AI hub-node project
Artificial Intelligence, Machine Learning & Deep Learning services for data-driven sciences (Hardware resource info is found here)
Data-driven science aims at understanding complex phenomena based on huge amounts of data coming from different sources. The understanding involves several steps such as modeling, implementation, validation where particularly the modeling and implementation traditionally is mainly based on human intelligence. Recent advances in computing technology (GPUs, accelerators in general), and particularly the emergence of easy-to-use software frameworks and ready-to-use cloud services enable a shift towards automating these steps. The goals of this project are to provide a common platform and service exploiting AI / ML / DL in such scenarios by:
providing necessary HW resources in-house preinstalled with state-of-the-art software stacks targeting researchers and students
building up competence in using ready-to-use cloud services from external providers (such as Google Edu, IBM IAI, MS Azure, Amazon Web Services, etc)
building up competence in advising researchers and students in the use of AI / ML / DL methods and frameworks running on internal or external resources
By providing a common platform or using external resources we aim at lowering the costs for building and maintaining such infrastructure. By letting stakeholders from different domains - researchers, lecturers, librarians and IT service providers - work closely together we will establish a network of experts which can address support requests in an efficient and effective manner.
If you're interested in using AI-based services or want to share your experiences, please contact us at firstname.lastname@example.org.
If you're interested in receiving news about the project's progress or public events related to the service, please subscribe to the email list email@example.com.