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NRIPage | Articles | Nithin Kamath Discusses India’s AI Challenges and China's Progress | Get Business News. Grow and Thrive in the Modern Market around the world - NRI Page
Overview of China’s Technological Progress and India’s Struggles
In the first paragraph, Nithin Kamath highlights the significant technological progress made by China, particularly in AI with startups like DeepSeek. Kamath draws a historical comparison between China and India’s development, noting that both countries had similar per-capita GDP in the 1960s and 70s. However, by the 1990s, China had surpassed India’s GDP, mainly due to its reforms that were focused on long-term scientific and technological growth. Kamath acknowledges the undeniable progress China has made, especially in innovation, contrasting this with India’s relatively slower pace of growth.
India’s Short-Term Focus and ‘Jugaad’ Mentality
In the second paragraph, Kamath discusses India’s challenge of short-term thinking, or the "jugaad mentality," which has hindered long-term solutions in business, politics, and regulatory frameworks. He explains that while India has made progress, it has typically been through temporary or patchwork fixes rather than addressing root causes with long-term strategies. This mentality, Kamath argues, has led to inefficiencies and setbacks in fostering innovation, particularly in emerging fields like AI, where India struggles to create an ecosystem conducive to talent and research.
The Need for Research and Innovation in AI
The third paragraph stresses the importance of research and talent in developing India’s AI capabilities. Kamath points out that acquiring resources like GPUs won’t be sufficient unless India creates an enabling environment for innovation, which includes supporting its researchers. He emphasizes that many talented researchers leave India for better opportunities abroad due to a lack of support. Kamath advocates for building a research-driven ecosystem over the next 5-10 years, drawing inspiration from China’s two-decade commitment to research and innovation. He concludes by acknowledging the importance of open-source initiatives like DeepSeek, which are pivotal in making AI progress accessible.