Meta is betting everything on superintelligence: billion-dollar investments, mega data centers, and a risky AI race

### Artificial Intelligence at Any Price: Meta's Unprecedented Transformation to Superintelligence ### From Social Media Giant to AI Pioneer: Meta's Risky Leap to Superintelligence ###

Why is Meta launching such a massive AI offensive?

Meta is undergoing one of the most ambitious corporate transformations in technology history. After years of focusing on social networks, CEO Mark Zuckerberg is now putting all his eggs in one basket: artificial intelligence. But why is this shift so radical, and why is the company investing hundreds of billions of dollars in AI infrastructure?

The answer lies in competitive pressure. While OpenAI led the AI ​​revolution with ChatGPT and Google countered with its powerful resources, Meta lagged significantly behind. Zuckerberg's own AI models, including the failed Behemoth project, couldn't keep up with the competition. The company realized that without a dominant position in AI development, it could lose its future as a technology leader.

Zuckerberg clearly states the goal: Meta wants to create a "personal superintelligence for everyone on the planet." This vision goes far beyond conventional chatbots. These are AI systems that surpass human intelligence in every respect and are intended to function as personal assistants. AR glasses, in particular, are expected to play a key role in this, as they provide the ideal interface between humans and AI.

The urgency of this transformation is also reflected in Meta's current market position. Although the company generates billions with its social networks, it is still perceived on the stock market as an "advertising company with side projects." Zuckerberg wants to prove that Meta is a fully-fledged technology company of the future.

How much money does Meta actually invest in AI?

The scale of Meta's AI investments is breathtaking. The company plans to spend between $66 billion and $72 billion in 2025, with the majority going into AI infrastructure. This sum exceeds the gross domestic product of many countries and underscores the seriousness of Zuckerberg's ambitions.

In the second quarter of 2025, Meta invested $17 billion in data centers and AI chips alone. These massive expenditures are financed by booming advertising revenues, which rose 22 percent to $47.5 billion during the same period. The company can afford these investments because its core business is flourishing.

In addition to the infrastructure investments, Meta secured $29 billion in external financing for additional AI projects. This complex financing structure includes equity and debt from private financial institutions such as Pimco, Blue Owl Capital, Apollo Global Management, and KKR.

A particularly costly aspect is Meta's talent acquisition. The company acquired a 49 percent stake in Scale AI for $14.3 billion, primarily to recruit its CEO Alexandr Wang to lead its new Superintelligence Lab. This "reverse acquisition" demonstrates Meta's willingness to pay for top talent.

Which data centers is Meta planning and how big will they be?

Meta's data center planning is reaching science-fiction dimensions. The first multi-gigawatt center, called "Prometheus," is scheduled to go online in 2026 and will comprise approximately 500,000 Nvidia GB200/GB300 accelerators. By comparison, OpenAI's Stargate project plans "only" 400,000 GPUs.

The even larger "Hyperion" project is planned to be scaled up to 5 gigawatts over several years. This plant in Louisiana would be the size of the Manhattan core—about 10 kilometers long and 2 kilometers wide. Its energy consumption would be equivalent to the electricity consumption of 10 million German households or 4 million US households.

Further "Titan clusters" are planned, one of which is expected to cover a significant area of ​​Manhattan. These bombastic names—Prometheus, Hyperion, Titan—reflect Zuckerberg's ambitions. In Greek mythology, Prometheus represents the Titan who brought fire to mankind, while Hyperion is the god of light.

The scale is unprecedented in the technology industry. Meta aims to become the first company to operate an AI data center with more than one gigawatt of capacity. This infrastructure is intended not only to give Meta a competitive advantage but also to attract additional talent seeking access to unlimited computing power.

How aggressively does Meta recruit AI talent?

Meta's talent acquisition has reached a new level in Silicon Valley. The company offers individual AI researchers salary packages of up to $300 million over four years, with up to $100 million available in the first year alone. In one extreme case, one candidate was reportedly even offered $1.5 billion over six years.

Zuckerberg personally leads this poaching campaign. He contacts potential candidates directly via WhatsApp and invites them to interviews. He uses an internal list of the world's top AI talent, who typically possess three characteristics: a PhD in a relevant AI field, experience in a leading lab, and contributions to significant AI advances.

The strategy has seen success, but also setbacks. Meta has recruited at least 50 new employees for its AI initiative, including 20 researchers from OpenAI and 13 from Google. Particularly valuable is Shengjia Zhao, one of the co-developers of ChatGPT, who now works as Chief AI Scientist at Meta.

But high salaries alone aren't always enough. Several prominent new hires left Meta after just a few weeks, including Ethan Knight and Avi Verma, who returned to OpenAI. One OpenAI employee commented dryly on Meta's offers: "That's about what I'd have to be paid to work for Meta."

Why did Meta suddenly stop all new AI hires?

In August 2025, Meta unexpectedly imposed a complete hiring freeze for its AI department. This decision came after months of aggressive recruiting and costly talent hunting. Even internal team transfers were blocked, and new hires are now only possible with the personal approval of Chief AI Officer Alexandr Wang.

Officially, Meta cites organizational reasons for the shutdown. The company wants to "create a solid structure for its new superintelligence efforts" and consolidate the team internally. After the massive expansion, it now needs time for structuring and internal organization.

However, external factors also played a role in this decision. Shareholders criticized the unprecedentedly high personnel expenses, and the broader tech selloff intensified concerns about a potential AI bubble. OpenAI CEO Sam Altman publicly stated that he believed AI was in a bubble, putting additional pressure on all AI investments.

The internal situation at Meta was also tense. The Superintelligence Lab underwent multiple restructurings, leading to frustration among employees. One former employee described the rapid development as "too dynamic" and complained that his supervisor had changed positions several times.

The hiring freeze marks the end of one of the most aggressive recruiting drives in technology history. Meta had spent hundreds of millions of dollars on talent in just a few months without yielding the hoped-for technological breakthroughs.

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How does the competition react to Meta’s offensive?

OpenAI reacted particularly harshly to Meta's poaching attempts. Chief Research Officer Mark Chen described the situation internally as feeling "like someone broke into our house and stole something." The company subsequently adjusted its compensation packages and developed new retention strategies.

CEO Sam Altman publicly attacked Meta's methods, calling them mercenary. "Missionaries will defeat mercenaries," he wrote in an internal message, emphasizing that he relied on his company's visionary culture rather than pure monetary incentives. Altman warned of "deep cultural problems" at Meta caused by the focus on money.

Google, on the other hand, strategically used the situation to its advantage. Instead of reacting defensively, the company managed to win Meta as a customer. Meta booked over $10 billion worth of cloud services from Google for the next six years. This deal demonstrates that even competitors in the AI ​​space are collaborating when it comes to infrastructure.

The entire industry is experiencing exploding salaries. According to industry experts, total compensation for mid- to senior-level research roles has nearly doubled since 2022. Microsoft Research Director Peter Lee compared the cost of a top-notch AI expert to that of an NFL quarterback.

Despite the intense competition, many of the best talent remained loyal to their original employers. None of the OpenAI researchers to whom Meta offered the highest sums ultimately switched. This suggests that factors such as work culture, technological vision, and research freedom are just as important as financial incentives.

What is Meta’s long-term AI strategy?

Meta's long-term AI strategy differs fundamentally from its competitors. While other companies rely on centralized AI systems for business and research, Meta pursues a "personal superintelligence." This is intended to act as an individual companion in everyday life and engage with creativity, relationships, and cultural interests.

The strategy is based on four pillars. The newly established Meta Superintelligence Labs are divided into four specialized teams: the TBD Lab for large models, an AI product department, an infrastructure team, and a basic research group. This structure is intended to enable faster innovation and optimally coordinate various aspects of AI development.

A key difference from competitors is Meta's open-source approach. While OpenAI is increasingly relying on closed models, Meta continues to make its AI developments freely available. The Llama language model is open source and can be used by developers worldwide. This strategy is intended to position Meta as a trustworthy alternative.

AR glasses play a key role in Meta's vision. Zuckerberg sees them as the preferred interface for AI applications and predicts: "Anyone who doesn't wear AI glasses in the future will be at a cognitive disadvantage." Meta has already invested $3.5 billion in eyewear manufacturer EssilorLuxottica to realize this vision.

The integration of AI into existing platforms is already well advanced. Meta successfully uses AI for personalized content on Facebook and Instagram, resulting in a five percent increase in dwell time on Facebook and a six percent increase on Instagram. Now, they plan to take these successes to the next level.

How does Meta's offensive affect the tech industry?

Meta's aggressive AI offensive is fundamentally changing the balance of power in the entire technology industry. The company, long considered a pure social media player, is now positioning itself as a serious competitor to established AI leaders like OpenAI and Google. This shift is forcing all players to rethink their strategies.

Talent mobility in the AI ​​industry has reached a new level thanks to Meta's actions. Top researchers now use chat groups on Slack and Discord to discuss job openings and coordinate negotiation strategies. This transparency is driving up salaries across the industry, creating a market that's more akin to professional sports than the traditional technology industry.

The battle for computing resources is also intensifying. Meta's announcement to build multi-gigawatt data centers is forcing competitors to make similar investments. xAI is already planning data centers with 1.1 gigawatts of capacity, while OpenAI is aiming for up to 1.2 gigawatts with Project Stargate. This escalation is leading to an arms race in infrastructure.

At the same time, unexpected collaborations are emerging. Meta's $10 billion deal with Google for cloud services demonstrates that even direct competitors are collaborating when it comes to critical infrastructure. This pragmatic approach could set a new pattern for the industry, with companies competing in some areas and cooperating in others.

The impact on smaller companies is already being felt. Startups are struggling to compete with the astronomical salaries of tech giants, leading to a concentration of talent among a few large players. This could hamper innovation in the industry in the long run if only the largest companies have access to top talent.

What risks does Meta's multi-billion dollar bet entail?

Meta's AI offensive is fraught with significant risks that could jeopardize the entire company. The biggest risk lies in the sheer size of the investments. With planned spending of over $70 billion for 2025 alone, Meta is staking a significant portion of its resources on an uncertain future. If AI breakthroughs fail to materialize, this could destabilize the company financially.

Dependence on external factors is another critical risk. Meta's AI strategy relies heavily on Nvidia chips, whose availability and prices the company cannot control. Supply bottlenecks or geopolitical tensions could jeopardize the entire strategy. Furthermore, the energy requirements of the planned data centers are so high that Meta is considering its own nuclear power plants.

Internal tensions threaten the company's cohesion. The preferential treatment of newly hired AI experts over long-standing employees is leading to frustration and departures. Prominent researchers like Joelle Pineau have already moved to competitors, and the restructuring is creating uncertainty throughout the company.

Regulatory risks are increasing, especially in Europe. The EU Commission is already examining restrictions on personalized advertising, which could threaten Meta's core business. Additional AI regulations could complicate the development and deployment of Meta's superintelligence models.

The technological challenges are immense. Despite billions of dollars in investment, it remains unclear whether Meta can actually develop superintelligence. The failed Behemoth project shows that money alone doesn't automatically lead to technological breakthroughs. The competition, especially OpenAI, has a significant lead that could be difficult to catch up with.

Will Meta be able to achieve his goals?

The prospects for success of Meta's AI offensive are mixed and depend on several critical factors. On the positive side, the company has the financial resources to invest long-term. Booming advertising revenues of over $47 billion per quarter provide Meta with the necessary financial stability.

Meta's open-source strategy could prove to be a decisive advantage. While other companies are increasingly siloing their AI models, Meta is focusing on transparency and community development. This strategy could enable broader adoption and faster innovation, as developers worldwide can contribute to improving the models.

The integration into existing platforms has already been successful. Meta is already effectively using AI for content recommendations and has been able to measurably increase engagement times. This proven application of AI demonstrates that the company is fully capable of successfully implementing the technology.

However, significant challenges stand in the way. The hiring freeze and the departure of researchers point to internal problems. The frequent restructuring and the failure of the Behemoth project raise doubts about the company's ability to execute.

The competition isn't sleeping. OpenAI, Google, and other companies are also investing billions in AI research, some of them with a significant technological lead. Meta's success depends on whether the company can close this gap while simultaneously realizing its own vision of personal superintelligence.

Time will tell whether Zuckerberg's billion-dollar bet pays off. The next two to three years will be crucial in assessing whether Meta can truly become a leading AI company or whether the massive investment will go down in corporate history as a costly failure.

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