TSMC is focusing on the lucrative AI industry, so Apple is looking for a new girlfriend. Found it at Intel

In 2023, Apple completed its transition and made all Macs in its catalog work with its Apple M-series chips. It was the end of a relationship that began in 2005, when Steve Jobs announced the transition from IBM PowerPCs to Intel chips. Then things went wrong and Apple ended up separating itself from Intel in its products, but once again there has been an interesting twist of the events. Intel does not know how to be a foundry. The integration of the Apple M1 in 2020 was the real beginning of a logical strategy: Apple wanted to design its own chips for its Macs as it had already done in its iPhone or iPad, and the result was extraordinary. The curious thing is that Apple negotiated with Intel to manufacture the iPhone chips, but Intel rejected the opportunity. When Morris Chang, founder of TSMC, asked Cook why he hadn’t chosen Intel to make those chips, responded “Intel just doesn’t know how to be a foundry (chip factory)”. TSMC turns to AI. The relationship between Apple and TSMC has been one of the most important in the semiconductor industry. TSMC makes virtually all of Apple’s advanced chips, from iPhone processors to Mac M chips. That dependence, however, has become uncomfortable for two reasons: Chip shortage: The rise of AI has made the demand for this type of chips extraordinary. TSMC is prioritizing customers with the highest volume and margin in the most advanced nodes, and there Apple competes with NvidiaAMD and other manufacturers looking for 2 and 3 nm chips. Geopolitics: 90% of the world’s advanced chip production is in Taiwanand any escalation of existing tensions with China could paralyze the supply chains of Apple and the vast majority of technology firms on the planet. Diversifying manufacturers is therefore a strategic necessity. Intel gets interesting. It is true that Intel is not the only alternative that Apple was exploring, and Samsung was another candidate to work closely with the Cupertino firm. However Intel has a first important advantage with the 18A nodeits next-generation manufacturing process that experts consider comparable to TSMC’s 2nm process. Apple has been considering this node for entry-level M chips for months. Intel will not be manufacturing Apple’s most advanced chips at the moment, but this is a potential first step so that it can be verified that Intel can indeed accomplish the task and then also manufacture its most ambitious designs. Lip-Bu Tan turns the tables. Intel’s new CEO took over in early 2025and since then the company has taken promising steps when it was in a situation really worrying. has reached agreements with Nvidia to develop x86 chip sets with RTX graphics, for example. It also collaborates with Tesla to manufacture chips with an even more advanced node14A, for Elon Musk’s future TeraFab. Preliminary agreement. Official details of the deal are not yet known, but in The Wall Street Journal they claim that said agreement exists although it describes it as preliminary. It is not currently clear which chip or chips Intel will manufacture or in which photolithographic process. It is expected that the 18A node will be used for those entry-level M chips, but it is not ruled out that the 14A will not be part of this new commercial relationship. Be that as it may, if the agreement is closed as it seems, we would be facing a definitive boost to this new strategy of foundry traditional approach—manufacturing chips for third parties—that Intel is adopting. The circle closes. Intel lost the contract for iPhone chips because it refused to manufacture them for not having enough marginand thus passed up the opportunity to be a de facto partner in probably the most lucrative product in the history of technology. He then tried correct the errorbut he didn’t succeed. Then Intel would lose the Mac chip business, which would be another major setback. Now it seems to be taking flight again, and its promising future—along with other factors—have made Apple want to work with it again. It seems that Intel, after all, is learning to be a foundry. Image | Fortune CEO Initiative In Xataka | The US’s problem in the AI ​​and humanoid race is not China: it is all of Asia and it is greatly disadvantaged

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

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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