Towards Robust and Efficient AI at Scale
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore cutting-edge research on robust and efficient AI at scale in this 51-minute NHR PerfLab seminar talk by Dr. Charlotte Debus. Delve into the challenges and opportunities of large-scale AI models, focusing on time series forecasting in scientific applications. Learn about transformer architectures, scalability issues, and the balance between computational power and energy efficiency. Discover innovative approaches to address the growing energy consumption of AI, including distributed optimization techniques and hyperparameter tuning. Gain insights into real-world applications such as electric load forecasting and power generation prediction. Examine the environmental impact of AI workloads and explore strategies for developing more sustainable AI solutions. Engage with topics like uncertainty quantification, attention matrix sparsity, and community outreach in the context of advancing AI technologies for scientific research and engineering.