Overview
Research led by Assistant Professor Uğur Teğin of Koç University's Department of Electrical and Electronics Engineering introduced two new systems designed to utilize light for artificial intelligence (AI) computations. These systems are presented as an alternative to conventional electronic circuitry for performing computational tasks in AI. The work, detailed in two published articles, suggests approaches that could support the development of AI systems with increased speed and reduced energy consumption.
Research Context
The widespread adoption of artificial intelligence technologies has led to an increasing demand for processing power and energy. This escalating demand is described as an emerging global challenge. The research aims to address this challenge by exploring alternative computational methods for AI.
Approach
Assistant Professor Uğur Teğin developed two distinct systems. The core principle behind both systems involves offloading a portion of the computational burden onto light itself, rather than relying solely on traditional electronic circuitry. This methodology is posited as a means to execute computations pertinent to artificial intelligence applications.
Findings
The studies introduced new approaches to computing. These approaches, by using light for computations, indicated a potential for developing AI systems that are faster and more energy-efficient. The research suggests a mechanism for reducing the computational load currently handled by electronic components through the integration of light-based processing.
Why This Matters
The development of these light-based computational systems is relevant due to the growing demand for processing power and energy by AI technologies, which constitutes a global challenge. By offering approaches for faster and more energy-efficient AI, this work contributes to addressing sustainability concerns associated with AI's expansion.