The shift from assistant to operator For a long time, public discussion treated artificial intelligence as an assistant. You ask, it answers. You upload a document, it summarizes it. You request a draft, it proposes… An always-on AI agent inside government is not a convenience feature, it’s a security risk
Convenience is not the same as learning Large language models are now part of everyday life in education, work, and public communication. They draft text, summarize documents, suggest ideas, organize arguments, and respond instantly to… How to Use Large Language Models Without Letting Them Weaken Your Thinking
Transparency is not optional, it is a requirement Artificial Intelligence has already moved from novelty to routine production. It writes text, generates images, edits audio, creates video, suggests code and helps reshape entire workflows. The… Everyone should know what has been produced by Artificial Intelligence
Why governments, researchers, and businesses should back open-source agentic AI built on low-cost local LLMs The public debate on artificial intelligence is still shaped by hype, marketing language, and the illusion that the largest commercial… AI must not become the next dependency
From automation gains to the trap of code overproduction The new generation of AI tools for software development is no longer limited to autocomplete or quick code suggestions. Coding agents can inspect a repository, propose… Coding agents should be used by programmers, not instead of programmers
From dependency on foreign systems to Greek digital sovereignty The debate on artificial intelligence in Greece can no longer revolve around which foreign model to rent, which proprietary API to plug into a service, or… Apertus and the case for a fully open Greek AI model
Fluency is not reliability Large language models create a dangerous illusion for both public administration and private organizations. They look like universal productivity engines: fast drafting, fast summaries, fast answers, fast recommendations. But speed and… Large AI models should not be used in administration without guardrails, verification, and experienced human review
From explicit programming to the synthesis of solutions For decades, computer science was grounded in a relatively stable principle: humans define the rules, computers execute the instructions, and the result is largely predictable, repeatable, and… AI as a paradigm shift in computer science
When innovation is built on insecure foundations The case of McKinsey’s Lilli platform is not just a dramatic breach story. It is a warning about how many AI platforms are being deployed today across companies… AI Without Security by Design Puts Citizens’ and Workers’ Data at Risk
Why the current AI infrastructure boom mainly enriches NVIDIA and other multinationals The global race to build “AI Factories” is being sold as the next great industrial transformation. Governments promise sovereign compute, strategic autonomy, new… AI Factories or digital dependency?
The typical ML engineer follows a familiar workflow: choose an architecture, train, evaluate. This mindset leads to searching for a single model that solves the entire problem on its own. In practice, no single computational… Beyond single models: architecture as competitive advantage
An approval that changes the scale of ambition The approval of the proposal “Enhancing multilingual foundation models through lexicographic grounding: advancing GlossAPI for Apertus Greek language integration” by the Swiss AI Initiative is more than… GlossAPI and the Swiss AI Initiative: a strategic investment in Greek as public digital infrastructure