AI & Machine Learning

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3D Convolutional Neural Network A neural network variant applying convolution across three spatial dimensions — used for video analysis, medical imaging, and volumetric data processing.
4-Layer AI Architecture A reference model organizing AI systems into data, model, application, and governance layers to guide enterprise AI design.
4+1 View Model (AI Systems) A documentation approach for AI systems covering logical, development, process, physical, and scenario views.
8-Bit Quantization A model compression technique reducing neural network weight precision from 32-bit floats to 8-bit integers — cutting model size and inference cost with minimal accuracy loss.

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Agent (AI Agent) An autonomous software entity that perceives its environment, makes decisions, and takes actions to achieve a goal — often using LLMs as a reasoning backbone combined with tools and memory.
Agentic AI AI systems capable of autonomously planning, deciding, and executing multi-step tasks with minimal human intervention — using tools, memory, and reasoning loops to complete complex goals.
AI Bias Systematic errors in AI model outputs caused by skewed training data, flawed model design, or unrepresentative sampling.
AI Governance The framework of policies, standards, and controls ensuring AI systems are used responsibly, transparently, and in compliance with regulations.
AI Hallucination When a generative AI model produces confident-sounding but factually incorrect or fabricated outputs.
AI Inference The process of running a trained AI model on new input data to generate predictions or outputs in production.
AI Model A mathematical system trained on data to recognize patterns and make predictions or generate outputs for a defined task.
AI Orchestration Coordinating multiple AI models, tools, data sources, and agents into a unified workflow that accomplishes a complex task.
AI-Native Development A software development approach where AI capabilities — LLMs, embeddings, agents, and ML models — are designed into the product architecture from day one, rather than added as features after the fact.
Algorithm A defined sequence of computational rules or instructions that a system follows to solve a problem or make a decision.
Anomaly Detection An ML technique identifying patterns or behaviors that deviate significantly from expected norms — used in fraud detection, predictive maintenance, and monitoring.
Attention Mechanism A neural network component allowing a model to focus on the most relevant parts of an input — the core building block of transformer architecture.
AutoML Automated Machine Learning — automating model selection, training, and tuning so non-experts can build predictive solutions without deep data science expertise.