Engram Commitments: A Commitment Scheme for AI Identity

We’ve just released Engram Commitments on Zenodo — a substrate‑rooted identity primitive for AI models, built with the same mindset that underlies commitments, attestations, and ZK‑verifiable structure in cryptography. (Here, the term engram is used in our broader substrate‑rooted sense: an execution‑derived identity object defined within a formal ontology, not a behavioral fingerprint or neuroscientific metaphor.)

Engram Commitments define a substrate‑rooted identity primitive for AI models, constructed from engrams, similarity‑preserving hashing, and a binding‑and‑hiding commitment with a zero‑knowledge proof of correct derivation. The goal is simple: make model identity verifiable, tamper‑evident, and falsifiable.

This is a primitive, not a protocol. It is intentionally minimal and published early so its lineage is clear. If your work touches commitments, attestations, ZK proofs, or identity as a formal object, this may be of interest. The first meaningful applications of engrams will likely emerge from cryptography, where definitions and verification matter most.


This work comes from a different corner of the research landscape, but the crypto community’s way of thinking — definitions first, primitives before systems, lineage before hype — has always resonated with us.  
So it felt natural to make the lineage visible early and anchor the concept in a timestamped, citable artifact.

Engram Commitments propose a way to bind a model to its execution‑realized identity using engrams, similarity‑preserving hashing, and binding‑and‑hiding commitments, with ZK proofs for verifiable derivation.  
It’s a conceptual primitive, not a finished system — adversarial models and falsification frameworks are still open work.

If you’re part of the cryptography or provenance community and this intersects with your interests, we’d love for you to take a look.  
Your field has a long tradition of shaping how identity, trust, and verification evolve — and we think AI needs exactly that kind of clarity right now.


Addendum: Notes for the Cryptography Community

Engram Commitments were designed with a simple intuition: AI identity should be treated the way cryptography treats trust — as a primitive, not an afterthought.

A few clarifications for readers coming from commitments, attestations, and ZK‑systems:

1. This is a primitive, not a protocol
The construction defines:

- an identity object (the engram vector),  
- a similarity‑preserving hash,  
- a binding‑and‑hiding commitment,  
- and a ZK proof of correct derivation.

It is intentionally minimal.  
We expect downstream systems — registries, provenance ledgers, derivative‑model audits — to build on top of it.

2. No security claims beyond the cryptographic substrate
We rely on standard assumptions:

- binding/hiding from Pedersen or Naor commitments,  
- soundness from Groth16 or Bulletproofs,  
- collision behavior from SimHash/LSH.

We do not claim:

- adversarial optimality,  
- universality across architectures,  
- or resistance to all identity‑manipulation attacks.

Those are open research directions.

3. Engrams are not fingerprints
They are not behavioral probes or activation statistics.  
They are execution‑rooted differentials defined within a four‑layer identity ontology.  
This makes them:

- stable under non‑destructive transformations,  
- sensitive to collapse modes,  
- and suitable for commitments.

4. Why publish early
Cryptography has a long tradition of:

- naming primitives early,  
- defining their properties,  
- and letting the community explore, refine, and challenge them.

We follow that tradition here.  
The goal is to anchor the lineage clearly and invite scrutiny from a community that values definitions and falsification over hype cycles.

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