Course Introduction Video
Generative AI
Generative AI is a subset of artificial intelligence that uses machine learning models to create new, original content by learning statistical patterns and relationships from large datasets during training.
The core mechanism involves learning the underlying probability distributions of the training data, enabling the model to sample from these learned distributions to generate new content that maintains the statistical properties and patterns of the original dataset.
Course Modules
AI Ethics & guidelines
Popular AI Research
Biases & AI Ethics
Syllabus
Schedule
Credits
Format
Suryansh Kumar is an Assistant Professor of Visual Computing and Computational Media at Texas A&M University. He also holds appointments in the Electrical and Computer Engineering Department and Computer Science Department at TAMU. Dr. Kumar directs the Visual and Spatial AI Lab within the College of PVFA where his group conducts research in the field of 3D computer vision, AI, and robotic automation.
Before joining Texas A&M University, Dr. Kumar worked at ETH Zürich. Disney Research honored him with the Best Algorithm Award at CVPR 2017 for his work on non-rigid 3D acquisition for marker-less motion capture, and his Ph.D. thesis was nominated for the J. G. Crawford Prize at ANU for Best Interdisciplinary Ph.D. Thesis in 2019. His current research focuses on designing next-generation visual and spatial intelligence systems.
LAAH 202