Riding the Wave of Green Change: Advancing Wave-Based Reservoir Computing for Sustainable AI
Speaker: Dr Giulia Marcucci
Wave-based reservoir computing stands as a promising analog computing paradigm, offering the potential for efficient and sustainable AI hardware. Diverse systems, spanning hydrodynamic, random, nonlinear, and multimodal, have demonstrated reliable physical computing capabilities, each exhibiting distinct input-output characteristics within complex operational domains. However, the challenge lies in refining the complexities of nonlinearity and randomness, which currently rely on chance rather than a robust foundational framework.
During this presentation, I will delve into the recent strides in photonic reservoir computing and elucidate the trajectory that led me to explore the complexities of wave propagation, aiming to comprehend its pivotal role in facilitating learning. My objective is to convey three key takeaways: first, the critical need to forge a connection between technological progress and ecological responsibility in today's landscape; second, the specific strides I have taken in this pursuit; and third, the strategies I have employed in understanding/measuring, optimising, and controlling wave-based reservoir computing systems, all in service of a smarter and greener world.
Dr. Marcucci is a dynamic and versatile professional with a solid foundation in Mathematics and Physics from Sapienza University of Rome. As a Research Associate at the University of Glasgow's Extreme Light Group, led by Prof. Faccio, she holds a world-class track record in optical hardware AI. Since August 2023, she is also the Co-Founder of an AI-focused startup committed to pioneering innovative solutions for reshaping paediatric neurology. Fuelled by a strong passion for interdisciplinary exploration, Dr. Marcucci expertly bridges academic and industry domains. Her research centres around analog, physical, and neuromorphic computing, with a unique focus on harnessing the nonlinear waves’ complexity AI applications.
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