Statement 2: Define the reference architecture
The use of a reference architecture provides a structured framework that guides the design, development, and management of an AI system.
Agencies must:
Criterion 4: Evaluate existing reference architectures.
Make use of the Australian Government Architecture to:
- consider reusing pretrained models when applicable
- consider whether to build in-house or use off-the-shelf software or services
- ensure strategic alignment with government's digital direction
- ensure consistency and interoperability across agencies.
Agencies should:
Criterion 5: Monitor emerging reference architectures to evaluate and update the AI system.
New architectural paradigms are emerging that address complex AI applications, including:
- Large Language Model (LLM) architectures: These architectures focus on deploying and managing large-scale language models. They encompass systems, tools, and design patterns that facilitate the integration of LLMs into applications, ensuring scalability and efficiency.
- AI infrastructure architectures: Conceptualised to streamline the production of AI models, AI factories provide comprehensive guidelines for building high-performance, scalable, and secure data centres dedicated to AI development. These architectures support the end-to-end lifecycle of AI system creation, from development to deployment.
- Generative AI (GenAI) reference architecture: This architecture outlines interfaces and components for GenAI applications, enabling users to interact with AI systems effectively. It emphasises modularity and flexibility, allowing for the integration of various AI functionalities to meet diverse user needs.