**India Aims for AI Advancement – But Is It Lagging?** Two years after the launch of ChatGPT, China's DeepSeek has significantly lowered the costs of developing generative AI applications, escalating the global competition for AI leadership. Despite its ambitious efforts, India seems to be trailing, particularly in creating foundational language models necessary for technologies like chatbots. The Indian government asserts that a domestically developed equivalent to DeepSeek is on the horizon, providing startups, universities, and researchers with advanced chips needed for development within 10 months. Recent endorsements from global AI leaders like OpenAI's Sam Altman and major investments from Microsoft, totaling $3 billion for cloud and AI infrastructure, suggest confidence in India’s potential as a serious player in the AI landscape. Nvidia’s CEO also cited India’s exceptional technical talent as vital for unlocking future possibilities. With around 200 startups focused on generative AI, there is significant entrepreneurial activity. However, experts warn that without essential reforms in education, research, and government policy, India risks falling behind. China and the U. S. hold a "four to five-year head start, " having heavily invested in research, academia, and military applications of AI, while India lags in key metrics outlined in Stanford's AI Vibrancy Index. From 2010 to 2022, China and the U. S. received 60% and 20% of global AI patents, respectively, while India secured less than half a percent. In 2023, Indian AI startups attracted only a small fraction of the private investment compared to their U. S. and Chinese counterparts. India’s AI mission, backed by $1 billion, pales compared to the U. S.

$500 billion Stargate initiative or China's $137 billion aim to become an AI hub by 2030. While DeepSeek's ability to utilize older, cheaper chips is encouraging, the lack of "patient" capital for long-term AI developments remains a significant hurdle. Moreover, India's diversity presents challenges in building quality datasets for training AI models in regional languages. Despite these challenges, India contributes 15% of the world's AI workforce. However, many talented professionals are leaving the country, often due to the lack of robust R&D environments needed for foundational AI innovations. Experts suggest fostering collaboration among government, industry, and academia, similar to the success of India's Unified Payment Interface (UPI), which revolutionized digital transactions through a strong partnership model. Bengaluru's $200 billion outsourcing sector, which houses millions of coders, has not transitioned effectively toward developing foundational AI consumer technologies, inadvertently leaving this gap to startups to fill. Concerns remain about whether these entities can achieve rapid progress, with some experts predicting it may take years for India to match DeepSeek's capabilities. Nevertheless, India has the potential to improve and adapt existing open-source platforms to advance its AI landscape. In the long run, developing its foundational AI models will be essential for achieving strategic independence and addressing dependencies on imports. Enhancing computational power and hardware infrastructure, including semiconductor manufacturing, is crucial to bridge the gap with the giants of the U. S. and China.