The tech giant is beginning to use publicly shared posts and comments from adult users in the EU to optimize its language models. This approach highlights the role of cloud infrastructure in the age of AI trained on massive datasets.
Meta has officially commenced training its generative artificial intelligence models in Europe using publicly shared content from adults on its platforms, such as Facebook and Instagram. This decision, announced as of April 15, 2025, marks a key step in the evolution of its AI systems and has significant implications for the cloud ecosystem, data governance, and the infrastructure that supports it.
The company will utilize posts, comments, and other public interactions generated in the EU, as well as queries made directly to Meta AI, its generative AI assistant. This process is part of the gradual rollout of Meta AI on the continent, following its initial launch last month in messaging apps like Messenger, WhatsApp, and Facebook.
Generative AI and Public Data: A High-Voltage Combination
From a technical standpoint, training large-scale models (LLMs) like those developed by Meta requires continuous access to massive volumes of textual data that are representative of the language and contexts in which they will operate. In this case, Meta claims that data from European users will refine the understanding of local dialects, cultural expressions, contextual use of humor, and specific social references.
Although using public content for training is not new in the industry—OpenAI and Google have done it previously—Meta’s move comes under a more demanding regulatory framework. In 2024, the company chose to postpone this training in Europe until it received a clear assessment from regulators. Following a favorable opinion from the European Data Protection Board (EDPB) in December, Meta reactivated its strategy, this time in direct coordination with the Irish Data Protection Commission (IDPC).
Regulatory compliance is supported by several technical pillars: the process does not include private messages or content from minors, and an accessible objection form is available for any EU user to oppose the use of their public data in the training.
Infrastructure and Computing: The New Heart of AI
Meta’s announcement also underscores the essential role of large-scale cloud infrastructures in supporting these operations. Training an LLM with information from millions of European users involves intensive storage capabilities, low-latency networks, distributed parallel processing, and strict compliance with data localization policies.
Multimodal training—which includes text, images, video, and audio—requires specialized GPU clusters and high-performance distributed storage systems capable of feeding models with low latency and maximum reliability. Additionally, mechanisms for data versioning, anonymization, and traceability are critical to respond to potential audits or deletion requests in compliance with European regulations.
From the perspective of the cloud and infrastructure sector, Meta’s case illustrates a paradigm shift: foundation models are not only intensive consumers of computational resources but also of user-generated content, which becomes a strategic asset.
Risks and Challenges for the European Ecosystem
Meta’s decision also reignites the debate around technological sovereignty and ethical data management. While hundreds of millions are invested in building efficient data centers and interconnected networks, the raw material that fuels AI continues to be, in many cases, user content that is not always fully aware of the extent of its reuse.
For European cloud providers and local infrastructures, this situation presents competitive and regulatory challenges. While Meta ensures compliance with GDPR and the National Security Scheme through robust governance and control systems, the technological dependency on U.S. platforms remains high. This reinforces the need for a European sovereign AI strategy that considers not only chips and data centers but also the data that trains the models.
As demonstrated, the most valuable product in the digital economy is not the application, nor even the algorithm: it is the user. Their behavior, language, questions, and emotions become—instantly—part of an artificial intelligence that replicates, predicts, and generates content. And all this is hosted in cloud infrastructures that become key pieces in this new digital power landscape.
Conclusion
Meta’s move anticipates a trend that will become more widespread in the coming months: training generative AI with regionally sourced public data as a basis for offering more “local” and personalized experiences. However, this transformation cannot be dissociated from the technical and ethical debate regarding how, where, and with what guarantees these processes are executed. In this sense, the cloud sector and infrastructure providers have a crucial role in ensuring that innovation in artificial intelligence aligns with the protection of digital rights and European technological sovereignty.
Source: Meta and Artificial Intelligence News