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A new partnership between Google Cloud and the Monetary Authority of Singapore (MAS) will study how generative artificial intelligence (AI) could be leveraged by the central bank.
Singapore’s central bank has signed a new memorandum of understanding (MoU) with Google Cloud that will commit the two organisations to finding central banking use cases through generative AI.
Under the partnership, the MAS will explore opportunities to develop generative AI applications that can be deployed to improve both its internal and industry-facing digital services.
The MAS will also study the potential of AI products to improve its business functions and operations, while helping Google to develop the knowledge and skill sets of its AI technologists.
Vincent Loy, assistant managing director of technology at the MAS, said that although new approaches to central banking tasks will be explored, the partnership will prioritise AI-based information security and data governance.
“Through this, we hope to inspire greater adoption of responsible generative AI in the financial sector,” he said.
Sherie Ng, country director for Singapore at Google Cloud, said the partnership will strengthen the status of the MAS as a “leading financial hub” for technological innovation.
“Our partnership will enable MAS and spur the broader financial sector to unlock new possibilities that could benefit consumers and businesses,” she said.
What is generative AI?
The term "generative AI" refers to a broad range of machine learning systems that are able to generate new creative possibilities on demand.
The most well-known generative AI system is Chat Generative Pre-trained Transformer, the large language model better known as ChatGPT.
According to IBM Research, generative AI can refer to any system that uses the data it was trained on to generate new content, such as text, images, videos and even software code.
“The applications for this technology are growing every day, and we’re just starting to explore the possibilities,” the company said.
“At IBM Research, we’re working to help our customers use generative models to write high-quality software code faster, discover new molecules, and train trustworthy conversational chatbots grounded on enterprise data.”
IBM Research is also using generative AI to create “synthetic data” that can be used to improve the richness of the data the AI is trained on, and thereby improve its generative potential.
Analysts at McKinsey & Company, meanwhile, have said that generative AI can be used by organisations to “optimise” their business processes.
This is the use case of generative AI that the MAS will be studying, using technologies such as Google Cloud’s Vertex AI.
As noted by the MAS, the Vertex AI Model Garden offers a central register or repository of pre-trained generative AI models that can be further customised to address a variety of AI use cases.
These models can be first-party, third-party or open-source, giving the user added control and flexibility over the inputs that feed into the system’s foundational data.
Similarly, the Vertex AI Generative AI Studio is a cloud-based developer platform that enables users to build, train and deploy customised AI models, and Generative AI App Builder can then be used to transform these models into AI-powered chatbots and search applications.
As covered by VIXIO, major payment companies, such as Stripe and Klarna, are already exploring generative AI in their own workstreams.
Stripe is currently using GPT-4 to improve search functionality within its Stripe Docs product, and Klarna offers highly personalised product recommendations via an integrated plugin for ChatGPT.
