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Europe's technology trends for 2025
eenewseurope.com, Jan. 13, 2025 –
The European Innovation Council (EIC) has detailed the emerging technology trends it sees as important for the region in the coming years.
The EIC is the EU's flagship programme to support deep-tech from early-stage research to market scale-up, with a budget of over €10 billion.
"The EIC Tech Report is a comprehensive watchlist of emerging technologies and breakthrough innovations developed by both funded and aspiring EIC awardees since 2018. It highlights 34 signals, identifying technologies and innovations at early development stages in EIC data that show significant potential for future advancement," said Jean-David Malo Director of the European Innovation Council and SMEs Executive Agency (EISMEA)
While half the technology areas cover green and biological innovations, for the electronics industry, these 15 areas cover:
- Thermal management innovations from electric vehicles to data centres
- Low-impact and bio-based materials for sustainable electronics
- Ultra-thin 2D and ultra-wide band gap materials for power-efficient electronics
- Brain-inspired computing with advanced neuromorphic chips
- Emerging non-charge-based memories for specialised semiconductor applications
- Photonic integrated circuits for next-generation computing and ICT
- Quantum compilers for enhanced circuit optimisation and reliability
- Fault-tolerant quantum computing to tackle decoherence and noise
- Miniaturisation and integration of quantum systems on a chip
- Edge AI for more sustainable and accessible technologies
- Novel technology enablers for very low Earth orbit satellites
- High-precision LiDAR instruments for atmospheric and environmental monitoring
- Flexible printed circuit boards for multi-level space sub-systems improvements
- Synthetic data-driven virtual worlds in hyper-realistic digital twins of built environments
- Computational approaches for next-generation and high-entropy materials
In AI, two areas cover graph neural networks (GNN) and distributed agentic systems
Recent developments are advancing graph-driven AI systems, including GNNs, emerging graph transformers, and scalable graph databases, to improve link prediction, classification, and explainability. Knowledge Graphs integrated with generative AI, such as large language models (LLMs), enhance factual accuracy and support domain-specific personalisation in fields like healthcare and finance. Retrieval-augmented generation systems (RAGs) further optimise question answering tasks...
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