More useful work
per unit of energy.
Explore compact models, selective computation and efficient inference. Compare energy use, task quality and response time together, rather than treating lower power alone as success.
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Green AGI
An independent vision · India
Green AGI
Research.
More capable intelligence.
A more considered footprint.
Our long-term vision is to develop energy-efficient, water-conscious AI technology in India, with environmental responsibility built into the questions we ask and the systems we hope to create.
Explore the mission01 / Purpose
Our Mission
Build towards useful AI in India while treating energy and water as design considerations from the beginning.
Green AGI Research expresses KDMS’s ambition to explore a path towards more general AI capabilities. The immediate direction is practical: understand resource use, investigate smaller and more efficient approaches, and evaluate useful capabilities step by step.
We want this work to reflect Indian contexts, including local needs, languages and access to computing. AGI is a long-term research aspiration here; this page does not announce that it has been developed or promise a date for achieving it.
02 / Where things stand
Current
Prototype Status
Prototype details not yet published
A direction to explore.
A direction to explore.
Results to establish.
This page presents the vision and proposed research goals. It does not present a validated AGI prototype, measured energy or water savings, or a production AI system.
Future prototype updates should explain what was built, the task it was tested on, the hardware and methods used, and the limitations observed. Concepts, experiments and validated results will be identified separately.
Current public material: research vision and goals. Prototype demonstrations and benchmark results are not published here yet.
03 / Questions to investigate
Research Goals
These are proposed areas of investigation, with progress to be judged through clear, reproducible evaluation.
More useful work
Look beyond
the model.
Investigate how hosting location, electricity supply and cooling choices affect water use. Document what can be measured and where infrastructure data is unavailable.
Start with specific
problems.
Define focused tasks relevant to Indian users, including language and accessibility needs. Use small, testable prototypes to assess reliability before considering broader capabilities.
Make progress
inspectable.
Set comparison baselines, record experiment conditions and report limitations. Examine safety, data handling and failure cases alongside capability and resource use.
04 / Working principles
Environmental
Responsibility
“Green” describes the direction of the work. Environmental benefits must be demonstrated with evidence.
Measure the whole question
Consider training and everyday operation, hardware use and the surrounding infrastructure. State the boundaries of any measurement and distinguish direct observations from estimates.
Respect local water conditions
Consider where water is used and the local context, rather than relying on one headline number. Seek information about cooling and electricity-related water use when evaluating infrastructure.
Report trade-offs openly
Assess resource use alongside quality, safety and accessibility. Avoid claims such as “zero water,” “carbon neutral” or guaranteed efficiency gains without supporting evidence.
05 / Start a conversation
Contact Us
Interested in energy-efficient AI, water-aware computing or research collaboration? Share a focused question, an idea or relevant expertise.
Send a research inquiry Or email KDMSdivinemaster.official@gmail.com
Use the existing inquiry form and mention Green AGI Research in your message.