The assumption: Memory scales O(n) with operations.
The result: I broke it.
| Tasks | Memory |
|---|---|
| 1K | ~3GB |
| 100K | ~3GB |
| 1M | ~3GB |
| 10M | ~3GB |
| 100M | ~3GB |
100,000x scale. Same memory. Merkle-verified.
The Proof
Every task is SHA-256 hashed into a Merkle tree. The root hash commits to all 100 million operations:
e6caca3307365518d8ce5fb42dc6ec6118716c391df16bb14dc2c0fb3fc7968b
Verify Yourself
git clone https://github.com/Lexi-Co/Lexi-Proofs.git
cd Lexi-Proofs
node verify.js --all
Don't trust me. Check the math.
What It Is
An O(1) memory architecture for AI. Structured compression that preserves signal, discards noise. Semantic retrieval for recall.
This is a memory layer — not a reasoning engine. You still need an LLM on top.
Background
Solo developer. Norway. 2013 hardware (i7-4930K).
Looking for feedback, skepticism, and verification. Also open to acquisition conversations.
Repo: https://github.com/Lexi-Co/Lexi-Proofs
Website: https://lexico.no
What am I missing? Poke holes in it.