Self-Optimizing Neural Architecture - Runtime-adaptive learning for LLM routers with two-tier LoRA, EWC++, and ReasoningBank
Self-Optimizing Neural Architecture (SONA) - Runtime-adaptive learning with LoRA, EWC++, and ReasoningBank for LLM routers and AI systems. Sub-millisecond learning overhead, WASM and Node.js support.
SONA Linux x64 GNU native binding
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Self-learning LLM runtime — TurboQuant KV-cache (6-8x compression), SONA adaptive learning, FlashAttention, speculative decoding, GGUF inference
Self-Optimizing Neural Architecture (SONA) for Claude Flow — adaptive learning, trajectory tracking, pattern reuse, 7 RL algorithms (PPO/A2C/DQN/Q-Learning/SARSA/Decision Transformer/Curiosity), Flash Attention, MoE routing, LoRA, EWC++ for continual lear
Complete WASM toolkit for edge AI: vector search, graph DB, neural networks, DAG workflows, SQL/SPARQL/Cypher, and ONNX inference - all running in browser
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Self-learning vector memory for AI agents — single-file .rvf cognitive container with HNSW search, episodic Reflexion memory, causal graph + Cypher, 9 RL algorithms, Thompson Sampling bandit, 41 MCP tools, hybrid (BM25 + dense) retrieval, GNN attention. 1
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WASM bindings for RuvLLM - browser-compatible LLM inference runtime with WebGPU acceleration
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Proof-gated graph transformer with 8 verified modules — physics, biological, manifold, temporal, economic graph intelligence via NAPI-RS
Self-learning vector database for Node.js — hybrid search, Graph RAG, FlashAttention-3, HNSW, 50+ attention mechanisms
High-performance vector database with HNSW indexing - 50k+ inserts/sec, built in Rust for AI/ML similarity search and semantic search applications
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Portable WASM embedding generation with SIMD and parallel workers - run text embeddings in browsers, Cloudflare Workers, Deno, and Node.js
RuVector Format Node.js native bindings
WASM bindings for ruvector-graph-transformer: proof-gated graph attention in the browser
Graph Neural Network capabilities for Ruvector - Node.js bindings
RVF self-learning temporal solver — Thompson Sampling, PolicyKernel, ReasoningBank
RuVector Format WASM microkernel for browser and edge vector operations
High-performance WebAssembly attention mechanisms: Multi-Head, Flash, Hyperbolic, MoE, CGT Sheaf Attention with GPU acceleration for transformers and LLMs
Self-Optimizing Neural Architecture - Runtime-adaptive learning for LLM routers with two-tier LoRA, EWC++, and ReasoningBank
Unified brain-like cognitive architecture integrating all Omega components