where Nvidia appears. SK Hynix announced in October 2024 that he intended to deliver the first HBM4 memory chips to his clients during the second half of 2025. However, Jensen Huang asked him That the delivery advances. Chey Tae-Won confirmed itthe president of SK Group, so it is absolutely reliable information. Why does NVIDIA require so urgently the HBM4 chips? Simply because you need to support your chips for the most capable with the most available energy and energy efficiency memories. And in this field SK Hynix currently has the pan well grabbed by the handle. Image | TSMC In Xataka | South Korea fears US reprisals. To avoid their old lithography equipment, they take dust on a warehouse

Nvidia world leadership in chips for AI is brutal. In GPU for games directly has fulminated the competition

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Nvidia dominates the global chips market for artificial intelligence (AI) with a fee that during the last three years has oscillated between 80 and 94%, according to Fourweekmba. Your leadership is supported by A very competitive hardware and a software ecosystem in which CUDA (Compute Unified Device Architecture) It has an essential role. This technology brings together the compiler and development tools used by programmers to develop their software for NVIDIA GPUs. Most of the artificial intelligence projects that are currently being developed are implemented on CUDA, 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. AND Moore Threads and Cambricon Technologies They have muse and neuware respectively. Even so, the competitors of Nvidia will cost them a lot to break the leadership of Cuda. Nvidia has distributed 94% of GPUs for market games During the second quarter of 2025, 11.6 million graphics cards for PC and 21.7 million processors for desktop computers have been distributed throughout the planet, according to the US consultant Jon Pedie Research. By themselves these figures do not tell us just anything, but they acquire the relevance they deserve if we consider that they indicate that the distribution of graphics cards has grown by 27% and that of CPUs 21.6% compared to the first quarter of 2025. Distributed units allow us to train a very precise idea about market behavior It is important that we do not overlook that these figures quantify the distributed units, and not the units sold. However, there is a direct correlation between them, so the distributed units allow us to form a very precise idea About market behavior. Anyway there is a fact that is even more shocking than all we have collected so far in this article: NVIDIA has distributed no less than 94% of GPUs for market games during the second quarter of 2025, again according to Jon Pedie Research. AMD has been forced to settle for 6% of the distributed units, and Intel does not even appear in the report of this consultant because its presence is anecdotal. So are things in the graphic hardware market for PC. One more note to conclude: the rebound of distributed units of graphics and processors for PC during the second quarter of 2025 against the first responds in all likelihood to the need for stores and users to supply before Tariffs approved by the US government They entered into force. Image | Xataka More information | Jon Pedie Research In Xataka | Nvidia is ready for the chip for the need to survive in China. Who is not ready to let him sell is the US government

This company is China’s great hope to definitely dispense with Nvidia chips

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In China there are dozens of companies that are dedicated to the design of GPU for applications of artificial intelligence (AI). Stepfun, which belongs to Tencent Holdings; Infinigence ai; Siliconflow, from Huawei; Metax; Biren Technology; Focus me; Iluvatar Corex or Moore Threads They are some of the most important. However, currently One shines more than the others. In fact, as we have anticipated from the head of this article, this company is the best China asset when dispensing with the Nvidia chips. Although it is not as well known as Huawei or Moore Threads, Cambricon Technologies is one of the companies specialized in the design of GPU for AI with greater growth potential. In fact, he has received the approval of the Shanghai bag (China) to raise 560 million dollars. Will allocate them to the design of four chips for training and inference of AI models, and also to the development of an alternative to CUDAfrom Nvidia. To this company everything seems to be going well. And is that during the last twelve months The value of its actions has tripled. The strategic role of AI for China in its technological and commercial war with the US supports Chinese companies dedicated to the hardware design for AI and the development of large language models. However, there is more than promises to boost the business not only of Cambricon Technologies, but also that of the other Chinese companies that design integrated circuits for AI: the Chinese government has decided to force the data centers that belong to the State throughout the country To use at least 50% of Chinese integrated circuits on their servers. Cambricon Technologies is not an emerging company like the others China needs talent to compete with the US on equal terms and knows where you should look for it: in its population. In fact, the Administration has encouraged the implementation of elite educational centers that receive the best students in the country with open arms. The Chen brothers were two of them. Today are the founders and maximums responsible for Cambricon Technologies. The first, Chen Tianshi, exercises as president and general director of this company specialized in chip design for AI applications. And the second, Chen Yunji, is an expert in the development of processors for neural networks that, as far as we know, exercises as an advisor and responsible for technology in Cambricon. Both formed in An elite program for young talents In the Chinese Academy of Sciences, and currently the two are researchers and professors in this educational institution. Your best asset is its complementarity. Tianshi is an expert in chips design, and Yunji in AI. Chen Tianshi and Chen Yunji obtained their doctorates in computer science at age 24 Together they created a project at the Chinese Academy of Sciences that pursued a processor specialized in deep learning. Their plan went well and that chip allowed them to found their company. Their curriculum supports them, and there is no doubt that their effort has helped them reach the position in which they are. In fact, both obtained their doctorates in computer science at age 24. However, Cambricon is not a traditional emerging company. The growth of which we have spoken a few lines above and the expectations it has raised have been led by the support of the Chinese government, which sees in this company the opportunity to achieve the technological self -sufficiency it needs. During the last three years Huawei has established himself as one of the main Chinese GPU designers for AI, but Cambricon has something that this giant does not count at the moment: he combines a very ambitious hardware and A constant software platform improves. Huawei Ascend family chips are very competitive, and also has Cann (Compute Architecture for Neural Networks), what is Your alternative to Cudabut Cambricon is demonstrating that he has the ability to adapt its Neuware software very quickly to the needs of its customers. And in a market in which CUDA governs with iron fist It is a very important asset. Currently the flagship products that have changed to compete with Nvidia and Huawei in the Chinese market are the MLU series (Machine Learning Unit) and yes. In fact, the expectations of the Chinese semiconductor industry defend that the GPU Siyuan 690 will have comparable performance to the chip NVIDIA H100. In addition, Cambricon guarantees that their products are compatible with the models of the leaders in China, such as Deepseek, Qwen de Alibaba or Hunyuan de Tencent, among others, which has allowed it Gain the confidence of the Chinese industry. If we add that, According to Financial Timesfor developers it is easier to use neuware that Cann is reasonable to anticipate that during the next months Cambricon will monopolize the attention of the technology industry. Image | Cambricon Technologies 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

Nvidia has become the most important company in the world. His problem is that he has all the eggs in the same basket

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In Nvidia everything goes on wheels, but Not even enough for Wall Street. The latest quarterly results report has once again demonstrated Eun Eun Exceptional Power, but be careful. The most important company in the world –by stock marketat least – has an Achilles heel. A dangerous concentration of customers. He Official document With the financial results, it refers to a “risk of concentration” of the great clients of Nvidia. The situation is really worrying, because Six customers They accumulate 85% of all income from the company: 10,750 million dollars – Customer A (23% of total ingreoss) 7,480 million dollars – Customer B (16%) 6,540 million dollars – Customer C (14%) 5,140 million dollars – Customer D (11%) 5,140 million dollars – Customer E (11%) 4,670 million dollars – Customer F (10%) The problem goes more, no less. If we only look at the two most important customers, A is responsible for 23% of Nvidia and B revenues of 16%: 39% of income therefore come from only two clients. A year ago the two largest Nvidia clients were responsible for 14% and 11% of income, 25% in total. These data raise an inevitable question: who is who in that client cast. And the answer is not simple. Direct customers … Nvidia makes a distinction between those clients to whom he refers to the document, and that are divided into two large groups, the first is that of direct customers, which are not end users of their chips, but companies that buy the chips and that mounted them in complete systems or on plates that then sell to data centers, infrastructure suppliers in the cloud or final cloud. Among the examples, they indicate In CNBCwould be Foxconn, Quanta or Dell. … and indirect customers. This is where those companies would enter that we are all thinking and use these chips – which they buy from direct customers – in Your gigantic data centers. Microsoft, Openai, Meta, Google, Tesla/Xai and Meta – and even Oracle – are clear candidates, but again, it is impossible to know for sure who is on that list of great buyers. But the two most important are direct. What they do indicate in Nvidia is that customer A and B are direct customers, so they are not theoretically none of those great technological ones. But those definitions of Nvidia are somewhat diffuse, and the company states that some direct customers buy chips to create systems for their own use, so Any of the Big Tech I could enter that definition. To curl the curl, Nvidia said that two of its indirect clients each of them were responsible for 10% of their total income, but above all through the purchase of systems from customers A and B. OpenAI in the pools. In Nvidia they talked about “an AI research and development company” contributed with a “significant” amount of income both through direct and indirect customers. Here are more candidates, but one of the strongest would be Openai, especially now that he is working In the Stargate project. But the situation is dangerous. Be as it may, depending on both so few clients is delicate and creates a dangerous dependency chain. Thus, Nvidia depends on intermediaries that in turn They depend on a handful of technological giants. The company’s destination is in the hands of two buyers who represent almost 40% of their business, but the risk is not only for Nvidia, but for the entire technological ecosystem that depends on their chips. There are not only companies, there are countries buying gpus. Another of the curious data of this report is the one that tells us about how Some foreign governments They are also buying chips massively. In fact, the company expects to enter 20,000 million dollars in these “Sovereign” projects with countries that try to create their own models and artificial intelligence infrastructure. Image | Sharon Waldron edited with Google Gemini In Xataka | Microsoft had a saved secret. His new AI model for Copilot is the clearest statement against Openai’s domain

Nvidia is ready for the chip for the need to survive in China. Who is not ready to let him sell is the US government

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The journey in China of the Nvidia GPU for artificial intelligence (AI) H20 He has been full of ups and downs. Since this chip reached the Chinese market in mid -2024 its sales 50% quarter to quarter grewwhich positioned it as The most successful Nvidia product of recent years. However, this era of bonanza lasted little. And it is that in the middle of last April the US Department of Commerce decided impose export restrictions To China of the H20 GPU. After several weeks of negotiations with the US government Nvidia got the export license that he needed to sell his GPU for the H20 in China, but the joy lasted little. And it is that the Chinese government has vetoed this chip. And he has done so that the administration of the cyberspace of China, which is the main Internet regulatory body in this country, is thoroughly investigating this GPU because it suspects that it could incorporate a rear door of difficult location by Chinese experts. Nvidia engineers have been working on a new GPU for several months for expressly designed for the Chinese market. It will be called B30A And on his shoulders he will rest, neither more nor less, the future of the company led by Jensen Huang in China. This chip must necessarily meet two conditions. On the one hand it has to be more powerful than the GPU H20, and, in addition, it must satisfy the restrictions imposed by the US Department of Commerce. Otherwise Nvidia will not get the export license you need to be able to sell this chip in this Asian country. The future of the B30A GPU in China right now is uncertain Chinese companies that are dedicated to the development of large AI models are trapped. On the one hand they are being forced to deal with the export restrictions of the GPU imposed by the US government. And, in addition, they are subject to their own dependence on American technology. A priori the optimal solution for them would be to stop buying Nvidia and other US companies their chips for AI, and getting “comparable” GPUs proposed by Huawei, Change either Moore Threadsamong other Chinese companies. Jensen Huang has just recognized that his next GPU will take to arrive in the country led by Xi Jinping However, as explained in your article to Foreign Policy The American analyst Kyle Chan, the scenario they face is more complicated than it seems. And it is that abandoning Nvidia in practice is very difficult. According to ChanTencent, Bytedance, Alibaba and other Chinese companies They prefer GPUs for Nvidia Because its performance is greater, especially when facing the training processes of their AI models. However, they especially opt for the chips of this American company thanks to 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. In these circumstances, the B30A chip that is putting to point Nvidia has all the meaning of the world. Presumably It will be half powerful that the most advanced GPU this company currently has, The B300 chipbut, even so, it is reasonable to assume that will overcome performance of all the chips for the developed in China, especially when facing the training processes of the AI ​​models. This is the best asset that Nvidia has, but Jensen Huang has just recognized that its next GPU will take to arrive in the country led by Xi Jinping. And it will not be because it is not ready. It will be because the US Trade Department will take long to give it approval, if it finally gives it. What is happening to Nvidia in China is a full -fledged soap opera. Image | Nvidia More information | Reuters In Xataka | The US gives Huawei a great opportunity: to get its new chip for AI with the Nvidia market in China

He has not bought Nvidia or a single H20 GPU in the last quarter

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The future of Nvidia in China is every day that spends more gloomy. In early October 2024 Chinese administration arrived to the companies of artificial intelligence (AI) A recommendation in which I asked them to use chips produced in China as much as possible. Ten months later This recommendation has been transformed into a requirement. And is that the Chinese government is already forcing data centers that belong to the State throughout the country to use at least 50% of Chinese integrated circuits on their servers. On the other hand, Nvidia has achieved the export license you need to sell in China Your GPU for IA H20but the Chinese government has vetoed this chip. And he has done so that the administration of the cyberspace of China, which is the main Internet regulatory body in this country, This GPU is thoroughly investigating Because he suspects that he could incorporate a rear door of difficult location by Chinese experts. If so, the possibility of China to use this chip. The direct consequence of this unfavorable scenario for Nvidia is that during the last quarter it has not sold a single H20 GPU in China, As Shaun Rein holdsan expert in the Chinese economy and founder of the consultant The China Market Research Group (CMR), which is housed in Shanghai. This statement is true, but it has a small trick. For a good part of the last quarter Nvidia did not have the export license that he needed to deliver this chip to his Chinese clients, but he already has it. And it could have sold thousands of these GPUs during the last weeks. China has alternatives designed to compete with Nvidia chips Despite the efforts of the US government to avoid it, the avant -garde chips for ia They have continued arriving in China. And they have done it mainly through secondary markets and parallel import roads that run in India, Malaysia or Singapore, in which The US action It is very limited. In addition, the developers of great AI models that have projects with projects with CUDA They have found the appropriate place to get these GPU: The international second -hand market. Cambricon Technologies is one of the companies specialized in the design of GPU for AI with greater growth potential Anyway China already has three alternatives Very clear to Nvidia. Although it is not as well known as Huawei or Moore Threads, Cambricon Technologies is one of the companies specialized in the design of GPU for AI with greater growth potential. In fact, he has received the approval of the Shanghai bag (China) to raise 560 million dollars. It will allocate them to the design of four chips for training and inference of AI models, and also to the development of an alternative to CUDA. On the other hand, Moore Threads He has developed several GPU for AI applications that, on paper, rivaize some of the advanced solutions that have placed in the Nvidia, AMD or Huawei market. The MTT S4000 and MTT S3000 cards are its most interesting proposals right now, although, curiously, in its porpholio the MTT S80 card, a proposal for games and content creation that, according to Moore Threads itself, has a 14.4 TFLOPS calculation capacity also appears in Floating Coma operations of simple precision. The other indispensable actor in the Chinese chips industry for IA is Huawei. His most ambitious proposal right now is the chip Ascend 910dwho seeks to overcome the performance of the GPU NVIDIA H100. However, this Chinese company has also recently presented its chip Ascend 920a solution that is clearly destined to occupy in the Chinese market The gaps that the NVIDIA H20 GPU is going to leave. This proposal will enter large -scale production during the second half of 2025 using 6 NM integration technology that have presumably developed elbow with Huawei elbow and SMIC (Semiconductor manufacturing international corp). Image | Nvidia | Zhang Kaiyv More information | Shaun Rein In Xataka | The US gives Huawei a great opportunity: to get its new chip for AI with the Nvidia market in China

Nvidia has become hostage of her own success. His record numbers know little when the world expects miracles

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Nvidia has presented her Results of the second fiscal quarter. Technically beat all forecasts: Adjusted benefits of $ 1.05 per share compared to the 1.01 expected. Revenues of 46,740 million dollars against the projected 46,230 million. The company has also projected income of 54,000 million for the current quarter, slightly above the consensus of 53.4 billion. Why is it important. These seemingly solid numbers have not been enough for a market that has turned Nvidia into the fire test definitive of boom of the AI. The action has fallen 3% in the operations after closing, a reaction that reveals to what extent the expectations about the most valuable company in the world – with 4.4 billion capitalization – have reached almost impossible levels of satisfying. China’s problem. The great shadow on the results has been the total absence of sales of the H20 chip To China during the quarter. Nvidia has not included any sales forecast to China in its guide for the third quarter, despite the fact that the financial director, Colette Kress, has mentioned that they have between 2,000 and 5,000 million dollars in ready -to -send orders to send if geopolitical issues are resolved. The company is waiting for the Trump administration to clarify the regulations on the 15% cut they want to impose to Chips sales to China. Jensen Huang has been unusually direct during the Call with analysts: “The Chinese market estimates that represents about 50,000 million dollars of opportunity for us this year.” He added that half of the world’s researchers are in China … And that it is “quite important” that American technology companies can access that market. Between the lines. Huang’s frustration with the geopolitical situation is palpable. His comment that “we just have to continue advocating” before the Trump administration makes us glimpse a more tense negotiation than the official statements say. The CEO has suggested that they are working in a modified version of their Blackwell chips for China, with reduced performance, indicating that Nvidia is willing to make weight concessions so as not to lose that market. Striking in a company Today as powerful as Nvidia. Data centers disappoint. The data centers segment, which represents 88% of total income, has generated 41,1 billion dollars, slightly below the expected 41,290 million. It is the second consecutive trimester that this important segment does not reach expectations, a worrying signal when large technological ones such as goal, Google and Microsoft are investing tens of billions each quarter in AI infrastructure. “Everything is sold”. Huang has said during the call that “everything is sold”, referring so much to the Hopper chips current as the new Blackwell. Has added that the production of Blackwell Ultra It is “progressing at full speed” and that demand is “extraordinary.” However, these statements contrast with the fact that the income growth of 56% year -on -year is the slowest in nine consecutive quarters of growth greater than 50%. Growing pressure. The market reaction tells an uncomfortable truth: Nvidia has become hostage of its own success. With a weight of 7.5% in the S&P 500 – 3% in December -, Any stumbling block has the potential to drag the entire market. An important Nvidia failure would be a detonation for half -world bags. The contrast. Huang has promised that AI infrastructure spending will reach between 3 and 4 billion dollars for the end of the decade, but the immediate reality is that NVIDIA cannot freely access the second largest computer market in the world. The repurchase of 60,000 million dollars in shares approved by the Council – one of the largest in American business history – seems more an attempt to sustain the price of the action than a real confidence signal in the future without regulatory mosquadillas. In Xataka | Deepseek has suggested that Nvidia chips no longer needs. We believe to know who is buying them Outstanding image | Nvidia

Deepseek has suggested that Nvidia chips no longer needs. We believe to know who is buying them

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Deepseek shook at the beginning of 2025 the foundations of the industry of the artificial intelligence (AI). This Chinese model developed by the specialized quantitative coverage fund trading High-Flyer algorithmic monopolized all the attention because He gave us free of charge an AI with a quality similar to the comparable solutions of Openai or Google. However, this was not all. And it is that for three weeks the debate about the hardware used by this company to train its model. High-Flyer, who specializes in addressing investment decisions using advanced mathematical models and computational algorithms, says he trained Deepseek R1 using 2,048 chips H800 of Nvidia. Several analysts They soon react ensuring that he had actually used 50,000 GPU H100which are more powerful, bought through intermediaries. The sanctions of the US government prevent Nvidia According to SCMPDeepseek’s next iteration will dispense with the GPUs of this American company. High-Flyer has suggested that everything you need already finds it in China Last week those responsible for the Deepseek development published on the Wechat platform an entry in which they hinted that next generation GPUs for China They will launch soon. This comment has unleashed endless speculation about the name of the Chinese company that is going to make this announcement, but, above all, it has put on the table the possibility that High-Flyer is preparing the following Deepseek iteration using these chips. A priori does not seem at all crazy. According to SCMP The five GPU designers for the Chinese who have the ability to deliver to High-Flyer the hardware they need are Huawei Technologies, Cambricon Technologies, Moore Threads, Hygon Information Technology and Metax Integrated Circi. Any of them could be responsible for the announcement anticipated by Deepseek developers in Wechat, but we We bet on the first three Because, in our opinion, they are Those who are “in a better way”. Cambricon Technologies is one of the companies specialized in the design of GPU for AI with greater growth potential Although it is not as well known as Huawei or Moore Threads, Cambricon Technologies is one of the companies specialized in the design of GPU for AI with greater growth potential. In fact, he has received the approval of the Shanghai bag (China) to raise 560 million dollars. Will allocate them to the design of four chips for training and inference of AI models, and also to the development of an alternative to CUDAfrom Nvidia. On the other hand, Moore Threads He has developed several GPU for AI applications that, on paper, rivaize some of the advanced solutions that have placed in the Nvidia, AMD or Huawei market. MTT S4000 and MTT S3000 cards They are its most interesting proposals right now, although, curiously, in its porpholio the MTT S80 card also appears, a proposal for games and content creation that, according to Moore Threads itself, has a calculation capacity of 14.4 Tflops in single -precision floating coma operations. The other indispensable actor in the Chinese chips industry for IA is Huawei. His most ambitious proposal right now is the chip Ascend 910dwho seeks to overcome the performance of the GPU NVIDIA H100. However, this Chinese company has also recently presented its chip Ascend 920a solution that is clearly destined to occupy in the Chinese market the gaps that the NVIDIA H20 GPU is going to leave. This proposal will enter large -scale production during the second half of 2025 using 6 NM integration technology that have presumably developed elbow with Huawei elbow and SMIC (Semiconductor manufacturing international corp). 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

Nvidia is the Canary in the mine for the world economy. It depends on whether a recession arrives or not

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Nvidia will present its results from the second fiscal quarter on Wednesday. The market Wait for income of 46,000 million dollars54% more than a year ago, with benefits per share of $ 1.01, 48% higher. Why is it important. Nvidia is no longer just one more technological company. With almost 8% of the weight of the American index S&P 500 and a market value of 4.3 billion dollars, its results move world bags. Investors hope that Wall Street ranges 0.9% after knowing the figures, more even after types of types of interest of the Federal Reserve. The context. Large technology still invests fortunes in artificial intelligence. Amazon, Microsoft, Meta and Google represent 40% of Nvidia’s income. Their investment plans in data centers and graphic processors do not show brake signals. Goal has just launched Your Superintelligence Laboratory. Tesla bets on autonomous cars and humanoid robots. The problem is that the market already discounts perfection. The action quotes in its historical maximums and any disappointment, however small, could trigger a brutal correction. Yes, but. China is still the great unknown. The Chinese government has just recommended to local businesses that Avoid NVIDIA H20 chipspecifically designed for that market. The United States had authorized sales in exchange for keeping 15% of incomebut the commercial war threatens a market valued at 50,000 million dollars. Between the lines. Analysts are still extremely optimistic. Nine investment firms have uploaded their target prices in the last week to an average of $ 194, 9% above Friday’s closure. But the option of options Sample nervousness: investors expect a 6% movement in any direction. Sectorial rotation has already begun. Technology has been the worst stock market sector in August and interest -ranking values ​​have taken off. Small companies rise 5% in the last month. The construction companies, 10%. At stake. If Nvidia disappoints, even if it is minimally, it could trigger a massive sale in technology and confirm bubble fears in artificial intelligence. If you exceed expectations, it will revive the technological increases and remove the ghosts of the recession. As says The strategist Art Hogan: “Nvidia has the potential to be the positive catalyst.” Or, we would add to sink everything. In Xataka | The countdown begins: Nvidia is going to give your chips to the push you need to maintain their domain Outstanding image | Nvidia

Nvidia is going to give your chips to the push you need to maintain their domain

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Nvidia is preparing to open the door to the door to The photonic silicon. Just a few hours ago it has started in Palo Alto, California (USA), the Specialized Conference in Semiconductor Engineering and High Performance Computing ‘Hot Chips’. And the company led by Jensen Huang has not let out the opportunity to announce that in 2026 its platforms of artificial intelligence (AI) latest generation They will use photonic interconnections to reach higher transfer speeds between GPU clusters. Most of the designers and manufacturers of integrated circuits are working on the development of silicon’s photonic. Douglas Yu, a TSMC executive with responsibility in the field of systems integration, explained In September 2023, what disruptive capacity has this technology: “If we manage to implement a good system of integration of silicon photonics we will trigger a new paradigm. We will probably be placed at the beginning of a new era.” Nvidia has just taught her letters Before moving forward we are interested in intuiting with some precision what we are talking about. The photonic silicon is a discipline that in the field that concerns us seeks to develop the technology of this chemical element to optimize the transformation of electrical signals into light pulses. The most obvious field of application of this innovation is the implementation of high performance links that, on paper, can be used both to solve communications between several chips and to optimize the transfer of information between several machines. Advanced packaging technologies with which the main semiconductor manufacturers work, such as TSMC, Intel or Samsung, can benefit a lot from a communication mechanism between very high performance chips. And the big data centers in which it is necessary connect a large number of machinesalso. However, there is a particular discipline that has a projection of the future overwhelming and the one that would be wonderful about the advantages proposed by the photonic silicon: AI. CPO technology reduces energy consumption to just 9 watts per port This is precisely Nvidia’s commitment. In the clusters of the thousands of GPU they must work in unison, so it is essential to connect them using high performance links. It is possible to solve this challenge using traditional copper cables or optical modules, but these two solutions introduce very important inefficiencies in the infrastructure. The most problematic are the loss of energy and bottlenecks. Data transfer can consume up to 30 watts per port, which increases the dissipation of energy in the form of heat and increases the probability of a failure. In addition, latency limits the scalability of clusters as the GPU number of data centers increases. To solve these inefficiencies NVIDIA will integrate the optical components that require photonic interconnections In the same encapsulated switching chip. This technology is known as CPO (Co-Packaged Optics) and reduce energy consumption to only 9 watts per port. In addition, it minimizes signal loss and improves data integrity. It looks really good. NVIDIA has confirmed that it will integrate CPO technology into its Quantum-X infiniband and Spectrum-X Ethernet interconnection platforms during 2026. However, there is something important that is worth not overlooking: CPO will not be an extra. When it arrives, it will be strengthened as a structural requirement of the next generation of data centers for AI in a clear attempt to increase the competitiveness of hardware platforms for NVIDIA. Image | Nvidia More information | Tom’s hardware In Xataka | Intel and TSMC lead the revolution of photonic chips. His problem is that China has just done fully in this war

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