Neural networks are artificial intelligence (AI) computing systems inspired by the intricate connectivity and processing power of the human brain. They already surpass human capabilities in certain tasks and are widely used in applications such as pattern recognition, classification, and optimisation. With the potential to reshape society, neural networks have become central to major technological strategies, as seen in Google’s "AI-first" approach, and are recognised by governments and policymakers worldwide as a key future technology.
However, despite their promise, existing neural network architectures suffer from fundamental inefficiencies, particularly when scaled to large and complex systems. Current hardware operates far below theoretical limits, posing a significant bottleneck to future AI advancements. Overcoming this challenge requires a paradigm shift in how neural networks are designed and implemented.
The EU-funded INSPIRE project will introduce a groundbreaking approach by harnessing advanced photonic integration. By leveraging three-dimensional photonic waveguides, **INSPIRE** will develop a biologically inspired, fully parallel, and highly scalable architecture. This pioneering technology will unlock unprecedented computational efficiency, paving the way for next-generation AI systems with orders of magnitude greater performance.