India poised to become global leader in digital AI economy: VMware CEO
Says India's Digital Public Infrastructure (DPI) has the potential to revolutionize the way governments and businesses deliver services to citizens
The global recognition of India’s DPI - like the unified payments interface (UPI) and Aadhaar - has demolished the old normals. The G20 leaders recently committed to adopt, build and maintain Global Digital Public Infrastructure and also agreed to foster a wholesome and safe digital ecosystem, and a resilient global digital economy
As artificial intelligence (AI)-propelled use cases emerge across industries, India which is playing a leading role in helping other countries improve efficiency, reduce costs, increase financial inclusion and create new opportunities, has the true potential to emerge as global leader in digital AI economy, says Raghu Raghuram, Indian-origin CEO of enterprise cloud services major VMware. Raghuram said that VMware is committed to supporting India in achieving its digital transformation goals.
“In fact, VMware works closely with the government, BFSI, IT/ITES and other segments. The scale and versatility of the customers we interact with help us to learn and then to build those key learnings into our product strategy,” he noted.
Since joining VMware in 2003, Raghuram has helped steer the company's strategic direction and its technology evolution throughout VMware's rich history. He is fascinated by India's Digital Public Infrastructure (DPI) that has the potential to revolutionise the way that governments and businesses deliver services to citizens.
“India's DPI is open, interoperable, and inclusive, which makes it attractive to countries around the world and creates the potential to play a significant role at a global level. In addition to the above, India is also working to promote its DPI solutions at a global level,” Raghuram emphasised.
For example, the Global Digital Public Infrastructure Repository (GDPIR), provides a virtual repository of DPI solutions that can be used by other countries and international organisations such as the World Bank.
The global recognition of India’s DPI - like the unified payments interface (UPI) and Aadhaar - has demolished the old normals. The G20 leaders recently committed to adopt, build and maintain Global Digital Public Infrastructure and also agreed to foster a wholesome and safe digital ecosystem, and a resilient global digital economy.
According to Raghuram, many of India's largest banks, both public sector and private, run their UPI workloads on VMware infrastructure. UPI is a challenging use case as the number of transactions per month crossed 10 billion in August as well as in September, growing over 50 per cent over last year.
“At the individual bank level, the workload can be tough to predict with spikes driven by market events, like festivals or e-commerce sales. Banks rely on VMware's robust and scalable infrastructure to ensure that their customers have a consistent, high-quality experience,” the top VMware executive said.
On the growing buzz around AI, he said that Private AI is VMware’s architectural approach to generative AI. VMware Private AI unlocks the business gains from generative AI with the practical privacy and compliance needs of an organisation by prioritising data gravity, data privacy and control, and access control and auditability.
“Private AI is about the platform and infrastructure architecture built in support of generative AI, which can be deployed in public clouds, virtual private clouds, data centres, and at the edge,” he informed.
Private clouds can be architected to satisfy the requirements of Private AI but are not a requirement. The importance lies in ensuring that the privacy and control requirements are satisfied, regardless of where AI models and data are deployed. Raghuram said that with a focus on enterprise use cases, VMware Private AI can help boost an enterprise’s productivity through improved performance, faster time-to-value, and increased efficiency.
“The performance of our Private AI offerings is equal to, and even exceeds, bare metal in some machine learning inference use cases as proven in recent industry benchmarks,” he noted. Additionally, he said, because AI environments need to be elastic and highly responsive to users, the offering enables available resources to be provisioned within seconds, thus speeding up time-to-value.
