What does it take to build India’s first fully dedicated AI Learning Lab and reshape the future of engineering education? Delta IT Network’s Deepanshu Chauhan reveals the vision, technology, and mission behind this pioneering initiative at Galgotias University to EFY’s Akanksha Sondhi Gaur.
Q. What was the vision and inspiration behind setting up the AI Learning Lab with Galgotias University?
A. 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.
Q. How does the infrastructure of this new AI Lab differ from a regular IT lab, and what has been deployed to support advanced learning?
A. 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. 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.
Q. What were the key hardware and performance considerations in designing the lab?
A. 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.
Q. How did industry collaborations play a role in shaping the lab’s infrastructure?
A. 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.
Q. How are students going to engage with this infrastructure on a practical level?
A. Practical engagement is central to the lab’s design. Housed within Galgotias University’s advanced central library, the AI Lab operates as an open-access facility, free from rigid timetables. Students can access it multiple times a week, enabling hands-on learning at their own pace and enhancing flexibility in applying classroom concepts.
Q. In what ways will this lab enhance the overall learning experience for students?
A. We have integrated the AI lab into the B.Tech Computer Science curriculum by linking it to credit-based, Intel-certified modules. This ensures students gain not just theoretical knowledge but practical, hands-on experience with AI systems, bridging the gap in access to specialised infrastructure. As a result, graduates emerge with verified skills that enhance both their employability and technical depth.
Q. Will students have access to internships or real-world projects through this initiative?
A. Absolutely. Intel is not just supplying the technology; they are deeply involved in shaping the curriculum, training and certifying faculty, and creating a strong pipeline for student success. Through their global network, students gain access to national hackathons, scholarships, internships, and potential job placements. This hands-on, competitive exposure ensures graduates are truly industry-ready.
Q. What core AI technologies and architecture does this lab use, especially for electronics and real-time system design?
A. The lab features a hybrid AI architecture combining on-premise edge devices with AI-grade NPUs, NVIDIA GPUs, and cloud integration for scalable performance. It supports real-time data processing, edge AI workloads, and electronic design automation (EDA) simulations. The infrastructure is compatible with leading frameworks such as TensorFlow and OpenCV, enabling both hardware-oriented innovation and software development. Designed in collaboration with Intel and the university, it equips students to work on modern electronics and real-time systems using both edge and cloud AI models.
Q. Will the curriculum focus on specific AI domains such as NLP, robotics, or computer vision?
A. Yes, the curriculum is built around open-source AI tools such as Python, TensorFlow, and computer vision libraries. It follows a modular, hands-on approach, enabling students to develop expertise in areas such as NLP, robotics, and computer vision, aligned with current global industry trends.
Q. Will the lab support development on embedded systems or FPGAs?
A. Yes, the infrastructure is versatile and capable of supporting embedded system and FPGA-based development. While the current focus is on foundational AI, we anticipate that faculty and student research will soon expand into these advanced areas, depending on how they drive usage in the coming months.
Q. Is the lab integrated with interdisciplinary research or tools such as Synopsys and Cadence?
A. While there are no current tie-ups with Synopsys or Cadence, the infrastructure is future-ready and capable of supporting EDA tools and LLM development. How it is leveraged will depend on the university’s academic leadership and their evolving research priorities.
Q. How does this support Make in India, Digital India, or startup incubation?
A. The lab strongly supports the Make in India mission, with all servers and workstations supplied by HPE and HP being made in India. On the startup and incubation front, companies such as TCS, Tata Technologies, Mahindra, and Wipro are already collaborating with Galgotias, creating on-campus touchpoints for knowledge exchange and talent scouting, particularly through this lab.
Q. How does the lab fit into the university’s innovation and startup ecosystem?
A. The lab is open not just to current students but also to alumni with viable startup ideas. During the inauguration by Shri Piyush Goyal, the Minister of Commerce and Industry, the focus was on using this infrastructure to drive innovation, patents, and job creation.
Q. When do you expect results, such as innovations or research breakthroughs, from the lab?
A. The lab is just a month old, so it is early for commercial outcomes. However, faculty are already pursuing patents, particularly in electronics and printed-circuit board (PCB) design. With continued exposure, student-led innovations are expected to pick up momentum in the coming months.
Q. Who is investing in the AI Lab at Galgotias University, and how are the partners contributing and expecting returns?
A. The AI Lab is a joint effort by Delta, Galgotias University, and Intel. Galgotias is committing ₹200 million in infrastructure and deployment. Delta is providing services, technology, and manpower without upfront charges, with returns expected through profit-sharing from the investment. Intel is providing strategic technology enablement and guidance.
Q. How will Delta benefit from its investment in the AI Lab, and how will revenue and profits be generated?
A. Delta’s ROI comes from long-term strategic gains rather than immediate service fees. As the exclusive technology and transformation partner for three years, Delta gains access to recurring opportunities in AI-driven solutions for academia and industry. Revenue will be generated through student enrolments, AI training programmes, industry collaborations, and digital transformation projects, with Galgotias anticipating 20,000 new admissions. Delta also benefits from brand visibility, future clientele, and a profit share from the ₹200 million investment.
Q. As we conclude, could you share any closing insights and explain what the future holds for the AI Learning Lab project?
A. This is just the beginning. With the infrastructure in place, it is now up to students, faculty, and university leadership to unlock its full potential. We are committed to supporting that journey, as this pilot will guide our larger initiative to transform the entire university infrastructure into an AI-powered ecosystem. We envision an environment where every department, from engineering to business, can leverage AI tools seamlessly, creating not just skilled graduates but future-ready innovators.
