Mr Glen Charlton1, Long Le1, Dr Jiaxin Fan1, Dr Anastasios Papaioannou2, Andy Botting3, Meirian Lovelace-Tozer3, Ben Chiu3
1Intersect Australia, Sydney, Australia, 2University of Technology Sydney, Sydney, Australia, 3Australian Research Data Commons, Australia
Biography:
Glen is the Lead Data Scientist for the Advanced Analytics & AI (3AI) Platform at Intersect Australia. The 3AI team empowers researchers with data science and AI through hands-on support and the transfer of knowledge to improve the efficiency and increase the capability of researchers to conduct novel and practically relevant research. Glen actively promotes the novel and responsible adoption of AI for both research and operational purposes within members, partners and internally within Intersect.
Abstract:
Background
Researchers and scientists are increasingly using programming languages for data processing, visualisation, and analysis. Advancement in machine learning (ML) and artificial intelligence (AI) helps accelerate the process of analysing complex research data and conducting experiments, leading to the discovery of hidden patterns in the data. In collaboration with the Australian Research Data Commons (ARDC), the Advanced Analytics and AI (3AI) Platform at Intersect has aimed to reduce the technical barriers and provide a research-ready AI/ML infrastructure on the Nectar Research Cloud, allowing researchers to focus on their science.
Method/Actions
The modular design provides a pre-configured Python environment, DataOps, MLOps, and system monitoring tools like Apache Airflow, MLflow, Prometheus, and Grafana. Interactive software such as RStudio and JupyterLab are included. Researchers can customise their environment with specialised Python installations optimised for tasks like computer vision or generative AI.
Results
The initiative offers pre-configured, optimized environments, simplifying cloud computing for AI/ML. Researchers can quickly and efficiently begin their AI/ML journey and utilise the available resources (e.g. Nectar’s Graphical Processing Unit (GPU) Reservation System). The platform provides essential tools for data analysis, workflow orchestration, and model development within a user-friendly framework, ensuring optimal performance.
Conclusion
This collaborative effort empowers researchers to leverage AI/ML tools by providing a user-friendly, documented environment. It aims to accelerate AI/ML research on the Nectar Research Cloud, enhancing the Australian research landscape by providing accessible and powerful computational resources.