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HOW ACCELERATED COMPUTING IS POWERING AI INNOVATION
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NVIDIA’s accelerated computing platform empowers businesses to harness AI, reduce costs, boost energy efficiency and drive growth.
Business technology leaders face relentless pressure to turn technological potential into real-world value. The rise of machine learning (ML) and generative Artificial Intelligence (AI) has only heightened these demands, with groundbreaking applications reshaping industries seemingly overnight.
From automating complex processes to transforming customer experiences, AI has shifted from being a niche innovation to a strategic imperative. Yet, its transformative power comes with a catch: AI needs significantly more computing power than traditional workloads.
Business leaders are now faced with new challenges: How can they harness AI to improve competitiveness and profitability while meeting its growing demands for speed, efficiency and computational power?
Enter accelerated computing.
THE BUSINESS CASE FOR ACCELERATED COMPUTING
Unlike traditional computing — which relies on central processing units (CPUs) to handle data sequentially — NVIDIA’s accelerated computing architecture pairs graphics processing units (GPUs) with CPUs, allowing them to operate concurrently and independently. This approach dramatically accelerates performance and energy efficiency.
For example, tasks that once took 100 units of time can now be completed in just one, slashing time, energy and operational costs. This breakthrough positions accelerated computing as an essential investment for businesses driving generative AI, industrial digitalisation and data-driven innovation.
UNLOCKING THE POTENTIAL OF AI WITH NVIDIA
NVIDIA offers an integrated stack of hardware and software solutions designed to help businesses across industries solve complex challenges. The following case studies illustrate the transformative impact of these tools.
1. NVIDIA GPUs: The cornerstone of NVIDIA’s accelerated computing platform.
Real-world use: FPT Smart Cloud, a member of FPT Corporation, an NVIDIA cloud partner and AI provider in Vietnam, leveraged NVIDIA H100 Tensor Core GPUs and NVIDIA HGX H200 in their AI Factories to develop multi-lingual AI agents for tasks such as customer service and employee training. Long Chau, a major pharmaceutical chain in Vietnam, used the employee AI agent and saw a 55 per cent improvement in pharmacist knowledge quality while cutting training resources by 30 per cent.
2. NVIDIA AI: A suite of AI services including pre-trained models, training scripts, software development kits and frameworks to speed up AI workflows, improve accuracy, efficiency and performance while reducing cost.
Real-world use: American Express leveraged fraud detection algorithms to monitor all customer transactions globally in real time, detecting fraud in just milliseconds. Using a combination of advanced algorithms — one of which tapped into the NVIDIA AI platform — American Express enhanced model accuracy, advancing the company’s ability to better fight fraud and improving security for cardholders.
3. NVIDIA Metropolis: An AI-powered video analytics platform for smart city applications. It processes video and sensor data in real time to improve safety, efficiency and decision-making in areas like traffic management, public safety and building automation.
Real-world use: Vietnam Posts and Telecommunications Group (VNPT) used NVIDIA Metropolis to build a system for monitoring and analysing traffic patterns in Tan An City, Long An Province. This initiative, combined with VNPT’s AI models, achieved an 80 per cent reduction in traffic violations within two months of implementation. Over a 10-month period, it detected 2,400 traffic violations and supported local authorities in tracing and investigating security offenders, reinforcing public safety.
SUSTAINABLE COMPUTING AND COST EFFICIENCY
With increased computational power often comes higher energy consumption. However, accelerated computing offers a solution to reduce energy consumption. As businesses face rising energy costs and mounting pressure to meet environmental, social and governance (ESG) goals, energy-efficient computing is becoming more important.
If data centres worldwide switched from CPU-only to GPU-accelerated systems for high-performance computing and AI workloads, they could save more than 40 terawatt-hours of energy each year – enough to power nearly five million homes in the United States annually. These advancements drive progress in fields like scientific computing, healthcare and climate technology while supporting businesses in meeting their sustainability targets.
PREPARING FOR FUTURE WORKLOADS
Looking ahead, AI-driven workloads will define the future of business. Whether it’s generative AI, autonomous systems or digital twins, the computational demands of these applications are growing rapidly. Companies that invest in accelerated computing now will be well-positioned to leverage it as these applications become mainstream.
Driven by NVIDIA’s innovative GPUs, specialised hardware, advanced software and parallel computing techniques, accelerated computing empowers businesses to unlock the full potential of AI, foster innovation and meet long-term ESG goals. For C-suite executives, investing in accelerated computing is not just about immediate gains — it’s a strategic decision that prepares their business for the challenges and opportunities of the future.
