NVIDIA

Nvidia is the first company to reach 4 billion dollars of capitalization

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Nvidia has achieved something historical: becoming the first company quoted to reach 4 billion dollars of stock market. During Wednesday’s session, the company’s shares They reached this symbolic milestonesurpassing both Apple and Microsoft. An ephemeral but significant achievement. Although Nvidia’s actions closed the day with A 1.8% riseplacing its valuation slightly below the 4 billion, the fact of having touched this figure during the session marks a historical moment in the markets. The company has managed to overcome giants like Apple, which began the year as The most valuable company in the world With 3.9 billion dollars, and Microsoft, which for months has exchanged positions with Nvidia as the ranking leader. The AI ​​revolution drives Nvidia. The meteoric rise of Nvidia It is explained by its central role in the boom of artificial intelligence. Their specialized chips feed on data centers that companies such as Microsoft, Amazon and Google need for their AI models and cloud services. This strategic positioning has catapulted its actions 22% so far this year, despite geopolitical turbulence and commercial restrictions with China. The numbers speak for themselves. In its last fiscal quarter, Nvidia generated $ 44,100 million in revenue, an increase of 69% compared to the same period of the previous year. The forecasts of the sector are even more optimistic: the global expenditure on the infrastructure of the 200,000 million dollars in 2028 is expected to exceed 2028, according to The International Data Corporation research firm. Obstacles on the road. Not everything has been a rose path for the company. Export restrictions of Your H20 chips China has cost about 8,000 million dollars in lost sales. In addition, the irruption of Deepseekthe Chinese startup that was planted out of nowhere with it developed from a powerful model and promising to have reached its milestone With ridiculous costs compared, caused doubts On whether the expensive Nvidia chips were really essential for the advance of AI, temporarily sinking your actions in January. Overflowing expectations. Despite these setbacks, Wall Street analysts maintain overflowing optimism. The Loop Capital firm esteem That Nvidia could reach a capitalization of 6 billion dollars in 2028, arguing that the company essentially maintains a monopoly in critical technology for the AI ​​sector. For its part, CEO Jensen Huang, who has become The tenth richest person in the worldaccording to the Bloomberg index, with a equity of 140,000 million dollars, See a promising future Ahead: “Of course, we know that AI is this incredible technology that will transform all industries, from the way we do the software to medical care and financial services to retail trade until, I suppose, all industries, transport, manufacturing … and we are at the beginning of that.” Cover image | Nvidia In Xataka | Depseek marked a turning point in OpenAi: now reinforces its safety while GPT -5 appears on the horizon, according to FT

The AI ​​has no future without nuclear energy when even Nvidia has begun to pray to Bill Gates reactors

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Data centers will be responsible for 10% of the increase in energy demand until 2030, according to the International Energy Agency (IE). The rise of artificial intelligence (AI) What we are living has triggered the proliferation of these facilities In the US, China, Japan, Singapore, India, Germany, Netherlands or Ireland, among other nations. And for the moment there is no indication that invites us to anticipate that this trend will be exhausted in the medium term. A data center dedicated to large AI can exceed 150 MWand, precisely, these are the facilities that are proliferating the most. In fact, in 2024 its global consumption amounted to about 415 TWH, a figure that represents around the 1.5% of global electricity consumption. To solve this challenge and guarantee to data centers the delivery of energy that more and more companies need nuclear. The last one who has done is Nvidia. And is that the company led by Jensen Huang has participated in a financing round Of 650 million dollars to support Terrapower projects, the nuclear energy company founded by Bill Gates in 2006. With this decision NVIDIA adds to the strategy that defends the use of Compact modular reactors (known as SMR for its denomination in English) with the purpose of delivering to the data centers the electricity they need. And, incidentally, put one more leg in a sector with an indisputable growth potential. Terrapower is already building the first Natrium nuclear reactor The nuclear fission reactor that this company has designed is a modular and compact design refrigerated by sodium that uses a molten salts storage system. Because of its characteristics, it is about A fourth generation machine That, according to those responsible, it will be able to generate electricity in half of the cost that a conventional nuclear fission reactor. Whatever the interesting thing is that the first Natrium nuclear reactor in Terrapower is being built in a Wyoming Mining town (USA), and, according to Bill Gates, will be completed in 2030. Nvidia has participated in a financing round of 650 million dollars to support Terrapower projects It sounds good, but we must not overlook that it is a new generation design, so a priori the five years that Terrapower manages seem too optimistic. However, this reactor has an important asset in your favor: on paper Its tuning should be faster and cheaper than that of conventional reactors. In addition, a Spanish public company is participating in the construction of this machine. It is called Ensa (Nuclear Teams, SA), is Cantabrian and has more than five decades of experience in the field of design and manufacturing large components for the nuclear industry. There is no doubt that the fact that Terrapower has decided to ally with it is a boost that will surely reinforce its international image. And, perhaps, he opens the door of other latest generation nuclear energy projects. “This is the first reactor of these characteristics that is manufactured following the highest standards of safety and quality in accordance with the most demanding nuclear regulations,” has declared A Enso spokesman. Interestingly, this Spanish company will participate in The manufacture of the Natrium reactor lid. A last interesting note: currently also intervenes in the construction of ITER (International Thermonuclear Experctor reactor), The experimental reactor of nuclear fusion that an international consortium led by Europe is pointing in the French town of Cadarache. Image | Terrapower More information | The Register In Xataka | “We are already on the last step”: how Spain has done with the key to realize nuclear fusion

We knew that humanoid robots would reach factories. Nvidia has already chosen where and when to start, according to Reuters

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When did humanoid robots stop being a spectacle to become a tool? Maybe that’s right there. Sources consulted by Reuters They assure that Nvidia and Foxconn are in conversations to display them in a server manufacturing plant of artificial intelligence in Houston. Nvidia has trusted the Taiwanese giant to lift a new server manufacturing plant in Houston, Texas. The objective: produce the GB300its new AI servers based on architecture Blackwellwithin the ambitious plan for relocate part of its production in US territory. As Reuters has advanced, both companies are in conversations to display humanoid robots in this factory. The intention would be that they begin to operate in the First quarter of 2026. If concrete, it will mark a double milestone: it would be the first time that a NVIDIA product is manufactured with the help of these tools, and also the first use of this technology by Foxconn in a production line of AI servers. Houston is not any factory: something new is prepared here For now, the details are scarce. It is not known how many robots will be used, how will they look or what exact functions they will perform. But there are indications. In an internal presentation of May, Foxconn showed how he was training humanoid robots for tasks such as manipulating objects, inserting cables or making basic assemblies, usual activities in the manufacture of servers. Houston’s choice is not accidental. Being a new plant, spaces are being designed with margin to integrate these technologies From the beginningsomething much more complex to achieve in already operational facilities. According to one of the sources consulted, that design would facilitate the incorporation of humanoid robots in the line. NVIDIA GB300 has a rack scale design That Nvidia bet on humanoid robots in its production chain is not just a logistics movement. It is also a declaration of intentions. Until now, no company product had been manufactured with the help of this type of robots. And Foxconn, the largest manufacturer on the commission of the world, had not used them in a production line dedicated to AI servers. The decision, according to what the sources have told Reuters, would mark the beginning of a new stage for both companies. In the case of Foxconn, it would also serve to show the world the advances in robotics who has been developing with Nvidia, although third -party models such as those of China Ubtech have also been tested. For Nvidia, the movement fits with its broader strategy. The company not only designs chips for AI models training: it also offers A development platform Specific for humanoid robots, with visual, motor and cognitive abilities based on their own architectures. In March, Jensen Huang himself He predicted that The generalized use of humanoid robots in industrial environments would come “in less than five years.” They are not alone: ​​Tesla, Mercedes, BMW, China The idea of ​​incorporating humanoid robots into the assembly lines is no longer a rarity. Although its deployment is still limited and experimental, several manufacturers have been testing this technology for some time in controlled environments or in very specific tasks. Among them BMW stands out, that has made trials in American plants. And it is known that Teslawhich has developed its own humanoid robot called OptimusHe has put at least two units to work in a production line. But interest is not limited to the great western brands. China has converted humanoid robotics into a national strategic priority Within its Made in China 2025 plan. Companies like Ubtech – whose model has also been evaluated by Foxconn – are being driven directly by the government with a view to transforming the country’s industrial fabric. Strategic alliances are part of this mission Like Huawei and Ubtech Specified this year. This possible deployment of humanoid robots in Houston does not occur in a vacuum. Is part of a broader movement, driven by political pressure and the strategic need of Relocate production Technological on American soil. In April, Nvidia announced its intention To manufacture AI infrastructure of up to 500,000 million dollars in the US in the next four years, with partners such as TSMC, Wistron and Foxconn itself. For many companies, automating is a matter of survival. The Houston factory, still under construction, is part of that strategy. But producing locally implies facing at least one new problem: the shortage of labor. And that is where automation would come into play. Perhaps not essentially for these factories, but as a test field for possible future expansions. For many companies, automating is no longer a matter of improvement. It is a matter of survival. Thus, more and more local actors are developing humanoid robots designed specifically for the industry. Tesla, Figure, Apptronik or Agility Robotics They are among the companies that have opted for this new generation of machines. Jeff Burnstein, president of the Association for Advancing Automation, summed up axios The new industrial reality: “This is how it competes today”, so “you have to take advantage of the best available tools.” Humanoid robots lived for years with skepticism: beautiful exhibitions, Little useful in practice. Now, that perception is turning. We are faced with a change that aims to be important, but whose real range we will know only over time. Images | Nvidia | Boliviainteligent In Xataka | The US is willing to do anything for advanced chips not to reach China. And Malaysia is an obstacle

AMD’s problem is not that it does not make good gpus for ia. Is that it is not even close to Nvidia

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AMD is doing things well, but even doing them still unable to compete with Nvidia. The company has just raised its renewed road map with promising models, but that is not a guarantee of anything to a NVIDIA that will not let its absolute leadership position escape. The problem for AMD is not to be, but get others to take note. IDC consultancy data indicate that Nvidia dominates the AI ​​chips market with 85.2% market dick, for 14.3% AMD. Other analysts like Jon Pedie Research go beyond and According to your data The NVIDIA quota in this segment is 92%. AMD instinct mi350 are just the beginning. The GPUS for IA, which AMD calls “accelerators”, follow its evolution. During the event they presented their family or Instinct Mi350 series with two variants, MI350X and MI355X. According to the manufacturer, these chips are four times higher in general performance with respect to the previous generation, but are up to 35 times more powerful in the field of inference AI (that is, in the practical use of models such as Chatgpt, which “infers” “their responses from our prompts). They have 288 GB of HBM3E memory and a memory bandwidth of 8 TB/s. Its yield is 18.45 pflops in FP4 precision and 9.2 pflops in precision FP8. Instinct Mi400 in 2026. Next year the new family of AMD’s accelerators will arrive. It’s about future MI400 instinctwhich will arrive with up to 432 GB of HBM4 memory, 19.6 TB/s of bandwidth of that memory, and a performance of 40 pflops in precision FP4 and 20 Pflops in precision FP8. These monsters will be sold in future racks with infrastructure “Helios“, that You can house Up to 72 Mi400 with up to 260 TB/s total bandwidth thanks to its interconnection technology, Ultra Accelerator Link. EPYC VENICE. AMD not only talked about GPUS: it also has its future processors for servers in data centers in full development. The Epyc Venice will arrive in 2026 and will be based on Zen 6 architecture. Among the variants, an especially spectacular with 256 cores that will offer up to 70% more performance compared to the previous generation. These processors will be built with future MI400 instinct. They are expected to be manufactured with the N2P (2 Nm) node of TSMC. Helios against Oberon. The aforementioned Rack Helios will compete with not already with the current Nvidia AI server, the GB200 NVL72 which connects 36 CPUS Grace and 72 Gpus Blackwell. He is destined to compete with his successor, which has Oberon’s code name and will use IA B300 GPUS with Vera Rubin architecture. The yields and benefits of these future racks are absolutely dizzy, and for example their Precision Power FP8 is 1.4 Exaflops. The same in some things, better in others. AMD promises to match NVIDIA in several sections, but also ensures that it will exceed it remarkably (50% more) in memory quantity and width, something crucial for training and inference AI. Be careful, because at the end of 2027 NVIDIA prepares the Rubin Ultra architecture, which promises racks with up to 5 Exaflops in FP8 precision, three times more than Helios or Oberon. In 2027 we will have another “summer”. The AMD roadmap goes further, and they have already prepared the development of their new generation of chips for summer Epyc servers, which will replace the Epyc Venice. These CPUS will be paired with the future MI500X instinct, and it is expected – although it is not safe – that both types of chip take advantage of the one already announced TSMC A16 node (1.6 Nm), which will begin to be used at the end of 2026. There are no specifications for these developments, surely because they will depend on the manufacturing node that AMD ends up using to produce them. Frantic race. All these ads show that AMD does not want to be left behind in that race to place their solutions in data centers worldwide. The Crusoe company, which is dedicated to the construction of large AI data centers, advertisement A few days ago I would spend 400 million dollars in AMD’s chips, and even Sam Altman, CEO of OpenAi, made a surprise appearance During the inaugural talk of the Lisa Su, CEO of AMD event. Altman said they will also use AMD chips in the data centers they use, and highlighted that the new AMD ia gpus “will be somewhat amazing.” AMD presumes to be more efficient (and cheap). AMD’s message was clear during the event: its MI355 offer much more efficiency and are cheaper than NVIDIA B200 and GB200 with comparable yields. The sales prices of those GPUS are not known, but we do know that at the beginning of 2024 the MI300x of AMD They cost a maximum of $ 15,000 for the more than $ 40,000 that cost The NVIDIA H100. The biggest challenge is still CUDA. The benefits of AMD AI chips are not in fact the problem of this company. Detailed studies revealed months ago that MI300X are clearly higher than NVIDIA H100 and H200 on performance and power. However, Nvidia has a Cudathe de facto standard in the industry for services of services and applications of AI. Using AMD native software is feasible, yes, but software experience, They assured in SEMIANALYSIS“Software is full of errors that make training (AI models) with AMD it is impossible.” AMD’s hope is Rocm. In that AMD event also presented Rocm 7, the latest version from your own Open Source programming platform for your GPUS. In AMD they indicated that this version is 3.5 times more powerful than Rocm 6, and even claim that it is 30% more powerful than CUDA in the B200 when serving the model Deepseek R1. Even so, they indicate In another report of semi -health, it is still lower in some sections. Getting that component allows developers to take advantage of all the potential of AMD’s chips is precisely key to the future of those efforts. Even … Read more

The Nvidia IA supercomputer costs three million dollars. And to function wears a switch with three km cable

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When Nvidia presented her new AI chips, The B200 with Blackwell architecturetook the opportunity to present an AI accelerator called GB200. And by joining 36 of those accelerators created its AI server, the monstrous DGX GB200 NVL72, which also keeps some spectacular surprises. Each node is bestial. Each of those GB200 accelerators has a CPU Nvidia Grace with 72 ARM Neaven V2 nuclei and two B200 GPUS. By combining its power we end up having a kind of bestial GPU combined with a power of 1.44 Exaflops in precision FP4. A closet that weighs a quintal. The appearance of the GB200 NVL72 DGX is that of a small and narrow closet that is above all very dense: this rack weighs 1.36 tons. Inside there are 18 Bianca computing nodes in 1u format, and each of them has two GB200, or what is the same, with four B200 GPUS (hence 18 x 4 = 72). He estimated cost of this AI server is about three million. Liquid cooling is key. The heat dissipated by these components is remarkable, which makes in this case the best option to cool those elements is the liquid cooling. This system not only applies to the CPU Grace or in the B200 GPUS, but in the NVLink chips of the switches, which can also be heated a lot due to the massive transfer of data between the accelerators. Interconnections everywhere. For all these GPUS to work together, each of the 36 GB200 has specialized network cards with NVLINK support of fifth generation that allow each of the computer nodes to be connected to others. For this there are nine switches that provide that huge amount of interconnections. 3 km cable. The system allows you to enjoy a bidirectional bandwidth of 1.8 TB/s between the 72 server GPUS. But as they point out In The Registerthe really surprising thing is that in total inside that “closet” there are 3.2 kilometers of copper cable. Only the module with the switches weighs more than 30 kilograms due to both these components and the more than 5,000 cables that are used so that all Nvidia GPUS work together and in perfect synchrony. Why copper? It may be able to opt for copper cable seems strange, especially taking into account the needs in terms of bandwidth imposed by this machine. However, the solution with fiber optic cables imposed clear problems: we would have to use electronic components necessary to stabilize and convert optical signals. That would have increased not only the cost, but the consumption of the final system. Can Crysis run? The performance of each B200 chip It is already brutal on its own: Its power is the triple than that of the GeForce RTX 5090, and the entire server includes 72 of these specialized GPUSs for AI, which demonstrates the computing capacity that said machine possesses. It also has RT (Ray-Training) nuclei of the fourth generation, which would theoretically allow you to use these AI chips to play video games, although of course that is not even its purpose. In fact your performance in this area will probably be almost as poor as the Nvidia H100. Cloud consumption. Although new chips are much more efficient than H100 –25 times less, says Nvidia – this AI server has an estimated TDP of 140 kW. Since the average consumption of an average home in Spain round The 3,000 kWh per year, in an hour of use of the Nvidia server we consume the same as an average Spanish home in 17 days. Have it on and running all year raises a consumption similar to 415 middle homes throughout the year in Spain. In Xataka | AMD has a splendid roadmap for its AI chips. The problem is still in your software

break the brutal leadership of Nvidia and TSMC

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TSMC, The largest semiconductor manufacturer on the planetproduces the GPUs for artificial intelligence (AI) that are placing in the Nvidia, AMD market and many other manufacturers of this type of chips. In fact, 90% of integrated circuits for AI available in the world market TSMC has manufactured them. In addition, in its client portfolio Apple, Nvidia, AMD, Qualcomm, MediaTak, and even Intel, among many other companies that are dedicated to the design of integrated circuits. We are now with Nvidia. The company led by Jensen Huang currently monopolizes about 90% of the market of the GPUs for Ia. It is likely that in the medium term its quota will be reduced against the presumable growth of competitors such as Huawei or AMD, but right now Nvidia has no reason to worry. And it does not have them because the semiconductor market to grow a lot over the next few years. According to the AMR consultant (Allied Market Research) In 2031 it will have a billing volume of more than More than 263,000 million dollars. SMIC and HUAWEI are China’s spearhead in the chips and AI industries Jensen Huang, the general director of Nvidia, has declared A few days ago, China is not behind in front of the US in AI. And the solvency of Deepseek, Ernie, Qwen, Pangu, Hunyuan or Sensenova endorses its analysis. Right now it is very difficult to determine in an objective way which country leads in AI. It is reasonable to conclude that the US is ahead of China if we stick to the joint capacity and performance of its AI models, but the really relevant thing is to determine if that capacity entails a real value. This is The line of thought that defends experts As Arthur Lai, Chief of Research for Asia of the Macquarie Financial conglomerate, or Jason Corso, professor of AI at the University of Michigan (USA). In addition, it is important that we do not overlook that the metrics that are currently used to evaluate the abilities and performance of the most advanced AI models They are less and less clarifying. And as the models improve and develop their global competitiveness, it matches. Nvidia continues to dominate the Chinese hardware market for IA despite the sanctions of the US government In any case, as we are seeing, it is evident that China is competing from you to you in the development of large language models for the US. The greatest challenges facing this Asian country do not reside in this field; They last in the field of hardware. Nvidia continues to dominate the Chinese market of the hardware for the The sanctions of the US government that prevent you from selling your best GPU for your Chinese clients. And TSMC manufactures 90% of semiconductors for this scenario of use because it has in production some of the most advanced integration technologies that exist, and, what is also crucial, the performance per candy of its avant -garde nodes is very competitive. China needs to have companies capable of Compete from you with Nvidia and TSMCand their best candidates are currently SMIC (Semiconductor manufacturing international corp) and Huawei. SMIC is the largest Chinese manufacturer of semiconductors with a fee in the world market of about 5%and currently has the ability to manufacture integrated circuits of 6 and 7 nm. However, according to Dr. Kim, an expert in chips manufacturing who has worked in Samsung and currently investigating TSMC in the US, is about to start 5 Nm chip production and plan to start Its first 3 nod nodes equipped with gaa transistors (Gate-alall-around) in 2026. Huawei, meanwhile, is determined to absorb Little by little the market share that Nvidia maintains in China. Your most ambitious hardware is now the chip Ascend 910dthat pursues overcome 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 it will leave The H20 GPU of Nvidia. This proposal will enter large -scale production during the second half of 2025 using 6 Nm integration technology that have presumably developed side with Huawei and SMIC side. Image | Nvidia 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

Switch 2 is important for Nintendo, but also for a nvidia that does not want to lose ground against AMD

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Nintendo Switch 2 It’s here. When a new generation of consoles arrives, beyond New games and experiences that allows, there is a substantive issue that may not interest all users so much, but it is of vital importance for the technology industry: Who signs the processor. We don’t know Switch 2’s heart beyond what the tests of their first games suggest. AND, Although it is evident that it is powerfulwe will have to wait to see how developers thoroughly squeeze their chip designed by NVIDIA and manufactured by Samsung. It is evident that the console is important for a Nintendo who saw that switch sales began to waverbut just as important for that NVIDIA that signs a processing unit with which, now, it comes back to the battle horse in the hybrid console segment. Nvidia returns to load When a company leads, what you want is to have even more part of the cake. Nvidia dominates The world of PC video games With iron hand and, although AMD is doing things well with its latest generations, the singing voice continues to take the company led by Jensen Huang. That battle against AMD on the PC is very unequal, but In the field of consoles, history tells us something else. Both were linked decades ago to video games on platforms dedicated with ATI (before being part of AMD) designing the GPU of Game Cube, Wii and Xbox 360 and Nvidia taking care of the GPU of the Original Xbox and of PS3. With the jump to the next generation, Nvidia got out of the equation and left the free ground for an AMD that did not succeed with her GPU, either with her CPU, but with her APU. It was his technology that convinced Sony and Microsoft for all their consoles from Xbox One and PS4 From now on. Nvidia, however, returned in 2017 with His tegra chip and a new alliance with Nintendo for Switch launch. It was not the most advanced at the time, that Tegra showed that the technology was ready To be able to create platforms that offered such experience with desktop power, but in portable format. And they have not gone wrong or Nintendo … neither Nvidia by extension. 152 million units and up. However, things have changed because Nvidia is no longer alone in this and AMD, along with Valve with Steam Deckshowed that its image reconstruction technology, Photograms generation and its power/consumption relationship could overcome what Nvidia offered with switch. Thus, we have seen AMD heart on PC consolidated as impressive as the Lenovo Legion Go or the Asus Rog Allyand it is a segment in which Intel, with a first failed proposal with the MSI Claw and a much more solid second with MSI Claw 8 AI+shows that you also have something to say. Nvidia has remained away from those PC consolidated for a reason: They didn’t have a CPU. Now, earlier this year, and after months of rumors, Nvidia presented Project Digits. It is a desktop computer for AI whose CPU is designed by NVIDIA: Graceof 20 cores, which although it is still ARM and arrived a few years ago, is now consolidated with digits as a blow to the table to a market that was dominated by Intel and AMD. Nvidia’s commitment is still far from the average user, and even further from the players, but although they are not possible to create processors that compete against Intel and the AMD Ryzen, on desktop PC, that renewed alliance with Nintendo to create Switch 2 can be, if sales accompany, the impulse that they lacked to finish deciding and being The third player in the battle of the PC consolidated. Your proposal? Beyond gross power, artificial intelligence nuclei for Push the hardware Beyond the possible until now. But of course, they would have to develop a X86 processor. Or that or throwing into the pool and marking an adventure with a valve that is already trying to stem Compatible with ARM. Although, of course, all this would be nothing if Nvidia, which money does not lack, would have signed an exclusive contract with Nintendo for this type of hardware. Whatever happens, Jensen Huang seems like engaged With Nintendo’s vision, and they may not end up getting into mud with Intel and AMD as the third company in discord, precisely, because with Switch 2 and their AI -based technology already have more than enough reasons to say an “EY, which in this segment we also have much to say at the power level”. After all, no matter how veteran the first switch was very obsolete that his heart was, I kept selling like hot bread Although the rest of hybrid systems offer much more as far as gross power is concerned. Images | Xataka, Ifixit In Xataka | I have played the ‘Nintendo Switch 2 Welcomme Tour’ thinking that it was a payment manual. It turns out that it is a science museum

Huawei is getting unstoppable. Everything he is doing seeks to beat Nvidia in both in China and beyond

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Huawei is determined to gradually absorb the market share that keeps Nvidia in China. Until just a few months ago this last company monopolized Something more than 90% of the Chinese market of the chips for artificial intelligence (AI), but after the entry into force of the last US sanctions package its leadership is all likely to be compromised. Even so, Nvidia has a very important asset that is helping her defend her presence in the Chinese market: 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 has Cann (Compute Architecture for Neural Networks), which is its alternative to CUDA, but for the moment CUDA dominates the Chinese market. These are the two great buzas of Huawei to beat Nvidia Huawei wants to snatch the leadership in performance in AI applications from NVIDIA. 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 it will leave The H20 GPU of Nvidia. 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. It is evident that to grow in the market is essential have good hardwarebut it is also crucial to position itself strongly in training the great language models, in Inference processesor, better yet, in both contexts. “Training is important, but it only happens a few times. Huawei focuses mainly on inference, which will ultimately give us access to more customers.” This declaration of Georgios Zacharopoulos, a senior researcher of AI who works on the acceleration of inference in the Huawei laboratory in Zurich (Switzerland) clearly reflects The effort that this company has made for years to dominate inference: “Training is important, but only a few times. Huawei focuses mainly on inference, which will ultimately give us access to more customers.” Inference is broadly the computational process carried out by language models with the purpose of Generate the answers which correspond to the requests they receive. In any case, the information we have reflects that the GPU Ascend 910D will allow Huawei to compete with the chips for the most advanced NVIDIA both in inference and in training. The US response to the steps that Huawei is not taking long to arrive. And is that the Department of Commerce has approved a resolution whereby no country on the planet can buy the GPUs for the Ascend de Huawei. According to this American institution, this Chinese company has produced these chips using US technologies illegally, so its export outside the country borders governed by Xi Jinping violates the export controls of the Department of Commerce. In practice to the US it will cost a lot to control the commercial flow of the GPUs for Huawei outside China, especially when these semiconductors They go to allies of the latter country. Its strategy to exert pressure on countries interested in getting the Huawei chips is to announce fines, the possibility of revoking export rights, and even establishing criminal consequences. In Xataka | In a low voice, China has begun to remove some tariffs from US products. Your concern: the chips In Xataka | China’s domain of rare earths has nothing to do with geography: it is born from 39 university programs

Nvidia desperately seeks engineers for its Taiwan R&D center. They even accuse you of “stealing them” to TSMC

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Nvidia smiles at the future. The pulse held by the US and China governments is degrading their business in the latter country because the US administration prevents them from selling its chips to its Chinese clients to artificial intelligence (Ia) more powerful. Even so, the company led by Jensen Huang currently monopolizes about 90% of the market of the GPUs for Ia. It is likely that in the medium term its quota will be reduced against the presumable growth of competitors such as Huawei or AMD, but right now Nvidia has no reason to worry. And it does not have them because the semiconductor market to grow a lot over the next few years. According to the AMR consultant (Allied Market Research) In 2031 it will have a turnover volume of More than 263,000 million dollars. It is a real barbarity, especially if we are in mind that in 2021 its business amounted to just over 11,000 million dollars. Although the NVIDIA quota is reduced during the next few years, it is reasonable to assume that its business volume will be increased by market growth. The problem facing this company is now another. This is what the engineers who hire in Taiwan pay Nvidia’s directive dome seems to be very clear about what to continue growing next to the AI ​​chips market for data centers: expand. It is about it. However, we must not overlook that this company is dedicated to the design of integrated circuits, so it does not need to invest in the construction of semiconductor manufacturing plants; What needs to expand its network of research and development centers (R&D). And Taiwan is a very attractive destination. Nvidia already has an R&D center in Taiwan, and is launching another The semiconductor industry is The main support of the island’s economywhich has caused Taiwanese universities to develop specialized training programs that seek to place the highly qualified technical staff on the labor market that They require companies such as TSMC, UMC or Foxconnamong others. Nvidia already has an R&D center in Taiwan, and is launching another. However, you are facing a very serious problem: it is having many difficulties in recruiting the highly qualified engineers you need. It is surprising, but although in Taiwan thousands of engineers are formed every year, the companies of the island have a hard time recruiting as many as they need. Even to TSMC. To solve this problem NVIDIA has chosen to offer very high wages. An engineer who has just finished his studies and, therefore, has no experience, pays him a maximum salary of $ 83,000 annually. And an experienced engineer up to 185,000 dollars a year and a very juicy bonus. According to the Taiwanese medium EBC News Nvidia’s aggressive salaries’ policy responds to the need for attract TSMC engineers highly qualified. It does not seem crazy. After all, the law of supply and demand works. Image | Nvidia More information | Tom’s hardware In Xataka | Nvidia has to deal with the absolute distrust of several US legislators. His plan in China is in danger

Nvidia has to deal with the absolute distrust of several US legislators. His plan in China is in danger

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The dispute that Eeuu and China hold It is deeply conditioning the business of many Chinese companies, such as Huawei, SMIC or Hua Hong semiconductor, but is also affecting a very important way To some western companies. The Dutch ASML and the American Nvidia They are in all likelihood that are facing the greatest challenges as a result of the pulse maintained by the American and China administrations. The Chinese market is essential for both, but the sanctions that have approved US governments and the Netherlands They prevent them from selling their customers led by Xi Jinping a good part of their product porpholio. Even so, both companies are doing what is in their hand to defend their economic and commercial interests, and dispense with the Chinese market is not one of its options. In fact, Nvidia has officialized His intention to put a specialized installation in the design of integrated circuits in Shanghai (China). Some legislators consider that Nvidia’s plan is a threat to the US The newspaper The Wall Street Journal It has been made with a letter in which the Republican senator by Indiana Jim Banks and the Democratic Senator for Massachusetts Elizabeth Warren are directed directly to Jensen Huang, the general director of Nvidia. In this text these legislators argue that the installation that Nvidia plans to open in Shanghai represents a direct threat to US national security due to the possibility that China acquires the ability to design avant -garde GPU for artificial intelligence (AI). “No American company should be helping the Chinese Communist Party to close the gap in artificial intelligence,” Nvidia has responded immediately. There is too much at stake to take this light attention call. A spokesman for this company has expressed that its purpose “It is simply to rent a new space that the company’s employees can use after the return to work after the Coronavirus pandemic. The scope of work will not change“However, Nvidia’s official justification does not seem convincing for Warren and Banks. In fact, this last legislator has declared that “no American company should be helping the Chinese communist party to close the gap in artificial intelligence.” It is evident that this is an accusation of full -fledged Nvidia. A very serious accusation that complicates the future plans of the company led by Jensen Huang in China if we are in mind that the manifesto is backed at least by a senator of the Republican party and a senator of the Democratic Party. In addition, this claim comes at a very important moment for Nvidia. The engineers of this company have just concluded The development of a GPU With Blackwell microarchitecture aimed at replacing to the H20 chip whose sale in China has been prohibited by the last sanctions package of the Department of Commerce. The Nvidia Plan is that TSMC starts the manufacture of this GPU expressly intended for the Chinese market in June, but at the current situation it would not be surprising at all that the Department of Commerce prevents its delivery to Chinese clients in Nvidia. We will see what happens finally, but the panorama does not paint anything well for the company led by Jensen Huang. Image | Nvidia More information | The Wall Street Journal In Xataka | The US gives Huawei a great opportunity: to get its new chip for AI with the Nvidia market in China

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