AI lingo

AI lingo is the specialized vocabulary, terminology, and jargon used within artificial intelligence research, development, and deployment that encompasses technical concepts, methodologies, and system components. This domain-specific language includes foundational terms like neural networks, machine learning, and deep learning, alongside advanced concepts such as transformer architectures, attention mechanisms, and reinforcement learning. AI lingo spans multiple disciplines including computer science, statistics, cognitive science, and engineering, creating a comprehensive lexicon for describing algorithmic processes, model architectures, training methodologies, and performance metrics. Common categories include model types (CNNs, RNNs, LLMs), training processes (fine-tuning, pre-training, RLHF), evaluation metrics (accuracy, F1-score, perplexity), and deployment concepts (inference, latency, scalability). For AI agents, understanding AI lingo is essential for effective communication between technical teams, stakeholders, and end-users, enabling precise specification of requirements, capabilities, and limitations.