Transforming governance with a unified AI stack
artificial intelligence (AI), organisations are scrambling to implement the technology in their business processes and service delivery frameworks to improve efficiency and enhance citizen experiences.
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AI is set to impact nearly every sector, but to harness its potential, organisations need an ‘AI-first’ strategy that includes scalable, flexible AI solutions for business transformation. This requires an integrated AI stack — comprising infrastructure, data, AI models and applications — enabling AI deployment across various use cases.
Can such an AI stack be developed as a digital public infrastructure (DPI) by the government to provide seamless, proactive services to citizens and businesses?
To create a DPI, it is essential to understand the components of an enterprise-level AI stack. The foundation of this stack is a compute infrastructure layer, which includes compute capacity, storage, networking and tools for developing, training and deploying AI models. This layer would utilise Graphics Processing Units (GPUs), Central Processing Units (CPUs) and Tensor Processing Units (TPUs) optimised for AI workloads. Cloud platforms offer scalability, while edge computing may be necessary for real-time services in remote or low-bandwidth environments.
The second layer consists of the data layer, which focuses on collecting, storing, cleaning and annotating data for use by the AI models. Data