AI & ML interests

At THOX.ai, we build local-first, privacy-first AI that runs where users need it most: on edge devices, workstations, portable hardware, and embedded systems. Our research and engineering focus on making advanced AI practical without requiring cloud infrastructure or sacrificing user ownership of data. Areas of Interest * Edge AI and on-device inference * Local-first LLM deployment * Small Language Models (SLMs) * Efficient transformer architectures * Quantization and model optimization * GGUF, LiteRT, and embedded AI runtimes * AI acceleration on consumer hardware * Mobile and embedded AI systems * Privacy-preserving AI * Offline AI assistants * Agentic AI systems * Multi-agent orchestration * AI operating systems * Retrieval-Augmented Generation (RAG) * Semantic search and knowledge graphs * Memory architectures for AI agents * AI developer tools * AI infrastructure * Open-source AI * Human-AI collaboration * AI for healthcare * AI for education * AI for accessibility * AI for legal and enterprise workflows * Robotics and autonomous systems * Digital humans * Computer vision * Speech and multimodal AI * Federated and distributed AI * Edge-to-edge AI networking * Secure AI deployment * Model benchmarking and evaluation * AI hardware integration * Quantum-inspired optimization * Responsible AI engineering Technologies We Explore * Gemma * LiteRT * llama.cpp * GGUF * ONNX Runtime * TensorFlow Lite * PyTorch * Hugging Face Transformers * Rust * C++ * Python * WebGPU * CUDA * Vulkan * Jetson * Raspberry Pi * Embedded Linux Our Mission THOX.ai develops open, modular AI technologies that help developers, researchers, businesses, and makers deploy powerful AI locally. We believe users should have meaningful control over their models, data, and computing resources while benefiting from modern AI capabilities across desktop, mobile, embedded, and edge environments.

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