---
title: "AI & 3D Glossary | Datameister"
url: "https://datameister.ai/glossary/"
description: "Key concepts in computer vision, 3D generative AI, MLOps, and spatial intelligence - explained by the engineers who build production systems with them."
content-type: "text/markdown; charset=utf-8"
x-markdown-tokens: 792
---
# AI & 3D Glossary

Key concepts in computer vision, 3D AI, and MLOps - explained by the engineers who build with them.

### Computer Vision

Computer vision is a field of artificial intelligence that trains machines to interpret and understand visual information from cameras, images, and video - enabling automated detection, tracking, segmentation, and scene understanding.

[Read More →](/glossary/computer-vision)

### 3D Generative AI

3D generative AI uses deep learning models to automatically create three-dimensional assets - meshes, textures, and scenes - from text prompts, images, or other conditioning inputs, dramatically accelerating 3D content workflows.

[Read More →](/glossary/3d-generative-ai)

### Gaussian Splatting

Gaussian splatting is a real-time 3D scene representation that models a scene as millions of small 3D Gaussian primitives, each with a position, covariance, colour, and opacity - enabling photorealistic rendering at interactive frame rates without neural network inference.

[Read More →](/glossary/gaussian-splatting)

### Neural Radiance Field (NeRF)

A Neural Radiance Field (NeRF) is a neural network that learns a continuous volumetric scene representation from a set of posed images, mapping every 3D position and viewing direction to a colour and density - enabling photorealistic novel-view synthesis.

[Read More →](/glossary/neural-radiance-field)

### Point Cloud

A point cloud is an unstructured set of 3D points - each defined by (x, y, z) coordinates and optionally colour, intensity, or normals - captured by LiDAR sensors, depth cameras, or photogrammetry, serving as a raw spatial representation of a physical scene or object.

[Read More →](/glossary/point-cloud)

### Object Detection

Object detection is a computer vision task that identifies and localises objects within an image or video frame by predicting bounding boxes and class labels - enabling machines to understand what objects are present and where they are.

[Read More →](/glossary/object-detection)

### Retopology

Retopology is the process of rebuilding the surface mesh of a 3D model with cleaner, more efficient polygon topology - converting dense, irregular scans or sculpts into production-ready meshes with proper edge flow, UVs, and controllable polygon count.

[Read More →](/glossary/retopology)

### MLOps

MLOps (Machine Learning Operations) is the set of practices, tools, and infrastructure for deploying, monitoring, and maintaining machine learning models in production - bridging the gap between model development and reliable, scalable operation.

[Read More →](/glossary/mlops)

### Digital Twin

A digital twin is a virtual replica of a physical object, environment, or system - continuously synchronised with real-world data - used for monitoring, simulation, analysis, and decision-making across its lifecycle.

[Read More →](/glossary/digital-twin)

### LiDAR

LiDAR (Light Detection and Ranging) is a remote sensing technology that measures distances by emitting laser pulses and recording their return time - producing dense, accurate 3D point clouds of the surrounding environment.

[Read More →](/glossary/lidar)