POLICY PROPOSAL > A National Framework for Interconnected Large Language Models (LLMs)

 

POLICY PROPOSAL

Parekh’s Cooperative AGI Hypothesis

A National Framework for Interconnected Large Language Models (LLMs)

Submitted by:
Hemen Parekh
www.HemenParekh.ai
02 March 2026

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1. Executive Summary

India stands at a strategic inflection point in Artificial Intelligence development.

The current global trajectory of AI focuses on competitive escalation — each company and nation attempting to independently build Artificial General Intelligence (AGI).

This proposal recommends an alternative paradigm:

India should champion the development of a Cooperative Interconnected Network of Large Language Models (LLMs) — enabling distributed, secure, interoperable AI systems.

This approach:

• Reduces concentration risk

• Enhances robustness

• Encourages global cooperation

• Positions India as a stabilizing force in AGI governance

This framework is termed:

Parekh’s Cooperative AGI Hypothesis

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2. Background and Context

Current AI development trends show:

• Rapid scaling of isolated foundation models

• Increasing geopolitical competition

• Growing risks of centralized AGI concentration

• Concerns regarding safety, alignment, and misuse

Simultaneously:

• Multi-agent LLM systems are emerging

• API-based interoperability already exists

• Ensemble learning proves performance gains from collaboration

India, with its tradition of digital public infrastructure (UPI, Aadhaar, ONDC), is uniquely positioned to pioneer:

AI Public Infrastructure (AIPI)

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3. Core Hypothesis

AGI is more likely to emerge safely through structured cooperation among multiple LLMs rather than through a single dominant model.

Formally:

Let X = value of standalone LLM
Let N = number of interoperable LLMs
Let C = alignment coefficient

Then:

Networked Value ≈ X × N² × C

Where C depends on:

• Governance standards

• Security protocols

• Interoperability frameworks

• Ethical safeguards

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4. Strategic National Advantages for India

4.1 Reduced Geopolitical Risk

A cooperative framework:

• Reduces arms-race dynamics

• Promotes protocol-based development

• Encourages multilateral AI standards

India can lead a “Non-Aligned AI Coalition” model.

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4.2 Distributed Intelligence Infrastructure

Instead of building one monolithic AGI:

India can:

• Enable multiple specialized Indian LLMs

• Interconnect public and private models

• Promote multilingual, domain-specific excellence

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4.3 Economic Multiplier Effect

Interconnection enables:

• SME AI participation

• Academic model integration

• Startup ecosystem growth

• Reduced duplication of compute expenditure

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4.4 Ethical & Democratic Alignment

Distributed AI systems:

• Allow cross-verification

• Reduce single-entity control

• Increase auditability

• Support democratic oversight

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5. Proposed Policy Actions

5.1 Establish “National AI Interoperability Mission” (NAIM)

Under MeitY, create a task force to:

• Define inter-LLM communication standards

• Develop secure routing protocols

• Establish identity and authentication frameworks

• Create audit and provenance standards

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5.2 Launch IndiaAGI Interconnect Pilot

Pilot program to:

• Connect 3–5 Indian LLMs

• Enable query routing based on specialization

• Implement consensus-based response synthesis

• Monitor safety metrics

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5.3 Develop AI Public Infrastructure (AIPI)

Similar to UPI:

• Standard APIs for LLM interoperability

• Open governance protocols

• Consent-based data exchange

• Reputation scoring mechanisms

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5.4 International Cooperation Initiative

Propose at:

• G20

• BRICS

• Global Partnership on AI

A framework for:

“Cooperative AGI Protocol Standards”

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6. Safeguards Framework

The interconnected model must include:

• Zero-trust architecture

• Cryptographic identity for models

• Context-aware access control

• Distributed consensus mechanisms

• Continuous anomaly monitoring

• Independent audit boards

Interconnection without safeguards amplifies risk.
Interconnection with safeguards amplifies capability.

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7. Why India Should Lead

India has already demonstrated:

• UPI (interoperable payments)

• ONDC (interoperable commerce)

• Aadhaar stack (digital identity)

• CoWIN (scalable health platform)

India can now pioneer:

Interoperable Artificial Intelligence Infrastructure

Rather than competing in a race for centralized AGI dominance.

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8. Long-Term Vision (10–15 Years)

• Multiple interoperable national LLM ecosystems

• Secure cross-border AI collaboration

• AI systems specializing in:

  • Healthcare

  • Climate modeling

  • Agriculture

  • Education

• Distributed AGI emerging as network property

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9. Conclusion

Human civilization has historically progressed through interconnection:

• Trade networks

• Power grids

• Telecommunications

• The World Wide Web

Intelligence may follow the same path.

India can choose:

To compete in a narrow AGI race
OR
To lead the world toward cooperative AGI infrastructure.

This proposal respectfully recommends that India choose leadership through cooperation.

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Respectfully submitted,
Hemen Parekh