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The way we produce and consume energy is changing. Across Europe, Energy Communities are bringing citizens, local organizations, renewable energy producers, and energy assets together around a more decentralized energy model. Solar panels generate electricity locally, batteries store excess energy, smart meters capture consumption patterns, and flexible assets can adapt their operation according to the

As electric vehicles, renewable energy, and connected devices continue to grow, so does the amount of data generated at the edge of the network. Processing this data efficiently is becoming essential for building faster, smarter, and more resilient energy systems. At Indigma, we are proud about our initiative ARIEL (federAted oRchestration In Ev fLeets), an

As AI-generated cartoons flood social media, a new question arises: Can a machine steal an art style without even giving any credit? In the last few days, social media feeds have been completely awash in pastel skies, dreamy forests, and wide-eyed characters that look straight out of a Studio Ghibli film. The resemblance isn’t subtle.

Federated Learning (FL) is often celebrated as a privacy-first machine learning technique and for good reasons. Instead of collecting data in one central place, FL allows model training to happen directly on users’ devices, keeping the raw data where it belongs. But here’s the truth: Federated Learning alone does not guarantee complete privacy. Yes, it’s

In a world where data is the new oil, protecting them has never been more important, especially when considering strict laws and regulations like the GDPR. Every time you type on your phone, ask your voice assistant a question or use a smart device, there’s a silent agreement: your data powers artificial intelligence, but at