Session: Greener Bytes: Exploring the Environmental Impact and Solutions for LLMs
In an era where technology and sustainability must coexist, large language models (LLMs) have emerged as transformative tools across various industries, from healthcare to finance, education to entertainment. This presentation delves into the multifaceted landscape of LLMs, beginning with an introduction to their capabilities and diverse applications. As we explore the innovative use cases that highlight the profound impact of LLMs, we also confront the pressing challenges they pose, particularly regarding energy consumption and carbon emissions. With the increasing deployment of LLMs, understanding their environmental footprint becomes necessary. Through this presentation, I aim to foster a deeper awareness of this issue and outline a roadmap for minimizing the environmental impact of LLMs while maximizing their potential.
Bio
I am a researcher, pursuing a PhD in Data Science from Harrisburg University of Science and Technology, PA. I am also working as Data Analytics Principal at S&P Global. I hold about 17+ years of experience. I earned my master’s in data science from UNC Charlotte (4/4 GPA). I am a member of the honor society of Phi Kappa Phi, IEEE (Senior member), ACM, IAENG, AAAI, and the StemUp mentoring network. I am actively involved in publishing, peer-reviewing, writing tech books and articles, and speaking engagements.