NVIDIA

In a financial carom, Google has stood up to NVIDIA, leaving an unexpected winner in the crazy AI race: Larry Page

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NVIDIA promised them very happy being the best-positioned AI chip manufacturer. At least it was until Google has started making chips. This new scenario has excited investors, who have rushed to buy Alphabet shares, making your price goes up up to 6.3% from one day to the next, and accumulating an advance of more than 75% since its August price. This increase in the value of Google’s parent company has also coincided with a dip in Oracle’s valuation, which has caused chaos on the podium of the world’s largest fortunes. according to Forbes. What AI gives you, AI takes away. A few months ago, Larry Ellison, founder of Oracle rose as the second largest fortune in the world, overtaking Mark Zuckerberg. His fortune reached 291.6 billion thanks to the good growth prospects posed by the construction of the data centers for AI. In fact, the Oracle founder’s fortune grew so much that he was close enough to the unattainable Elon Musk as to threaten its position on that list. Just as AI raised Larry Ellison to become the world’s second-largest fortune, AI he has taken that place away to hand it over to Larry Page, who reaches that position with a fortune of 261.5 billion dollars. Google rises, Oracle falls. He Google stock rally contrasts with the downturn suffered by the main architect of the cloud infrastructure in which AI lives, leaving up to 6.79% of its price in recent days. This decline has meant that Ellison’s fortune, with a strong influence of Oracle on its income balance, has suffered, falling to $256.7 billion, being displaced to third position. That same stock market momentum of Google has taken another founding partner, Sergei Brin, to fourth position, with a fortune of 242.4 billion dollars, while Alphabet shares brought the company closer to a market capitalization of almost 4 billion dollars. Mark Zuckerberg and Jeff Bezos didn’t even see it coming. The most pronounced falls in recent months have been those of Jeff Bezos and, above all, Mark Zuckerberg, who, accustomed to remaining in the Top 3 of the greatest fortunes, fall to fifth and sixth position in the ranking of Forbes. The decline in Mark Zuckerberg’s fortune is especially striking, due to the poor performance of Meta shares in recent weeks. Interestingly, Meta shares have broken their downward trend following Google’s announcement to get into the semiconductor business for AI and the rumors that Zuckerberg could change NVIDIA processors for the Tensor Processing Unit manufactured by Alphabet. Larry Page and Sergei Brin: same company, different fortunes. Although Page and Brin co-founded Google and share control of the company through their shares, both millionaires do not own exactly the same number of shares, and that detail makes a big difference in their assets. According to public statements of Alphabet before the US Securities and Exchange Commission (SEC), between the two magnates they concentrate 87.9% of Alphabet’s class B shares, which grant 10 votes per title. However, the figures show that Page has just over 389 million shares, while Brin account with some 362.7 million of these shares, which makes Page the main beneficiary of the rally in the shares of the company they founded. Brin has been more generous with science. The key to this gap is that Sergei Brin has been much more active than Page in donating and selling part of his stake in Alphabet, and that has reduced his share package over time. Brin has been targeting large volumes of Alphabet and Tesla shares to research donations of treatment against Parkinson’s disease, bipolar disorder or autism, after being discovered a genetic mutation which made him prone to developing that disease. In Xataka | Larry Page and Sergey Brin founded Google and became millionaires. Now they are dedicated to collecting gigantic airplanes Image | Flickr (Fortune Global Forum, TED Conference)

NVIDIA, Microsoft and Anthropic have signed a new multi-million dollar agreement

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Microsoft, NVIDIA and Anthropic have announced recently a series of strategic alliances that redistribute the map of power in the generative AI race. Anthropic will deploy its Claude models in Azure, Microsoft’s cloud, while committing to purchase $30 billion in computing capacity and contract additional capacity of up to one gigawatt. For their part, NVIDIA and Microsoft will invest up to 10,000 and 5,000 million dollars respectively in the startup. The triangular pact, in figures. Anthropic will have access for the first time to Microsoft Foundry, where its most advanced models (Claude Sonnet 4.5, Claude Opus 4.1 and Claude Haiku 4.5) will be available to Azure enterprise customers. With this, Claude becomes the only advanced model present in the three main cloud services in the world. Additionally, Microsoft promise maintain the integration of Claude into its Copilot family, including GitHub Copilot, Microsoft 365 Copilot, and Copilot Studio. In parallel, NVIDIA and Anthropic establish their first collaboration of such caliber. To do this, they will work together in design and engineering to optimize the Claude models on future NVIDIA architectures, starting with systems Grace Blackwell and Vera Rubin. Microsoft looks for alternatives to OpenAI. This move comes just weeks after OpenAI will complete its restructuring towards a for-profit model and will renew its agreement with Microsoft. Although Microsoft maintains a 27% stake in OpenAI valued at about $135 billion, the new terms of the deal have relaxed some key elements of its exclusivity. And OpenAI can now collaborate with third parties and release open source models, while Microsoft no longer has the right to try to be its sole computing provider. According to The Vergethese changes in the relationship with OpenAI have precisely allowed Microsoft to close this pact with Anthropic. In fact, Microsoft had already been betting on Claude in some of its services, for example, in Visual Code, prioritizing Claude over GPT-5 in your model selector. It also recently added Claude Sonnet 4 and Claude Opus 4.1 to Microsoft 365 Copilot. Circular financing: money that comes back. As is customary in these AI macro-agreements, a clear circular financing dynamic. Microsoft and NVIDIA pump capital into Anthropic, which in turn commits to spending tens of billions on infrastructure provided by those same companies. In essence, some of the money invested returns as revenue from cloud computing services and specialized hardware. It is not a new phenomenon: in fact, Anthropic already has similar agreements with Amazon, which has invested 8 billion dollars and continues to be its main infrastructure provider, and with Google, which in recent weeks announced a pact to provide up to one million TPUs to the startup. These types of cross-investments have become the norm in the generative AI ecosystem, creating almost symbiotic relationships between companies to meet their computing and infrastructure needs. one gigawatt. Building a data center with that capacity could cost around $50 billion, according to industry estimateswith some 35 billion dedicated exclusively to AI chips. Although the figure pales compared to OpenAI’s Stargate project, which aspires to 500,000 million dollars In investing, Anthropic’s approach seems more pragmatic and execution-focused. The company led by Dario Amodei has gained ground in the business market with less media noise but with solid results. And its annualized revenue rate now reaches $7 billion, although like the rest of the AI ​​startups it continues to spend much more than it earns. Diversification. What is really relevant about this agreement is that it confirms a trend: that large technology companies are no longer betting everything on a single card in AI. Microsoft, which has invested billions in OpenAI since 2019 and made it the flagship of its AI strategy, is now expanding its portfolio with Anthropic. For its part, Anthropic demonstrates its ability to maintain multiple alliances without compromising its independence. It is the sensible option and the one that minimizes risks. Cover image | Microsoft In Xataka | Tim Cook’s end at Apple is approaching

SoftBank abandons NVIDIA in its prime. What comes next is the biggest bet in its history

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SoftBank has sold its 32.1 million NVIDIA shares for $5.83 billion, completely liquidating its position in the chipmaker, according to CNBC. It has also divested part of its stake in T-Mobile for another 9.17 billion. Why is it important. The sale speaks of a radical strategy: SoftBank is abandoning the physical infrastructure (chips) to bet directly on the application layer (AI models). This is not necessarily a lack of trust in NVIDIA (although that is not a great sign), but an extreme concentration of capital in OpenAI, where it has committed up to $40 billion and leads the stargate project of 500,000 million for data centers. The facts. SoftBank announced profits of $16.3 billion in its fiscal second quarter, driven primarily by your investments in OpenAI through the Vision Fund. The fund earned 19 billion in the July-September period, offsetting losses in other positions such as another AI giant: Alibaba. Between the lines. This is not the first time that SoftBank has sold NVIDIA. He already did it in January 2019, then liquidating a position of 4,000 million acquired in 2017. That move, made when NVIDIA shares had fallen more than 50%, received a lot of criticism for its timing. Now it repeats the move, but in a radically different context: NVIDIA is at all-time highs and dominates the AI ​​chip market. The difference is that in 2019 SoftBank sold due to the need for liquidity after the WeWork fiasco. In 2024 he sells by strategy: he needs a lot of cash to finance his bet on OpenAI and he cannot do so without liquidating winning positions. In any case, the reading is clear: when it comes to AI, SoftBank believes more in the profitability of the models than in that of the infrastructure. The money trail. SoftBank has already invested 9.7 billion in OpenAI through Vision Fund 2 since September 2024. The company will lead the Stargate project with OpenAI, contributing 19 billion of the initial 100 billion (OpenAI will put in another 19,000). Each firm will control 40% of the project. To contextualize the magnitude: SoftBank’s total commitment to OpenAI (40 billion) is equivalent to almost seven times the value of the NVIDIA shares it just sold. The contrast. The really surprising thing is not that someone is selling NVIDIA at maximums, but that that someone is precisely SoftBank. Masayoshi Son He has built his reputation as one of the most aggressive investors in the tech world, known for holding positions even when the market turns against him and for doubling down on bets in times of uncertainty. This sale of NVIDIA, the most coveted asset of the moment in technology, would have made more sense coming from conservative funds or traditional institutional investors looking to secure profits. But SoftBank is not that type of investor. That it is precisely the Vision Fund that abandons the star AI stock says more about the magnitude of its commitment to OpenAI than about its vision of NVIDIA. Yes, but. SoftBank remains indirectly linked to NVIDIA. The Stargate project will rely heavily on NVIDIA chips for its data centers. The company also maintains its majority stake in ARM, whose architecture competes with NVIDIA’s in certain segments. In addition, Son’s record in big bets is lime and sand: the Vision Fund lost 27.4 billion in 2022 due to failed investments like WeWork (100 million invested) and FTX. OpenAI could be your great redemption. Or your biggest mistake. At stake. SoftBank’s bet represents a clear hypothesis about where value is captured in AI: not in making the chips that train the models, but in owning the models and the infrastructure that runs them. It is choosing to be OpenAI rather than being the provider of OpenAI. Time will tell if they were right to change picks and shovels for the mine itself. In Xataka | AI is a bonfire of money and the ‘big tech’ have just decided that they are going to add even more fuel to it Featured image | Wikimedia Commons, Wikimedia Commons

NVIDIA and OpenAI know that the AI ​​bubble can burst in their faces. His solution: let dad pay for the state

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Too big to fail or, in English, “too big to fail.” It is a theory of economics and finance which argues that certain corporations, especially banks, are so large and so interconnected that their failure would have catastrophic consequences for the global economy and therefore must be rescued by governments. The speech gained traction in the 2008 financial crisis and is beginning to sound again from the mouths of NVIDIA and OpenAI, no less. Government support. At an event of WSJSarah Friar, CFO of OpenAI, stated that the company will not go public in the short term (she says until at least 2027) and that its priority is growth and investment in R&D, above profitability. The most striking part of his speech was when he said that they hope that the government will support the financing of future agreements related to data centers. That OpenAI is burning astronomical amounts of money to lead the AI ​​race is something we have been discussing for a long timebut it is the first time that they directly appeal to the state to guarantee it. Shortly after, Friar collected cable in a post on LinkedIn: “OpenAI does not seek government support for our infrastructure commitments. I used the word ‘support’ and that confused the message,” but the seed was already planted. Depreciation. OpenAI is closing deals to secure computing capacity. We have seen it with his alliance with NVIDIAwith amdwith Broadcom and more recently with amazon. The complexity of the situation is that the depreciation rates of AI chips remain uncertain. As it says Washington Post’s Gerrit de Vynck in XOpenAI is going to need the best chips to be at the forefront of the AI ​​market, but financing this demand is not the same if the life cycle of the chips is seven years, as if it is only two years. The money is flowing, the question is for how long. In this uncertain scenario, government support would act as a safety net so that banks and private equity firms would feel more comfortable and continue releasing billions for OpenAI. China will win. NVIDIA is also appealing for government involvement in subtle ways. In a Financial Times event in London, Its CEO Jenshen Huang has warned that “China is going to win the AI ​​race.” Their arguments are that China has more flexible regulation and government subsidies for the energy your data centers needthat It is not little. This energy advantage allows China to compete even if they cannot buy NVIDIA’s most powerful chips. Huang doesn’t say it directly, but it is a clear wake-up call: either you subsidize the energy our data centers need or China will win. The fear. The question has been hanging over the air for a long time: Are we witnessing a new bubble? The investor Michael Burry thinks soand he is not just any investor, he was the one who made gold when the real estate bubble burst in 2008 (the movie ‘The Big Short’ is based on his story). The thing is, Burry just bet short against NVIDIA, which recently It was valued at 5 billion dollars. Fear of the bubble continues to grow, according to a Coatue report and the number of fund managers who believe we are in a bubble increased to 54% in October, up from 37% in July this year. 48% of the S&P 500 index corresponds to AI-related stocks. Fountain: Bianco Research Numbers. The fear is not at all unfounded and all you have to do is take a look at the numbers. Account Tomás Pueyo in Uncharted Territories that the economy should be in recession, but the numbers show the opposite and AI is behind this growth. The S&P 500 index is through the roof and 48% of this growth corresponds to AI-related stocks. The share price is far above what it was in the dotcom bustall with ridiculous benefits. And that’s not all, the economic growth of the United States in 2025 is due almost entirely to the construction of data centers for AI. According to the Economist Jason Furmanwithout taking data centers into account, the GDP of the United States would have grown only 0.1% in 2025. The creator of the newsletter Today in Tabs He gave a very graphic example: “Our economy could be reduced to three AI data centers in trench coats.” Tightrope. Returning to OpenAI, its financial director assured the Financial Times that it could be profitable simply by stopping investing too aggressively since it has a “very healthy” margin structure. The thing is, they can’t do it. OpenAI needs to achieve AGI, its great promise and the only thing that could justify this insane investment. If it fails, will cause a shock wave that can impact NVIDIA, AMD, Oracle… and end up dragging down the global economy. The competition tightens, Anthropic is eating the business market’s toast and Google is not only winning every time more users with Geminireached record revenue in the last quarterwhile OpenAI lost $11.5 billion in the same period. It doesn’t look good. Images | Wikipedia In Xataka | NVIDIA will invest 100 billion in OpenAI so that OpenAI buys chips from NVIDIA. And it’s a disturbing sign

Michael Burry just shorted NVIDIA. All good except because he was the one who predicted the 2008 real estate bubble

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Michael Burry, the well-known investor and fund manager who predicted the 2008 financial crisis, has recently shown his bearish positions against NVIDIA and Palantir just after launching on social networks a warning about excess optimism in the market. Warning which the Bloomberg media has qualified ‘cryptic’, for several reasons. The movements, made known in regulatory documents filed on Mondayhave reopened the debate on whether artificial intelligence is generating a speculative bubble. What exactly has Burry done. His investment fund, Scion Asset Management, has bought put options (puts) worth $186.5 million against NVIDIA and $912.1 million against Palantir, according to mandatory filings with the SEC. These options benefit if the stock price falls. Burry also took bullish positions (calls) in Pfizer and Halliburton, two stocks that have underperformed the market this year. Why does it matter? Burry is not just any investor. Its history is marked by having bet short against the US real estate market two years before the 2008 crashenduring criticism from his investors until Lehman Brothers went bankrupt and his fund multiplied its profits. His story inspired the film ‘The Big Bet‘. Having gained that fame, when Burry bets against something, the markets pay attention, although his track record is not infallible, as he has been wrong in the past with other bubble predictions. Click on the image to go to the post The context of their movements. Days before these positions became known, Burry broke two years of silence on social networks with a disturbing message: “Sometimes we see bubbles. Sometimes you can do something about it. Sometimes the only winning move is not to play,” accompanied by an image of his character in the film. On Monday night he posted again, this time sharing a Bloomberg chart about concerns about circular financing between OpenAI, NVIDIA and other AI companies. Market reactions. Palantir shares fell more than 10% following the news, even though the company had just raised its annual revenue guidance. NVIDIA also fell by up to 2.9%. Palantir CEO Alex Karp responded in an interview with CNBC calling the idea of ​​shorting against companies like Palantir and NVIDIA, which he says are doing “noble tasks,” “crazy.” The bubble debate. For months, many investors have expressed concern about whether the AI ​​boom is being artificially sustained. Ray Dalio, founder of Bridgewater Associates, warned recently told CNBC that “there are many things that look like bubbles,” although he clarified that bubbles do not usually burst until the Federal Reserve tightens its monetary policy. According to its “bubble indicator”, approximately 80% of market gains are concentrated in large AI-related technology companies. An important nuance. It’s not entirely clear whether Burry is betting directly on the downside or whether these options are part of a more complex strategy to protect other investments. And just as share Bloomberg, regulatory filings only reflect long positions, so if you were using these puts as a hedge for other investments, we wouldn’t know. The curious thing is that its first quarter presentation did include a note explaining that puts “could be used to cover long positions”, but the third quarter presentation does not say anything about it. Scion’s recent history. This is not the first time Burry has bet against NVIDIA. During the first trimester He has already liquidated almost his entire portfolio of listed shares and bought put options against the chipmaker. However, it has also achieved success: in the third quarter it closed positions in Alibaba (with a 36.5% profit), Estée Lauder (27%), ASML Holdings (45.7%) and Regeneron Pharmaceuticals (10.8%). Canary in the mine or false alarm? The question on Wall Street is whether Burry is once again detecting a bubble before anyone else or if he is wrong this time. NVIDIA is up 54% this year until reaching a capitalization of 5 billion dollarswhile Palantir has soared 173% thanks to its expansion in AI-related businesses. Valuations are high, but both companies continue to grow and expand their business. Be that as it may, if there is a bubble, we will find out in the worst possible way: when it bursts. Cover image | Solen Feyissa and ‘The Big Short’ In Xataka | The geopolitical irony that we are experiencing in the chip war has an unexpected beneficiary: Russia

The secret of Chinese AI companies to compete without Nvidia chips: electricity subsidized by Beijing

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Everywhere we look, there is artificial intelligence. Everyone talks about it, but what is its fuel? It’s not the data or the chips: it’s the electricity. While in the West technology companies are looking for how to power their data centers —increasingly energy hungry—, China has decided to take a different step. Beijing has designed an energy subsidy for its technology sector with a clear objective: to make the energy that powers the digital brains of its next generation of chips cheaper. Energy subsidy. Since September, the Chinese Government banned large national technology companies —including Alibaba, ByteDance and Tencent—acquire artificial intelligence chips from the American Nvidia, in an attempt to strengthen local production. However, the consequence was immediate: national processors consume more electricity. According to The Chosun Dailygenerating the same number of tokens with Chinese chips requires 30% to 50% more energy than with Nvidia’s H20, which sent electricity bills skyrocketing and led companies to complain to regulators. To make up for that gap, local governments introduced grants that cover up to a full year of operating costs, according to the Hong Kong media on.cc. In those provinces, industrial electricity was already 30% cheaper than in the developed coastal areas of the east, but with the new incentives the price could fall to 0.4 yuan per kilowatt-hour, a record figure for the Chinese technology industry. ¿How does the energy plan work? The scheme is relatively simple, but strategic. Local governments offer electricity discounts of up to half to data centers that use chips produced within the country. Operators that use foreign processors – such as those from Nvidia or AMD – are excluded from the program. In addition, the energy provinces receive direct support from the State to finance the discounts, with the aim of reducing dependence on technological imports and compensating for the increased consumption of local chips. According to the Financial TimesChinese data centers that rely on domestic semiconductors are, for now, less energy efficient, but the subsidy seeks to bring their costs in line with those of more advanced foreign chips. These regions—Guizhou, Gansu, and Inner Mongolia—have become hotbeds for data center clusters, thanks to their abundance of hydropower and coal. There, companies like Alibaba or Tencent are building new facilities to house their generative AI models, taking advantage of lower energy costs and tax incentives. This policy combines three strategic priorities: making energy cheaper, promoting domestic chips and reinforcing technological sovereignty. In a context of United States restrictions, each subsidized kilowatt is also a political statement. An industrial policy with a geopolitical charge. Behind the energy plan is a long-range political commitment. The Chinese Government intends for its technology companies to progressively replace imported chips with domestic processors, even if this implies higher costs in the short term. The electricity subsidy acts as a temporary bridge for national giants to adopt local chips without losing competitiveness. This measure is included in a broader national strategy of technological self-sufficiency. As the Financial Times explains in its series The State of AIChina is using its “society-wide mobilization capacity” to accelerate the development of artificial intelligence. The country already leads the number of patents and scientific publications in AI, and although the United States maintains an advantage in chips and talent, the gap narrows every year. Analyst Dan Wang, quoted by the same media, points out: “China has achieved a unique balance between engineering capacity, state control and massive industrial deployment, allowing it to advance faster than other countries in the practical application of AI.” Meanwhile, in the West… China’s decision contrasts with the energy challenges of the United States. Microsoft CEO Satya Nadella warned that the real bottleneck of AI It is no longer the chips, but the energy. In fact, he explained that many companies accumulate chips that they cannot connect due to lack of power supply. Both Microsoft and Google are already studying building modular nuclear reactors to power their future data centers, a sign of the enormous energy consumption that artificial intelligence requires. While Silicon Valley seeks electricity, China subsidizes it. This asymmetry reflects two different models: one guided by state intervention and the other by market competition. Both pursue the same goal—sustaining the artificial intelligence revolution—but with opposite philosophies. A future plugged into the State. The Chinese subsidy not only alleviates costs: it redefines the relationship between the State and the private sector in the age of AI. As analyst Arnaud Bertrand observed, US restrictions pushed China towards a different model: more efficient, more open and more collective. “By operating under hardware limitations, Chinese companies have learned to optimize resources and share open models like Qwen or DeepSeek,” wrote Bertrand on the social network That strategy, based on efficiency and diffusion, could give China a long-term advantage in global adoption, since any company in the world can download and adapt its models. The country that controls the plug. China isn’t just making the chips that power its artificial intelligence. It is also building the electrical grid that makes them possible. In a world where data is the new oil, Beijing has decided to subsidize the fuel of the digital brain. While the West debates how to connect its supercomputers, China plugs them in at a reduced price. And in this race, whoever controls the plug could end up controlling the future. Image | FreePik and FreePik Xataka | The world of AI has a problem: there is no energy for so many chips

NVIDIA is the most powerful company on the planet because it made a bet and it is winning: Crossover 1×28

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At NVIDIA they can’t stop rubbing their hands. They sell by piece and they don’t stop signing circular financing agreements that do nothing more than enlarge your position current. The company has made gold with the rise of artificial intelligence, and to talk about it we have dedicated this new Crossover 1×28 to recount the history and evolution of a company that is in a state of grace. We started by talking about how NVIDIA gained a privileged position in the world of gaming and how in the 2010s it (briefly) took advantage of the rise of cryptocurrency mining. All of this has managed to make NVIDIA enjoy the leading role in the duopoly that exists in the graphics card market for gamers: only AMD overshadows it, although Intel in recent times has tried to carve out some space for itself. However, what catapulted the company was a singular bet: to ensure that its GPUs could be used for the field of artificial intelligence. That market was still in its infancy. when CUDA emergedbut little by little the researchers working in that field were verifying that this platform was a great ally for their advances. And then, of course, ChatGPT arrived and with it the AI ​​gold rush. NVIDIA has become more essential than ever, and everyone, large and small, wants their AI accelerators for new data centers. It’s non-stop amazing and somewhat disturbingbecause the exaggerated growth of NVIDIA only validates the hypothesis that we are facing a gigantic AI bubble. On YouTube | Crossover

NVIDIA has risen to the top for its AI data centers. Your next big leap: cars

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NVIDIA has unveiled its platform Drive AGX Hyperion 10a computing and sensor system designed for any manufacturer to produce Level 4 autonomous vehicles. Uber has already signed an agreement to deploy 100,000 units across its global network starting in 2027, and Stellantis, Lucid and Mercedes-Benz have also joined the project. Why is it important. For years, autonomous driving has been a persistent promise often wrapped in marketing. NVIDIA has turned that promise into an industrial offering with standardized architecture, certified chips, and out-of-the-box simulations. It does not sell autonomous cars, but it does sell the operating system that will make them possible. The contrast. Tesla has been selling autonomy as a leap of faith for a decade, with permanent updates, its own fleet and promises of “millions of autonomous Teslas” every year. NVIDIA, on the other hand, offers an open platform where any manufacturer can plug in their hardware. Tesla wants to be an equivalent to Apple in cars. NVIDIA prefers to be something more similar to Windows. Between the lines. Automotive only accounts for NVIDIA 1.3% of its revenue, but that segment is growing faster than the rest. In any case, Uber’s announcement has no real timetable for those 100,000 units unless it has been made public. Waymo, which has been developing its robotaxis for years, is already its sixth generation and it has the financial muscle of Alphabet behind it, it barely operates 2,000 of them. There is a considerable gap between ambition and reality. The backdrop. Drive Hyperion 10 is based on two Thor chips (2,000 teraflops each), fourteen cameras, nine radars, one LiDAR and twelve ultrasonic sensors. NVIDIA has designed it with full redundancy: if a component fails, the vehicle stops safely to avoid chain errors that multiply the potential damage. Lucid will be one of the first in offering level 4 autonomous driving to individual customers and not just fleets. Its interim CEO has admitted that so far they have disappointed in terms of driving assistance. Their commitment to NVIDIA is the classic implicit recognition: it is better to buy the brain than to build it. The money trail. NVIDIA will not continue building robotaxis for now, but for now it sells infrastructure: chips, simulation software, synthetic data… And it charges for each vehicle that uses its platform. It’s a more predictable revenue model than depending on full autonomy to arrive one day. Huang, in any case, has said that that moment is near. The interesting thing is not whether he is right, but that his definition no longer depends on blind faith. It depends on regulators, certifications and industrial tests. Autonomy has ceased to be science fiction and has become an engineering problem. And those problems are solved with processes, not with promises. In Xataka | China has turned the electric car market into a crazy race. And Porsche pays for it with billion-dollar losses Featured image | Xataka

NVIDIA will invest $1 billion to continue advancing AI. The surprising thing is that it will do it in NOKIA

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Nokia stopped being in the general public’s conversations years ago. For many people, Nokia is a memory of those rugged phones from decades past. That is why it has attracted so much attention that NVIDIA, the most powerful company right now in the world of artificial intelligence, announce that it is going to invest 1 billion dollars in Nokia and that the two companies are preparing a strategic alliance around mobile networks and artificial intelligence. The immediate question is obvious: what has NVIDIA seen in Nokia to put that money there. The company in which NVIDIA has invested It is the usual Nokiathe Finnish telecommunications parent company that survived the mobile era. Its headquarters are in Espoovery close to Helsinki, and today its business focuses on the development of network infrastructures, software and advanced connectivity solutions. It is the company that provides operators around the world with technology that makes mobile networks and the expansion of the 5G. From 3210 to 5G towers. There was a time when Nokia dominated the mobile market with terminals that marked an era. The 3210, recently re-released as a single phoneor the first camera phones are part of collective memory. However, the emergence of smartphones completely changed the landscape. In 2014, Nokia said goodbye to that stage by selling its device business to Microsoft.. Since then, the mobile phones with its name belong to HMD Global, while Nokia Corporation, as we say, concentrates on network technology. The movement that no one expected. NVIDIA and Nokia have announced a strategic alliance that combines money and innovation. The American technology company will invest $1 billion in Nokia, an operation that will be carried out by subscribing new shares at a price of $6.01 per share. This is not a purchase, but rather a capital increase. In exchange, both companies will work together to develop mobile networks based on artificial intelligence, a step that prepares them for the jump to 6G. NVIDIA’s investment does not consist of purchasing shares on the market, but rather subscribing to new shares issued directly by Nokia. In total, more than 160 million titles will be created, in an operation that will expand the company’s capital. There is no change of control and the planned participation is 2.9%. The deal is subject to customary approvals before closing, but projects an interesting long-term alliance between both companies. A bet with 6G destiny. The agreement is not limited to money. With this investment, NVIDIA and Nokia are teaming up to develop a new generation of mobile networks based on artificial intelligence. The objective is for operators to be able to offer faster, more efficient services adapted to the growth in data traffic generated by AI. Dell Technologies, which provides servers, and T-Mobile US, which will test the first AI-RAN networks with a view to the jump to 6G, also participate in this roadmap. Behind the acronym AI-RAN lies the great bet of this alliance: applying artificial intelligence to the network that links our mobile phones with the antennas. This is what is known as AI-RAN. These networks learn from traffic, adjust themselves and make better use of available energy and spectrum. Omdia estimates that this segment will move more than 200 billion dollars between now and 2030. It is a technical leap, but above all a way to prepare the ground for 6G. Why Nokia is back on the scene. For Nokia, the agreement represents a capital injection and strategic validation. The company reinforces its roadmap towards new generation networks and consolidates its position in a market where it competes with giants such as Ericsson and Huawei. In addition to financing, it gains visibility: NVIDIA’s support boosts its image as a leading technological partner in the era of artificial intelligence. On the stock market, the announcement has already caused a strong rise in its shares. What NVIDIA earns (and it is not little). For NVIDIA, this alliance expands its reach beyond data centers. Getting into the network infrastructure means bringing artificial intelligence to the edge, where the data is generated. With Nokia technology, you can integrate your platform into antennas, base stations and optical systems, delivering AI capabilities directly from the network. It’s a way to extend your dominance in accelerated computing into new territory: telecommunications. The first to try it will be far from Europe. None of this will be immediately noticeable, but it will lay the foundation for the connectivity of the future. AI-RAN networks promise faster, more stable and more efficient connections, which is essential for new services that depend on artificial intelligence. From augmented reality glasses to drones or connected cars, everything aims to operate with lower latency and greater reliability. The first tests, promoted by T-Mobile US, will be carried out in the United States. Images | NVIDIA | BoliviaIntelligent In Xataka | Elon Musk already bought Twitter to control the narrative. His Grokipedia is another symptom of that obsession

OpenAI teamed up with NVIDIA and made circular financing fashionable. Anthropic has returned the ball with a surprise girlfriend: Google

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Let’s see if we were going to believe that OpenAI was going to be the only one to look for powerful allies. Nothing of that: Anthropic just did the same and has announced an eye-catching agreement with Google. The AI ​​startup will have access to up to one million Google TPUs in a pact that is worth “tens of billions of dollars.” Less noise, but a lot of nuts. The figures of the agreement are modest if we compare them with those that OpenAI has managed in its circular financing agreements with NVIDIA, amd either Broadcombut here Anthropic seems to take a very different position. Compared to colossal projects like Stargate, Anthropic’s idea is focused on execution. Without making much noise, the company led by Dario Amodei has been gradually conquering the business sector. More than 1 GW of computing capacity. On CNBC indicate that this investment will allow the creation of a data center with a computing capacity greater than 1 GW and have it ready in 2026. It is estimated that a center of these characteristics would cost about 50,000 million dollars, of which about 35,000 million would be dedicated to AI chips. It may not be comparable to Stargate and the idea of ​​investing $500 billion in data centers, but the alliance between Anthropic and Google is significant. More than circular financing. The partnership certainly features elements of circular financing, but it is more of a symbiotic relationship with that cross-investment component. The dynamic is simple and is now completed with that commercial return. The agreement requires Anthropic to buy or rent infrastructure services from Google Cloud. Virtuous circle. With its original investment in Anthropic, Google helped that company grow, which in turn allows Anthropic not only the ability to grow, but the need for enormous computing power… provided by Google. In essence, some of the money Google invests in Anthropic returns to Google Cloud as revenue. The vicious (or virtuous, as they say in the US) circle is complete. Anthropic diversifies. Anthropic’s AI models are trained and used using infrastructure from various manufacturers. Thus, they use both Google TPUs and Amazon Trainium processors and NVIDIA GPUs: each platform is assigned to a specialized workload. In the case of Google’s TPUs, according to Anthropic the focus is “its strong price/performance ratio and its efficiency.” Promising successes, but… Anthropic’s growth is evident, and its annualized revenue rate (ARR) is now estimated to reach $7 billion. Claude Code, its developer assistant, managed to generate 500 million dollars after just two months on the market. But as always, that revenue can’t hide the fact that Anthropic, like other AI startups, you continue to spend much more money than you earn. Amazon is your other great ally. In fact, the company led by Andy Jassy has invested around $8 billion, when official data indicates that Google has invested $3 billion. AWS is still considered the largest infrastructure provider for Anthropic, and its supercomputer Project Rainierbased on the Trainium 2, allows you to have a large computing capacity for every dollar invested, they point out on Amazon. The company’s influence is not only financial: it is structural. Image | Wikimedia | Fortune Brainstorm Tech In Xataka | You thought you had an amazing connection on Tinder, but you were actually chatting with ChatGPT

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