Learning from DeepSeek, honing India's AI strategy
Extract
from the article:
The opening months of 2025 have indeed been momentous in the field of
Artificial Intelligence, with India at a crucial juncture in its AI journey.
The article outlines the imperative for India to build foundational
pillars—robust frameworks, indigenous capabilities, and strategic policies—to
propel true innovation rather than merely adopting or adapting foreign
technologies. A significant announcement highlighted is the government’s plan
to develop a Large Language Model (LLM) domestically within the coming months.
This move signifies India’s intent to not only participate in but also lead AI
development, creating tailored models that serve local needs and contexts.
Furthermore, the article delves into the broader AI
ecosystem in India, underscoring the importance of synchronized efforts among
academia, industry, and government. Emphasizing the role of data governance,
ethical frameworks, and collaborative research, it advocates for a carefully
curated AI strategy that balances ambition with responsible deployment. The
narrative also stresses learning from global exemplars while tailoring
strategies to India’s unique demography and linguistic diversity. In essence,
the article is a call to action for a more cohesive, innovation-driven approach
to AI that leverages India’s strengths in talent and technology.
My
Take:
A. RE:
PIAI - Regulating Artificial Intelligence
The fulcrum of this blog was about establishing an auditing and regulatory
framework for AI, something that seemed futuristic then but has now become
practically indispensable. "I had emphasized the need for a UN agency
devoted to AI, outlining how international coordination combined with national
regulatory oversight would be the cornerstone for safe, ethical AI
deployment." This insight resonates deeply with India's current push for
indigenous LLM development—without robust regulation and audit trails, even the
most advanced AI technologies can falter or be misused. Reflecting on this, I
see a continuity in the thought process: visionary frameworks must precede or
at least accompany technological leaps. India’s current AI strategy needs to
integrate these regulatory principles to ensure technological sovereignty
coupled with ethical responsibility.
Moreover, the mention of “Parekh’s Law of Chatbots” in my
earlier work, which illuminates how interaction paradigms must evolve with AI
maturity, aligns perfectly with the challenge India faces now. Building an LLM
domestically isn’t simply about algorithms; it’s about creating AI that
genuinely understands India’s linguistic and cultural nuances. The foresight
from those blogs about licensing regimes analogous to those for vaccines or
medicines also underscores the urgency for India to implement standards that
prevent misuse and safeguard public interest as the technology scales.
B. Priorities
for AI - Artificial Intelligence Portal
Back in 2020, I applauded the launch of India’s National Artificial
Intelligence Portal as a seminal step towards creating a unified hub for AI
resources, research, and policy. "The vision was for India to harness its
vast talent pool and data assets by sharing knowledge, fostering innovation,
and enabling collaborations across government, industry, and academia."
This foundation is now bearing fruit, as reflected in the article’s emphasis on
building the key building blocks for AI innovation. The portal’s role in
disseminating AI knowledge and enabling new job roles was not merely
administrative but catalytic, sparking deeper engagement nationwide.
Understanding that AI is set to dominate life globally, I
had remarked on the urgent need for India to not only participate but lead with
its own strategies and technologies. The current government initiative to
engineer a homegrown LLM perfectly exemplifies this progression from aspiration
to actualization. What started as a digital knowledge-sharing platform has
evolved into a springboard for strategic national projects. For me, this
trajectory validates the early priorities articulated—India’s AI ecosystem has
matured with deliberate focus on infrastructure, education, and research.
C. Shri
Meghwalji - Who Killed 288 in Train
In this blog, while the primary narrative centered on governance and policy
reform, there were keen insights about the rapid generational shifts in AI
technology. "Two generations of AI barely last two years," I noted,
underscoring the breakneck speed of change and the imperative to adopt agile
policies. The article reinforces this sense of urgency: India must rapidly
build its AI capacities to keep pace globally rather than remain a follower. My
reflections on integrating LLMs to enhance government services presaged the
current strategic plans to develop country-specific linguistic models.
Additionally, the idea of AI analyzing socio-economic data
to improve governance anticipates the practical implications of AI beyond
technical innovation. It is not only about building powerful language models
but also about embedding these tools in ways that amplify service delivery and
policy responsiveness. The article’s mention of ethics, data governance, and
collaboration resonates with the point I made—that innovation must be
harmonized with social utility and accountability.
Call to
Action:
To the Hon’ble Ministry of Electronics and IT and policymakers shaping India’s
AI trajectory: It is imperative to complement the technological development of
indigenous LLMs with transparent regulatory frameworks and ethical safeguards.
Create a national AI oversight body that includes technologists, ethicists, and
civil society representatives to guide development and deployment.
Additionally, invest in expanding the AI skill ecosystem aggressively through
the National AI Portal and partner with academia to foster cross-disciplinary
AI research. Harness this pivotal moment not merely to catch up but to leapfrog
into a future where India sets global standards in ethical, innovative AI.
With regards,
Hemen Parekh
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