The next in the series featuring conversations with entrepreneurs, technologists and researchers about emerging technologies and what students need to know about these fields.

What do you do?

I am the co-founder and CEO of Ziroh Labs. We work at the convergence of advanced mathematical concepts and sophisticated distributed-system algorithms to efficiently execute open-source foundational models on Central Processing Units (CPUs). Through research and development, we hope to bring down the barrier of access to AI technology and make it available to a broader range of individuals, businesses, and organisations.

Why is your work important globally?

Today, access to AI infrastructure is skewed. Most advanced AI systems rely on Graphics Processing Units (GPUs), which are expensive and not readily accessible. This creates a divide that only well-funded organisations can fully overcome. Our product, Kompact AI, enables AI to run on CPUs that are already widely available and cost-effective. If AI is to be truly democratised, it must run on infrastructure that is accessible across geographies. By reducing cost barriers and enabling scalable deployment, we aim to make AI more inclusive and globally available.

What is exciting about your work?

The problems we are solving are deeply scientific and require both fundamental research and precise engineering. The journey involves constant experimentation, failure, and iteration. I also see technology as a form of art. A well-engineered solution, in many ways, is no different from a good poem or a good play. The combination of discovery, creativity, and real-world impact makes this work deeply engaging.

Any experiences in college that led you to become an entrepreneur?

Cotton College in Guwahati and later IISc-Bengaluru played an important role in shaping my thinking. Cotton College exposed me to a culture of ideas and intellectual responsibility, while IISc taught me to approach problems scientifically and accept failure as part of the process.

What should students specifically know about your field?

Solving meaningful and crucial problems demands deep scientific inquiry and comes with setbacks and a few hard-earned wins. Failure is acceptable and learning to wait is essential. Technology transcends geographies and cannot be confined to a single region. Students should think globally while remaining grounded in strong fundamentals, honesty, and sincere work. In the context of AI and computing, this means building a strong foundation in algorithms, data structures, and system design, while also understanding how models learn from data. Equally important is developing the ability to critically evaluate outputs, ensuring reliability, efficiency, and responsible use of AI systems.

The writer is an avid follower of emerging technologies and their applications.