Ask original questions.
Choose problems that reward understanding. Make room for findings that challenge the starting assumption.
INDIA / FRONTIER AI / FORMATION STAGE
Intelligence
worth
building.
An Indian frontier AI research initiative.
Exploring foundation models, compute efficiency,
and the science of safer intelligence.
FIG. 01 / THE FIELD OF INQUIRY
INQUIRY IS THE BEGINNING.
INQUIRY IS THE BEGINNING.ANVIKSHARA / AN OPEN QUESTION, PURSUED.SCROLL TO DISCOVER ↓
01 / OUR AMBITION
Built from India.
With a global horizon.
The next chapter of AI
should have
more authors.
Our ambition is to build an Indian frontier AI research company: one that develops its own scientific understanding, contributes original work, and treats safety as a research discipline.
Anvikshara is at the beginning. The immediate priority is finding a technical co-founder and shaping a focused, testable first research programme.
Formation stage. No released models, published research results or operating compute infrastructure are announced on this site.
02 / PROPOSED RESEARCH AGENDAThree questions.
Three questions.
One long horizon.
These are areas we intend to investigate.
They describe our direction, not completed results.
01What should intelligence
be able to understand?FOUNDATION MODELS
Investigate how foundation models learn, reason and generalize. Begin with a bounded question, a reproducible evaluation, and a clear account of what the evidence supports.
Learning · Reasoning · Evaluation02How far can each
unit of compute go?COMPUTE EFFICIENCY
Explore the relationship between capability and the resources it requires. Study efficient training and inference, with measured trade-offs and reproducible comparisons.
Training · Inference · Measurement03How do we know
when to trust it?AI SAFETY
Study model behaviour, limitations and failure modes. Make evaluation and safety part of the research process from its first experiment.
Behaviour · Robustness · Limits03 / RESEARCH PRINCIPLES
A standard for the work
we intend to do.
Let evidence lead.
Distinguish an ambition from a result. Make methods, comparisons and limitations legible.
Make resources count.
Start with a tractable experiment. Learn what matters before committing to scale.
Build with responsibility.
Consider the consequences of capability alongside capability itself.
04 / THE FOUNDING CHAPTERA research company
A research company
begins with
the right people.
Seeking a technical co-founder with deep experience in machine learning research, foundation models or efficient compute, and the patience to build from first principles.
Meet the founder