Foundation Models for Geoscience Webinar
IMPACT team member Sujit Roy is partnering with Johannes Schmude from IBM to present an IEEE GRSS webinar titled “Towards Digital Twin: Introduction to Foundation Models for Geoscience” on April 23, 2024.
Foundation models (FMs) are pre-trained neural networks that serve as the architecture for a range of computer vision tasks, including object classification, detection, and segmentation. To building a ‘foundation’, these models are constructed by training on large and diverse datasets. This training process enables them to capture a wide array of visual features applicable across multiple domains, making them incredibly versatile.
The significant advantage of foundation models lies in their ability to perform specific tasks without requiring the extensive dataset typically necessary for training a model from scratch. By leveraging the deep learning neural networks’ advanced representational learning capabilities, foundation models can generalize effectively across different tasks. This approach not only enhances the efficiency of deploying deep learning models but also makes the power of deep learning more accessible for a variety of applications.
In this webinar, we will cover two FM designs, where we learn about dynamics, and large spatial and temporal scales. These models can help in understanding earth processes and advancement towards Digital Twin. You can register for the webinar here.
