From open weights to AI that can genuinely be inspected and rebuilt The word “open” is used so broadly in artificial intelligence that it risks losing its meaning. One lab publishes model weights, another releases inference code but not training code, and a third publishes a technical report while withholding the data pipeline. Each offers … Read more
The rapid development of Artificial Intelligence is making something increasingly visible that we often tend to overlook: the digital ecosystem has a very tangible physical foundation. AI models, cloud services and public digital applications run inside buildings filled with processors, storage systems, power supplies, networks, cooling loops and backup power systems. Data centers consume electricity … Read more
Why their value for the IT market lies in reuse, open standards and avoiding vendor lock-in In the IT sector, we know well that a successful prototype is not necessarily a sustainable information system. It may work perfectly in a controlled environment, yet fail when it has to integrate with existing infrastructure, be maintained for … Read more
From WiFi4EU to public connectivity infrastructure that remains open, controllable and sustainable Municipal and community wireless networks are no longer an experimental technology used by a small number of networking enthusiasts. They have become essential digital infrastructure for public squares, libraries, schools, cultural venues, health centres, tourist areas and remote communities. The European WiFi4EU initiative … Read more
How software teams turn experience into shared, open and controllable knowledge infrastructure The first phase of generative Artificial Intelligence adoption in software development focused heavily on prompt engineering. The basic assumption was that a skilled user, by formulating a request correctly, could obtain better code, more complete documentation or more accurate technical analysis. This assumption … Read more
A language model built for a specific linguistic community AMALIA is an important example of what it means to build an open language model not as a generic commercial product, but as a public research infrastructure for a specific linguistic community. Its central goal is clear: European Portuguese should not be treated as a secondary … Read more
Most discussions about artificial intelligence begin with models. Which model is stronger, faster, cheaper or more capable? For public administrations and private enterprises, however, the decisive question is different: what data does the model reason over, who governs that data, how is it connected to real workflows, and how can every answer be traced back … Read more
Artificial intelligence is entering public administration, healthcare, education, local government and state security services. The central question is not whether public institutions will use AI. They already will. The real question is who will control the infrastructure, the data, the models, the logs and the rules of use. Public authorities can either build internal capacity … Read more
From PHAROS to local models: a layered architecture for open AI The right strategy for artificial intelligence is not to choose one single technological solution. Not everything needs to run on a supercomputer, and it is equally unreasonable for every public body, university, school or business to depend permanently on commercial cloud APIs. The rational … Read more
From better retrieval to answer inspection before delivery Retrieval-Augmented Generation was introduced as a practical answer to one of the central weaknesses of large language models: their ability to produce fluent, confident text even when they do not know the answer. The core idea is straightforward. Before the model answers, the system retrieves relevant documents. … Read more
