Question 1

How is shodh-memory different from a vector database?

Accepted Answer

Vector databases give you similarity search. Shodh-memory gives you cognition — memories strengthen when accessed together (Hebbian learning), decay naturally over time (power-law forgetting), and form associative networks via a knowledge graph. It's the difference between storage and memory.

Question 2

Does shodh-memory require an internet connection?

Accepted Answer

No. Shodh-memory runs 100% offline. Embeddings, vector index, knowledge graph — everything runs locally in a single ~30MB binary. Perfect for edge devices, air-gapped systems, or anywhere you need data privacy.

Question 3

Can shodh-memory run on a Raspberry Pi?

Accepted Answer

Yes. Shodh-memory is designed for edge deployment. It runs on Raspberry Pi Zero, Jetson Nano, industrial PCs, and other resource-constrained devices. Graph lookups are under 1 microsecond.

Question 4

What is Hebbian learning in AI agent memory?

Accepted Answer

Hebbian learning is a neuroscience principle: neurons that fire together wire together. In shodh-memory, when memories are accessed together, their connection strengthens. When memories compete, interference effects occur. This is how biological brains work, applied to AI agent memory.

Question 5

What languages and frameworks does shodh-memory support?

Accepted Answer

The core is Rust. We provide: an MCP server (for Claude, Cursor, and other AI agents), Python bindings (via PyO3/maturin), and a REST API. The Rust crate can be embedded directly in your application.

Contact

Other ways to reach us

Email

Schedule a Call

GitHub Issues

Discord