Working glossary · 130+ terms
AI, defined for the
people who ship it.
A practitioner-grade reference for AI terms, architectures, frameworks, and operating concepts. Written for the people who actually have to ship AI systems — and the leaders who fund them.
Featured terms
Start hereArtificial General Intelligence (AGI)
A hypothetical AI system that matches or exceeds human capability across the full range of intellectual tasks, not just narrow domains.
AI Governance
The frameworks, policies, and controls that organizations apply to ensure AI systems are deployed safely, ethically, legally, and aligned with business goals.
Responsible AI
A practice of designing, building, and deploying AI systems that are fair, transparent, accountable, safe, and respectful of user privacy and rights.
AcronymEU AI Act
The European Union's comprehensive AI regulation (in force 2024-2026), the first major legal framework to classify AI systems by risk and impose obligations accordingly.
Browse by category
12 domainsFoundations & History
The ideas, debates, and milestones that shape modern AI — from symbolic reasoning to deep learning.
Machine Learning
Algorithms and methods that learn patterns from data: supervised, unsupervised, and reinforcement learning.
Deep Learning
Neural network architectures — CNNs, RNNs, Transformers — that power today's frontier models.
Natural Language Processing
Techniques and models for understanding and generating human language.
Computer Vision
How machines perceive images and video — classification, detection, segmentation, generation.
Generative AI
Foundation models, LLMs, diffusion, and the creative output stack.
AI Agents & Autonomy
Tool-using, planning, and multi-step systems that act on their own.
RAG & Retrieval
Grounding LLMs in your knowledge base — chunking, retrieval, re-ranking, citations.
Vector Databases & Embeddings
Storing and searching meaning — embedding models, ANN indexes, and the vector DB landscape.
MLOps & AI Platforms
The lifecycle: experiment tracking, model serving, monitoring, drift, evals.
AI Governance, Risk & Safety
Bias, fairness, explainability, regulation, red-teaming — the trust stack.
Hardware & Infrastructure
GPUs, TPUs, accelerators, inference engines, and the silicon under it all.
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The AIMenta team translates these concepts into AI strategy, training, and shipped systems for Asian mid-market enterprises.