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Reference implementation of "An Algorithm for Routing Vectors in Sequences" (Heinsen, 2022) and "An Algorithm for Routing Capsules in All Domains" (Heinsen, 2019), for composing deep neural networks.
Holistic system for storage and transformation of information based on associative model of data. Целостная система для хранения и обработки информации, основанная на ассоциативной модели данных.
A TypeScript-based MCP server implementing a memory system inspired by neurodivergent cognitive styles. It organizes thoughts into five districts (knowledge domains), ranks search results using BM25 semantic ranking, and stores memories as a persistent knowledge graph with bidirectional connections.
Memory system for LLMs that remembers everything you teach it during conversation. No reindexing, no context window limits. CPU by default, GPU optional.
Synapse Context Engine (SCE) is a brain-inspired hypergraph-based AI memory architecture for persistent context, coherent reasoning, and long-term memory, designed for transparency and safety.
Experimental self-growing local AI brain in Rust — learns facts into neural weights, never forgets, runs on your laptop CPU. No cloud. No GPU. No ML framework.
High-performance Holographic Memory System (HMS) for Node.js, powered by Rust. This library implements Vector Symbolic Architectures (VSA) using Binary Spatter Code (BSC) to enable semantic search, analogical reasoning, and associative memory at scale.
AI agent memory using Modern Hopfield Networks — no LLM calls, no database, one matrix multiply. MCP server for Cursor, Claude Code, and other AI coding agents.