From the human nervous system to a programmable chip – that’s the inspiration behind Spiker+, a project developed at Politecnico di Torino that transforms “spiking” neural networks – modeled after biological neurons – into highly efficient hardware accelerators, with the potential to revolutionize artificial intelligence.

The project was developed by PhD student Alessio Carpegna, under the guidance of Professors Alessandro Savino and Stefano Di Carlo, members of the SMILIES research group. Carpegna is enrolled in the PhD Program in Artificial Intelligence within the Department of Control and Computer Engineering (DAUIN). His work was recently featured in the June issue of HiPEAC Info, the magazine of the HiPEAC network (High Performance, Edge and Cloud computing) – a major European research and innovation community in advanced computing systems, involving more than 2,000 academic researchers, industry professionals, and students from across Europe.

These neural networks use electrical spikes to process information more efficiently than traditional deep learning models. Their approach shows great promise in fields that require real-time processing, low power consumption, and robustness, such as sensor systems, wearable devices, and the Internet of Things (IoT).

Spiker+ is designed for compact and embedded applications –  that is, integrated systems often with limited resources, built to perform specific functions within electronic devices. It can be used in systems that process temporal signals from analog sensors, such as microphones, photodiodes, or electrodes that capture bioelectrical signals. Spiking neural networks are especially well-suited for tasks involving temporal variability, such as audio and video signal recognition, offering a more efficient and accurate response compared to traditional models.

“If you had asked me during my undergrad whether I wanted to do a PhD, I would have said absolutely not,” says Alessio Carpegna. “And yet, life – especially meeting Professor Stefano Di Carlo –  led me to take that path. If you asked me today whether I’d do it again, I’d say yes without hesitation. It changed me, shaped me, and taught me that in life, you don’t need to be a genius – you just need to believe in an idea, commit to it, and enjoy the ride. The rest will follow.”