Artificial Intelligence (AI) Terminology Concept Map

From: Translation Bureau

This concept map highlights key concepts in four important branches of AI. This novel presentation of terms makes it possible to show the relationships between concepts.

The terms selected for the concept map are just a small sample of the vast array of terms that exist in the ever-expanding domain of artificial intelligence. A wealth of additional terms are available in TERMIUM Plus® (opens in new tab), the Government of Canada’s terminology data bank.

Translation Bureau terminologists are constantly updating TERMIUM Plus® to reflect changes in AI terminology. In some cases, new terms are proposed when a gap exists in one or more languages.

A text-based description of the terms and their relationships, as well as a bilingual list of terms, can be found at the bottom of the page.

How to Use the Concept Map

To view the TERMIUM Plus® terminology record corresponding to a term in the map, click on the term. The record will open in a new tab in your browser. You can also start a new search in the TERMIUM Plus® data bank from this tab.

To move the map within the frame, click on the map and, while holding down the mouse button, drag the pointer in the desired direction.

To enlarge the map within the frame, click the “+” button located in the bottom right corner of the map or double-click on the map. To reduce its size, click the “-” button in the same corner.

When the pointer is inside the frame, you can also zoom in or out on the map by scrolling the mouse wheel. Scroll the wheel forward to zoom in on the map and backward to zoom out.

To reset the map display, click the “Reset” button in the bottom right corner of the map.

Concept Map

artificial\nintelligence\n(AI) artificial intelligence (AI) natural\nlanguage\nprocessing\n(NLP) natural language processing (NLP) artificial\nintelligence\n(AI)->natural\nlanguage\nprocessing\n(NLP) machine\nlearning\n(ML) machine learning (ML) artificial\nintelligence\n(AI)->machine\nlearning\n(ML) computer\nvision computer vision artificial\nintelligence\n(AI)->computer\nvision generative\nAI\n(GenAI) generative AI (GenAI) artificial\nintelligence\n(AI)->generative\nAI\n(GenAI) tools tools natural\nlanguage\nprocessing\n(NLP)->tools tasks tasks natural\nlanguage\nprocessing\n(NLP)->tasks language\nmodel language model tools ->language\nmodel pre-trained\nlanguage\nmodel\n(PLM) pre-trained language model (PLM) language\nmodel->pre-trained\nlanguage\nmodel\n(PLM) small\nlanguage\nmodel\n(SLM) small language model (SLM) language\nmodel->small\nlanguage\nmodel\n(SLM) large\nlanguage\nmodel\n(LLM) large language model (LLM) language\nmodel->large\nlanguage\nmodel\n(LLM) machine\ntranslation\n(MT) machine translation (MT) tasks ->machine\ntranslation\n(MT) sentiment\nanalysis sentiment analysis tasks ->sentiment\nanalysis speech\nrecognition speech recognition tasks ->speech\nrecognition rule-based\nmachine\ntranslation\n(RBMT) rule-based machine translation (RBMT) machine\ntranslation\n(MT)->rule-based\nmachine\ntranslation\n(RBMT) statistical\nmachine\ntranslation\n(SMT) statistical machine translation (SMT) machine\ntranslation\n(MT)->statistical\nmachine\ntranslation\n(SMT) neural\nmachine\ntranslation\n(NMT) neural machine translation (NMT) machine\ntranslation\n(MT)->neural\nmachine\ntranslation\n(NMT) shallow\nlearning\n(SL) shallow learning (SL) machine\nlearning\n(ML)->shallow\nlearning\n(SL) deep\nlearning\n(DL) deep learning (DL) machine\nlearning\n(ML)->deep\nlearning\n(DL) techniques techniques machine\nlearning\n(ML)->techniques tools tools machine\nlearning\n(ML)->tools supervised\nlearning supervised learning techniques->supervised\nlearning semi-\nsupervised\nlearning semi- supervised learning techniques->semi-\nsupervised\nlearning unsupervised\nlearning unsupervised learning techniques->unsupervised\nlearning self-\nsupervised\nlearning self- supervised learning techniques->self-\nsupervised\nlearning reinforcement\nlearning reinforcement learning techniques->reinforcement\nlearning machine\nlearning\nmodel machine learning model tools->machine\nlearning\nmodel knowledge\ngraph knowledge graph tools->knowledge\ngraph training\ndata training data tools->training\ndata big data big data tools->big data tasks tasks computer\nvision-> tasks object\ndetection object detection tasks->object\ndetection facial\nrecognition facial recognition tasks->facial\nrecognition image\nsegmentation image segmentation tasks->image\nsegmentation semantic\nsegmentation semantic segmentation image\nsegmentation->semantic\nsegmentation instance\nsegmentation instance segmentation image\nsegmentation->instance\nsegmentation panoptic\nsegmentation panoptic segmentation image\nsegmentation->panoptic\nsegmentation tasks tasks generative\nAI\n(GenAI)-> tasks content\ngeneration content generation tasks ->content\ngeneration image\ngeneration image generation content\ngeneration->image\ngeneration video\ngeneration video generation content\ngeneration->video\ngeneration audio\ngeneration audio generation content\ngeneration->audio\ngeneration text\ngeneration text generation content\ngeneration->text\ngeneration tools tools content\ngeneration-> tools techniques techniques content\ngeneration->techniques code\ngeneration code generation content\ngeneration->code\ngeneration GenAI\ntranslation GenAI translation text\ngeneration->GenAI\ntranslation text\nsummarization text summarization text\ngeneration->text\nsummarization generative\npre-trained\ntransformer\n(GPT) generative pre-trained transformer (GPT) tools ->generative\npre-trained\ntransformer\n(GPT) prompt\nengineering prompt engineering techniques ->prompt\nengineering retrieval-\naugmented\ngeneration\n(RAG) retrieval- augmented generation (RAG) techniques ->retrieval-\naugmented\ngeneration\n(RAG)


Alternative Text

The concept map contains a sample of terms from four important branches of artificial intelligence (AI):

  • machine learning (ML)
  • natural language processing (NLP)
  • computer vision
  • generative AI (GenAI)

The following list shows the relationships between these branches and the terms in the concept map.

Machine Learning (ML)

Types of Machine Learning

  • shallow learning (SL)
  • deep learning (DL)

Machine Learning Tools

  • machine learning model
  • knowledge graph
  • training data
  • big data

Machine Learning Techniques

  • supervised learning
  • semi-supervised learning
  • unsupervised learning
  • self-supervised learning
  • reinforcement learning

Natural Language Processing (NLP)

Natural Language Processing Tools

  • language model

Types of Language Models

  • pre-trained language model (PLM)
  • small language model (SLM)
  • large language model (LLM)

Natural Language Processing Tasks

  • speech recognition
  • machine translation (MT)
  • sentiment analysis

Types of Machine Translation

  • rule-based machine translation (RBMT)
  • statistical machine translation (SMT)
  • neural machine translation (NMT)

Computer Vision

Computer Vision Tasks

  • facial recognition
  • object detection
  • image segmentation

Types of Image Segmentation

  • semantic segmentation
  • instance segmentation
  • panoptic segmentation

Generative AI (GenAI)

Generative AI Tasks

  • content generation

Types of Content Generation

  • image generation
  • code generation
  • video generation
  • audio generation
  • text generation

Types of Text Generation

  • GenAI translation
  • text summarization

Content Generation Techniques

  • prompt engineering
  • retrieval-augmented generation (RAG)

Content Generation Tools

  • generative pre-trained transformer (GPT)
Bilingual List of Terms (English-French)
English French
artificial intelligence (AI) intelligence artificielle (IA)
audio generation génération de contenu audio
big data mégadonnées
code generation génération de code
computer vision vision par ordinateur
content generation génération de contenu
deep learning (DL) apprentissage profond
facial recognition reconnaissance faciale
GenAI translation traduction par IA générative
generative AI (GenAI) IA générative (IAG)
generative pre-trained transformer (GPT) transformeur génératif préentraîné
image generation génération d’images
image segmentation segmentation d’images
instance segmentation segmentation d’instances
knowledge graph graphe de connaissances
language model modèle de langage
large language model (LLM) grand modèle de langage (GML)
machine learning (ML) apprentissage automatique
machine learning model modèle d’apprentissage automatique
machine translation (MT) traduction automatique (TA)
natural language processing (NLP) traitement automatique du langage naturel (TALN)
neural machine translation (NMT) traduction automatique neuronale (TAN)
object detection détection d’objets
panoptic segmentation segmentation panoptique
pre-trained language model (PLM) modèle de langage préentraîné
prompt engineering rédactique
reinforcement learning apprentissage par renforcement
retrieval-augmented generation (RAG) génération améliorée par récupération d’information (GARI)
rule-based machine translation (RBMT) traduction automatique à base de règles (TABR)
self-supervised learning apprentissage autosupervisé
semantic segmentation segmentation sémantique
semi-supervised learning apprentissage semi-supervisé
sentiment analysis analyse de sentiments
shallow learning (SL) apprentissage peu profond
small language model (SLM) petit modèle de langage (PML)
speech recognition reconnaissance de la parole
statistical machine translation (SMT) traduction automatique statistique (TAS)
supervised learning apprentissage supervisé
text generation génération de texte
text summarization génération de résumé
training data données d’entraînement
unsupervised learning apprentissage non supervisé
video generation génération de vidéo
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