The Future of Energy-Efficient AI with Memristor Technology
Artificial intelligence is expected to require increasingly massive amounts of computing resources in the coming decades at significant financial and environmental costs. New hardware technologies are necessary to keep up with the major demand in complexity and energy efficiency of these algorithms. Brain-inspired computing is very promising, since the brain is capable of continuously learning from new data, while consuming only a small fraction of energy that would be consumed in artificial intelligence systems. The reason could be that current artificial intelligence systems have limited biomimicry, as exemplified by deep neural networks with simplistic neuronal and synaptic dynamics. Their training is usually executed in microprocessors, graphics processing units or tensor processing units based on existing digital hardware technologies with poor energy efficiency for these tasks. By comparison, emerging analog hardware technologies, like memristors, show promise for dense energy efficient systems given their ultra-scalable footprint and better energy/bit consumption. In this talk, I will describe the basics of memristors, as well as opportunities and challenges of achieving practical adoption. I will also summarize our interdisciplinary efforts across the innovation stack, from new types of complex materials and synaptic devices to new types of prototyping systems and brain-inspired algorithms.
Interdisciplinary efforts involved in advancing AI hardware
Future of AI Hardware
Energy Efficiency in AI Systems
Q&A session
Expert career advice
Job search strategies
International student support
Success stories
Located at the heart of the Washington, D.C. Metropolitan Area, the George Washington University School of Engineering and Applied Science (GW Engineering) is a beacon for transformative education, research, and innovation. Driven by a deep commitment to interdisciplinary collaboration, GW Engineering empowers students to become tomorrow's problem-solvers, equipping them to address the world's most pressing challenges. Ranked among the top engineering schools, GW Engineering boasts an impressive network, with nearly 300 leading companies such as Amazon, Cisco, Google, and The World Bank actively recruiting its graduates. With its unique location in Washington, D.C., the school leverages its proximity to government agencies, businesses, and international organizations, empowering students and faculty to make impactful contributions globally. SEAS prioritizes ethical leadership, academic excellence, and the pursuit of innovation in the service of humanity.
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