“With The Infrastructure In Place, It Is Now Up To Students,… Full Time

Deepanshu Chauhan, Group CEO, Delta IT Network

Q. What was the vision and inspiration behind setting up the AI Learning Lab with Galgotias University?

• You see, the idea stemmed from the need to bridge the gap between theoretical knowledge and real-world AI applications. With over 25 years in the tech industry, Delta IT Network recognises how vital AI has become across sectors. In collaboration with Galgotias University, we aim to equip students with practical, hands-on experience in artificial intelligence (AI). Discussions with Mr D. Galgotia focused on addressing the lack of infrastructure in most institutions, where AI is taught in theory but lacks the systems needed for real-world practice.

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• How does the infrastructure of this new AI Lab differ from a regular IT lab, and what has been deployed to support advanced learning?
• Unlike conventional IT labs that rely mainly on central-processing units (CPUs) and basic graphics processing units (GPUs), this AI Lab features purpose-built infrastructure optimised for AI-first learning. At its core are powerful AI-grade components such as neural processing units (NPUs) capable of delivering up to 30 TOPS, ideal for real-time edge AI workloads.

The lab also includes advanced NVIDIA GPU servers and 60 AI-ready workstations connected via a virtual desktop infrastructure (VDI) or hyper-converged infrastructure (HCI). This setup allows 60 students to access full computing power simultaneously from any terminal, ensuring consistent performance and eliminating hardware bottlenecks.

Beyond raw compute, the lab is equipped to handle edge computing, parallel processing, and high-throughput data pipelines. It includes scalable memory, optimised power delivery, and comes preloaded with essential AI frameworks and simulation environments to support real-world applications in areas such as computer vision, language models, and robotics.

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And this is just the beginning; the broader vision is to evolve from a single lab into a fully AI-enabled campus, democratising access to cutting-edge AI tools for every student.

• What were the key hardware and performance considerations in designing the lab?
• Each endpoint is a high-performance, AI-ready workstation valued at ₹250,000. Backing them are three NVIDIA-powered servers with 24GB GPUs, totalling over ₹840 million. The setup enables scalable parallel computing, designed to grow with future demand and function like a mini supercomputer for student projects.
• How did industry collaborations play a role in shaping the lab’s infrastructure?
• Once the vision was defined, Intel joined through their Intel Unnati programme, focused on advancing AI education. HP also came on board as the hardware partner, contributing to an investment of around ₹200 million in high-performance, AI-ready infrastructure at Galgotias over the past two years. These collaborations ensured the lab was fully equipped for practical, advanced AI learning, not just theoretical instruction.
• How are students going to engage with this infrastructure on a practical level?

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