A year ago, Zuckerberg was hiring AI talent like the world was ending, offering millionaire salaries and even buying entire companies to be able to sign Alexandr Wang. One year later, 8,000 people have been laid off, the work environment is unbreathable and We are still waiting for them to launch that great model with which to compete with OpenAI and Anthropic, all this while they spend money a lot. Despite everything, Meta has a real chance of closing positions and getting closer to the podium in the AI race.
The near future. In a complete report by Semianalysis They talk about how Meta is playing with better cards than it may seem. Muse Spark, its first language model, was somewhat disappointing, falling behind Chinese competitors such as Deepseek v4 Pro or Kimi K2.6. But the important thing is not where Meta is now, but where it can be in the near future thanks to the combination of three key elements: data, talent and computing.
Record employees. It was a very controversial decision and, as expected, Meta employees were not amused. Without them being able to object, software was installed on the company computers that I recorded everything they didnot to spy on them, but to train their AI. This data is pure gold for training agents: Meta is accumulating thousands of examples of different people solving the same tasks, while data companies like Surge or Mercor have to partner with others to be able to record their workflows. Meta has the data at home.
They say in Semianalysis that this decision is as if they had created a “top-tier startup for RL environments” within the company, with one of the founders of Scale AI leading the transformation. In addition, after the restructuring they have put at least 3,000 engineers on reinforcement learning environment tasks. All this data is key to being able to create programming agents like Claude Code or Codex from OpenAI.
Data centers. It is one of the main sources of spending for Meta, which is building several gigantic data centers whose capacities are more than 1 gigawatt. Maybe Meta cannot compete in infrastructure with hyperscalers like GoogleMicrosoft and Amazon, but things change if we confront it with frontier AI laboratories. Here, Meta has a clear advantage and, according to Semianalysis’ projections, Meta will have more computing power than Anthropic and OpenAI combined before the end of the year.
The talent. Last summer, Meta began signing talent with a checkbook. They hired at least 14 high-level researchers who came directly from Anthropic, Google and OpenAI, paid $14 billion to keep Alexandr Wang and Scale AI. Bringing together the best does not ensure that the team will work and, in fact, for months now there have been rumors of internal tensions. Of course, if they make it work, they have the talent.
keep focus. Meta may be in the rearview mirror of OpenAI and Anthropic sooner rather than later, but it is one thing to have the resources and quite another to achieve it. Meta is in a delicate moment internally, with many employees very dissatisfied with the company’s strategy. If they do not navigate these waves well, they risk becoming unfocused and lost along the way.
Image | Xataka with Magnific
In Xataka | Meta has a long history of privacy scandals. We can add one more to the list
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