{
  "id": "ai-ml",
  "version": 1,
  "title": "AI and machine learning models, vendors, tools and jargon",
  "tags": ["ai-ml", "vendor-names", "jargon"],
  "languages": ["en", "ru"],
  "license": "CC0-1.0",
  "source": "curated by hand from AI vendor and model names, open-source ML library docs and common LLM jargon; aka spellings are real stt (whisper large-v3-turbo) mis-transcriptions of macOS say voices Samantha and Milena reading each term in a sentence, reviewed by hand",
  "terms": [
    {"id": "claude-code", "term": "Claude Code", "note": "Anthropic's coding agent CLI"},
    {"id": "claude", "term": "Claude", "note": "Anthropic's LLM family"},
    {"id": "anthropic", "term": "Anthropic", "aka": ["Enthropic"], "note": "AI company behind Claude"},
    {"id": "openai", "term": "OpenAI", "aka": ["Open'ы"], "note": "AI company behind ChatGPT"},
    {"id": "chatgpt", "term": "ChatGPT", "aka": ["Пшеткпт"], "note": "OpenAI chat assistant"},
    {"id": "ollama", "term": "Ollama", "aka": ["Alima", "Олэмо"], "note": "local LLM runner"},
    {"id": "llama-cpp", "term": "llama.cpp", "aka": ["llama cpp", "LAMA CPP", "LEMO CPP"], "note": "C++ LLM inference engine"},
    {"id": "qwen", "term": "Qwen", "aka": ["Квен"], "note": "Alibaba open-weight LLM family"},
    {"id": "deepseek", "term": "DeepSeek", "aka": ["Дипсик"], "note": "Chinese AI lab and LLM family"},
    {"id": "mixtral", "term": "Mixtral", "aka": ["Mixtroll", "Микс Трилл"], "note": "Mistral mixture-of-experts model"},
    {"id": "mistral", "term": "Mistral", "aka": ["Мистрил"], "note": "French AI company and LLM family"},
    {"id": "llama", "term": "Llama", "aka": ["Лэмо"], "note": "Meta open-weight LLM family"},
    {"id": "gemini", "term": "Gemini", "aka": ["джеминой"], "note": "Google LLM family"},
    {"id": "pyannote", "term": "pyannote", "aka": ["Pyanote", "Payenout"], "note": "speaker diarization library"},
    {"id": "hugging-face", "term": "Hugging Face", "aka": ["Lugging Face"], "note": "model hub and ML company"},
    {"id": "llamaindex", "term": "LlamaIndex", "aka": ["Lama Index", "лимэйндекс"], "note": "LLM retrieval framework"},
    {"id": "langchain", "term": "LangChain", "aka": ["Lanchine"], "note": "LLM application framework"},
    {"id": "safetensors", "term": "safetensors", "aka": ["SAFA tensors", "Sofa Tensors"], "note": "model weight file format"},
    {"id": "pgvector", "term": "pgvector", "aka": ["Gvector", "гвектор"], "note": "Postgres vector search extension"},
    {"id": "copilot", "term": "Copilot", "aka": ["CallPilot"], "note": "GitHub AI coding assistant"},
    {"id": "codex", "term": "Codex", "note": "OpenAI coding agent"},
    {"id": "mcp", "term": "MCP", "note": "Model Context Protocol for agent tools"},
    {"id": "vllm", "term": "vLLM", "aka": ["VLLM"], "note": "LLM serving engine"},
    {"id": "gguf", "term": "GGUF", "note": "quantized model file format of llama.cpp"},
    {"id": "lora", "term": "LoRA", "note": "low-rank adaptation fine-tuning method"},
    {"id": "qlora", "term": "QLoRA", "aka": ["QLR"], "note": "quantized LoRA fine-tuning"},
    {"id": "rag", "term": "RAG", "note": "retrieval-augmented generation"},
    {"id": "rlhf", "term": "RLHF", "aka": ["ARLHF"], "note": "reinforcement learning from human feedback"},
    {"id": "llm", "term": "LLM", "aka": ["ЛЛМ"], "note": "large language model"},
    {"id": "gpt-4o", "term": "GPT-4o", "aka": ["GP-4O"], "note": "OpenAI model"},
    {"id": "midjourney", "term": "Midjourney", "aka": ["Меджерме"], "note": "image generation service"},
    {"id": "whisper", "term": "Whisper", "aka": ["Виспер"], "note": "OpenAI speech recognition model"},
    {"id": "faiss", "term": "FAISS", "aka": ["Phies"], "note": "Meta vector similarity search library"},
    {"id": "anyscale", "term": "Anyscale", "aka": ["Enniskale"], "note": "Ray-based AI compute platform"},
    {"id": "weights-biases", "term": "Weights & Biases", "aka": ["ZEIT Send Biasis"], "note": "ML experiment tracking service (W&B)"},
    {"id": "kv-cache", "term": "KV cache", "aka": ["KVCash"], "note": "transformer key-value attention cache"},
    {"id": "onnx", "term": "ONNX", "aka": ["OUNNX"], "note": "neural network exchange format"},
    {"id": "coreml", "term": "Core ML", "aka": ["CoreML"], "note": "Apple on-device ML framework"},
    {"id": "jax", "term": "JAX", "aka": ["Джекс"], "note": "Google numerical ML library"},
    {"id": "pytorch", "term": "PyTorch", "aka": ["Pytorch"], "note": "ML framework"},
    {"id": "tensorflow", "term": "TensorFlow", "aka": ["Tensorflow"], "note": "Google ML framework"},
    {"id": "cuda", "term": "CUDA", "note": "Nvidia GPU computing platform"},
    {"id": "nvidia", "term": "Nvidia", "note": "GPU maker"},
    {"id": "groq", "term": "Groq", "note": "LLM inference hardware company; not xAI Grok"},
    {"id": "haiku", "term": "Haiku", "aka": ["Хейку"], "note": "Anthropic's small Claude model"},
    {"id": "mlx", "term": "MLX", "note": "Apple silicon ML framework"},
    {"id": "openrouter", "term": "OpenRouter", "note": "LLM API router service"}
  ]
}