As Artificial Intelligence (AI) rapidly evolves, the demand for High Performance Computing (HPC) continues to rise. One of the most transformative technologies enabling this growth is GPU as a Service (GPUaaS) — a cloud-based solution that allows users to access powerful GPU computing without building physical infrastructure.
Indonesia is now seizing this momentum. With global players like NVIDIA and local infrastructure providers such as BDx Indonesia, GPUaaS could become the backbone of the nation’s digital transformation. But the question remains — how ready are we?
In Podcast Nusantara Episode 8B, Andry Gunawan (Country Manager, NVIDIA Indonesia) and Agus Hartono Wijaya (CEO, BDx Indonesia) dive deep into the opportunities, challenges, and the future of GPUaaS in Indonesia. The discussion is moderated by Dr. Dini Fronitasari, CEO of PT. Goritma Teknologi Indonesia and AI Researcher at BRIN RI.
What Is GPU as a Service?
Simply put, GPU as a Service (GPUaaS) is a cloud-based model that provides on-demand access to high-performance GPU computing for companies, researchers, and AI creators — without the need for massive upfront investment.
Unlike traditional on-premise systems that require costly servers, cooling, and maintenance, GPUaaS offers a flexible pay-as-you-go approach. This enables users to experiment, scale, and innovate faster without financial or technical burdens.
“GPUaaS opens access to advanced technology for everyone — not just large enterprises,” said Andry Gunawan (NVIDIA Indonesia).
The On-Premise Challenge: Heavy CapEx and OpEx
During the discussion, both speakers highlighted that on-premise GPU systems require massive Capital Expenditure (CapEx) for infrastructure and significant Operational Expenditure (OpEx) for maintenance, security, and manpower.
Maintaining uptime and system reliability 24/7 is another challenge.
“Not every organization can afford to build its own AI infrastructure. GPU as a Service removes those barriers and accelerates innovation,” explained Andry Gunawan.
Comparison between On-Premise and GPU as a Service (GPUaaS) computing models. GPUaaS offers flexible costs, scalability, and faster implementation compared to traditional on-premise infrastructure.
Sources: NVIDIA Cloud GPU Solutions, AWS EC2 GPU Instances, Google Cloud GPU Guide, BDx Indonesia Podcast – Nusantara Data Center Academy (NDCA).
Data Security: The Backbone of GPUaaS
One of the biggest concerns in cloud GPU adoption is data security.
According to Agus Hartono (BDx Indonesia), BDx data centers implement eight layers of physical security — from biometric access to 24/7 surveillance.
On top of that, cybersecurity is enhanced through collaboration with national security providers like Indosat and Lintasarta, supported by AI-based anomaly detection to identify and mitigate sophisticated cyber threats.
Local Talent: A Growing but Limited Resource
Indonesia’s rapid AI development is not yet matched by the availability of certified AI and data center professionals.
To address this, NVIDIA’s Deep Learning Institute (DLI) has committed to training 20,000 Indonesian talents in AI and deep learning technologies.
However, certification costs and motivation remain challenges — highlighting the need for stronger collaboration between industry, academia, and government to expand training accessibility.
AI Sovereignty: Protecting National Data
Another key topic discussed is AI sovereignty — ensuring that data and AI models remain within Indonesia’s jurisdiction.
By keeping data local, Indonesia can avoid “digital colonization”, where valuable national data and innovations are exploited abroad.
“Keeping data within Indonesia means protecting our digital sovereignty,” emphasized Agus Hartono.
Locally hosted GPUaaS solutions guarantee that sensitive data and AI models stay under national law, aligning with Indonesia’s vision of secure and sovereign digital transformation.
Ecosystem Collaboration: The Key to AI 2045
No single entity can drive AI advancement alone. The pentahelix collaboration model — uniting government, industry, academia, communities, and media — forms the foundation for a sustainable AI ecosystem.
Within the GPUaaS context, partnerships between NVIDIA, BDx, telecom operators, universities, and research institutions are vital to driving research, innovation, and AI adoption across sectors such as finance, manufacturing, logistics, and healthcare.
Real Impact: Accelerating Industrial Innovation
GPUaaS is creating real change in Indonesia’s creative and research sectors.
With easier GPU access, AI model development and multimedia rendering times can be cut from weeks to mere hours.
Examples of GPUaaS applications in Indonesia include:
- Video rendering and animation for media production
- Big data analytics for business intelligence
- AI training for robotics, automotive, and smart manufacturing
Optimism for Indonesia’s AI Future
With its young population, vast data generation, and collaborative spirit, Indonesia is well-positioned to become a leading AI hub in Southeast Asia. Supported by GPUaaS infrastructure, talent development, and strong government backing, the nation’s AI ambitions are well within reach.
“We’re optimistic that within five years, GPUaaS will become the backbone of AI development in Indonesia,” said Agus Hartono (BDx Indonesia).
Conclusion
GPU as a Service is not just a technological trend — it’s the foundation of Indonesia’s AI-driven future.
With secure infrastructure, skilled talent, and multi-sector collaboration, Indonesia is on track to achieve its Vision 2045 as a digitally sovereign and innovative nation.
Read also: Accelerating AI Infrastructure: The Role of GPU as a Service in Indonesia’s Data Center Ecosystem — explore how cloud-based GPU solutions are transforming Indonesia’s data center landscape and enabling faster AI adoption.
For more details, listen directly to the podcast on YouTube Nusantara Academy and don’t forget to register for training by contacting https://wa.me/6285176950083
