Let's take a moonshot at AI

economictimes.indiatimes.com:

AI to boost productivity is vast, whether it's automating customer service interactions or accelerating drug discovery. A McKinsey report, The Economic Potential of Generative AI: The Next Productivity Frontier reveals that 63 generative AI use cases could add the equivalent of $4.4 trillion in value to the global economy, and 75% of the value would arise from the four areas: customer operations, marketing and sales, software engineering and R&D. However, the emergence of foundational models could lead to capital concentration, potentially amplifying inequalities.

This accentuates the need for careful and inclusive utilisation of AI. AI research and development has witnessed two approaches. Building large foundational models, imbued with impressive, spontaneous emergent properties, creating more contextually relevant AI tools capable of a broad spectrum of tasks.

Fine-tuning open-source foundational models for domain-specific tasks, allowing for customisable, targeted AI solutions. These fine-tuned foundational models can cater to specialised needs, generating accurate, context-specific content. Considering the benefits of both these approaches, India should focus on both large and smaller domain-specific foundational models.

Much like space tech investment resulting in capacity building, innovation and ecosystem growth, a large foundational model with emergent properties can propel India as a global AI leader, stimulating the growth of novel technologies and capacities. Moreover, AI's capabilities in identifying patterns and anomalies in network traffic and conducting intelligence analysis, surveillance and predictive analytics should be leveraged to enhance national security and reinvent cybersecurity strategies. Most