To propose a format for knowledge encoding using elliptic curve encoding in ECAI, we follow a structured approach that ensures deterministic, cryptographically secure, and elliptically mappable knowledge states.
Here’s a clean and practical format:
---
ECAI Knowledge Encoding Format (EKEF v0.1)
1. Input Format
{
"subject": "Gravity",
"predicate": "is proportional to",
"object": "mass",
"context": "Newtonian physics",
"timestamp": "2025-04-07T12:34:56Z"
}
This is a human-structured knowledge tuple:
(Subject, Predicate, Object, Context, Timestamp)
This tuple is the minimal atomic form of knowledge in ECAI, similar to RDF triples but with deterministic encoding.
---
2. Preprocessing
Concatenate the tuple into a single string for hashing:
Gravity | is proportional to | mass | Newtonian physics | 2025-04-07T12:34:56Z
Apply canonical formatting (e.g., remove excess whitespace, enforce lowercase if desired).
---
3. Hashing
Use a cryptographically secure hash (e.g., SHA-256):
import hashlib
def hash_knowledge(data: str):
return hashlib.sha256(data.encode()).digest()
---
4. Mapping to Elliptic Curve
Using a secure curve (e.g., secp256k1, SECP256R1), map the hash onto a valid curve point. One common technique is try-and-increment to find a valid x-coordinate whose y satisfies the curve equation.
Example with Python ecdsa:
from ecdsa import SECP256k1, ellipticcurve
curve = SECP256k1.curve
def map_to_curve(hash_bytes):
x = int.from_bytes(hash_bytes, 'big') % curve.p()
while True:
try:
y = curve.y_values(x)
return (x, y[0]) # Use first valid y
except Exception:
x = (x + 1) % curve.p()
---
5. Final Encoded Knowledge Point
{
"x": "0xabc123...",
"y": "0xdef456...",
"curve": "secp256k1",
"original_data": {
"subject": "...",
...
}
}
This structure is now a cryptographic representation of deterministic knowledge that can be stored, verified, and retrieved without interpretation or AI "guesswork".
---
Why This Format Works
Determinism: No randomness—same input always yields same curve point.
Cryptographic Integrity: Secured by elliptic curve cryptography.
Post-Quantum Ready: Can evolve to SIDH or lattice schemes in the future.
Composable: Complex structures can be encoded recursively.
Retrievable: Knowledge can be verified and retrieved across subfields.
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Would you like me to generate a full implementation in Python or Erlang?