Navigating the Open v. Closed Source AI Debate with Kailash Nadh

Interpreting India

The episode opens with an in-depth discussion about the value of open source as a model of development and how the definitional contours of open-source AI differ from those of traditional open-source software. The discussion also explores the characteristics and challenges that distinguish open-source AI models from conventional software development approaches.

The discussion goes on to address recent strategic shifts in the AI industry towards more open development, sparked by developments like DeepSeek's open-source R1 model and leaked internal assessments suggesting that open-source communities may be outpacing tech giants.

The discussion also explores the complex trade-offs between open and closed AI development. While open-source models offer transparency, democratization, and innovation benefits, they also present cybersecurity vulnerabilities and potential national security risks. Nadh addresses concerns about jailbreaking vulnerabilities in open models, using DeepSeek's recent security lapses as an example, while also examining the limitations and risks of closed proprietary systems.

Nadh also provides his perspective on India-specific considerations, including the government's IndiaAI Mission and the decision to develop a homegrown large language model, and discuss the strategic implications of India's approach, which is not expected to be open-source at first, and the potential for India to make meaningful progress in driving open-source AI development as a matter of policy.
Episode Contributors
Kailash Nadh is the chief technology officer of Zerodha, India’s leading stock brokerage platform, where he has led its technology and product stack development since 2013. He is also the co-founder and director of FOSS United, a non-profit foundation based in Bangalore, that aims to provide grassroot support to free and open-source software projects and communities in India. In addition to being a full-stack software developer with more than two decades of technical experience, Nath holds a PhD in artificial intelligence and computational linguistics. His most recent writings also provide a compelling analysis of open-source software developments and AI breakthroughs, including in the Indian context.
Shruti Mittal is a research analyst at Carnegie India. Her current research interests include artificial intelligence, semiconductors, compute, and data governance. She is also interested in studying the potential socio-economic value that open development and diffusion of technologies can create in the Global South.

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