Infosys Develops Software to Reduce AI's GPU Dependence

AI Without GPUs? Infosys Has a Solution

As AI adoption surges worldwide, so does the demand for powerful GPUs. However, software giant Infosys is working on an innovative software layer that reduces dependence on GPUs for AI workloads. This move comes at a time when the supply of high-performance chips struggles to meet growing demand, leading to increased costs and deployment delays.

"Not every workload needs a GPU. We are working on a software layer that ensures AI models can run efficiently on commodity hardware, reducing the need for expensive and scarce GPUs," said Satish HC, EVP & Chief Delivery Officer, Infosys, at the NASSCOM Technology and Leadership Forum 2025 (NTLF) in Mumbai on February 25.

The Growing Concern of GPU Dependency

The demand for AI-driven applications has skyrocketed, putting immense pressure on GPU availability. Infosys' solution could provide businesses with a cost-effective and efficient way to deploy AI models without waiting for expensive GPUs.

Infosys’ Small Language Models (SLMs)

One of Infosys' key AI advancements is the development of Small Language Models (SLMs). Unlike large AI models that require vast amounts of data and processing power, SLMs are optimized for specific tasks and industries, making them faster and more efficient.

"We have already built four models for our business within Infosys," Satish shared. On January 16, Infosys announced that it had successfully developed these SLMs, allowing businesses to implement AI solutions with reduced computational requirements.

Wipro Joins the AI Efficiency Race

Infosys isn’t alone in its efforts to optimize AI infrastructure. Wipro, another IT giant, has committed $1 billion to AI research and development. The company is focusing on embedding AI into its operations before rolling it out for clients.

"Our Vega Studio has helped us build AI use cases across HR, legal, and manufacturing, optimizing performance," said Sanjeev Jain, COO, Wipro. This strategic approach aims to ensure seamless AI integration while maximizing efficiency.

The Global GPU Crunch

The AI boom has created an unprecedented demand for GPUs, with India heavily reliant on imports from NVIDIA, AMD, and other chip manufacturers. This dependency has led to supply chain disruptions and higher costs for enterprises looking to scale their AI capabilities.

India’s Push for Semiconductor Independence

To address this challenge, the Indian government is actively investing in domestic semiconductor production. As part of its Rs 76,000 crore semiconductor mission, India is setting up chip fabrication plants in collaboration with global tech partners. These efforts aim to build the country’s first indigenous GPU within the next three to five years.

The Future of AI Computing

With Infosys and Wipro leading the charge in AI efficiency, the future of AI computing may not be solely dependent on GPUs. The development of software-driven AI solutions, combined with India’s semiconductor ambitions, could reshape the AI landscape, making it more accessible and cost-effective for businesses worldwide.

As the industry evolves, one thing is clear—companies that innovate in AI infrastructure will be the ones shaping the future of technology.