GLOSSARY · T-GLOS-001
AI Glossary
68 essential terms in artificial intelligence — from Large Language Model to Mechanistic Interpretability. Each entry is a short, source-grounded definition, an explanation, why it matters, and a few common questions. Updated as the vocabulary moves.
A
- Agentic AI Agentic AI refers to artificial intelligence systems that can autonomously pursue complex goals, make decisions, and take actions in dynamic environments.
- AGI Artificial general intelligence (AGI) is a hypothetical type of AI that matches or surpasses human cognitive abilities across a wide range of tasks.
- AI Agent An AI agent is an autonomous software entity that perceives its environment, makes decisions, and takes actions to achieve specific goals.
- AI Alignment AI alignment is the field of research aimed at ensuring that artificial intelligence systems reliably pursue the goals and values intended by their human designers.
- AI Ethics AI ethics is a field of study and practice that examines the moral principles and societal impacts of artificial intelligence systems.
- AI Safety AI safety is a field of research focused on ensuring that artificial intelligence systems operate reliably and align with human values and intentions.
- Attention Mechanism An attention mechanism is a neural network component that allows a model to dynamically weigh the importance of different input elements when producing an output.
B
- Backpropagation Backpropagation is a supervised learning algorithm that computes the gradient of a loss function with respect to network weights by applying the chain rule through the network's layers.
- Benchmark (AI) A benchmark in AI is a standardized test or set of tasks used to evaluate and compare the performance of different models or systems.
C
- Chain of Thought Chain of thought is a prompting technique that elicits step-by-step reasoning from large language models by providing intermediate reasoning steps in the prompt.
- Constitutional AI Constitutional AI is a method for training AI systems to align with a set of principles or rules, reducing harmful outputs without extensive human feedback.
- Context Window A context window is the maximum number of tokens a language model can process in a single input, including both the prompt and generated output.
- Creator Economy The creator economy is an economic model where independent content creators monetize their work directly through digital platforms and audiences.
- Creator Management Agency A creator management agency represents and supports digital content creators in business dealings, brand partnerships, and career development.
- Creator Monetization Creator monetization refers to the methods and systems through which individuals who produce digital content generate revenue from their work.
- Creator Recruitment Creator recruitment is the process of identifying, vetting, and onboarding content creators to produce branded content or promote products and services.
- CRM (Customer Relationship Management) Customer relationship management (CRM) is a system for managing a company's interactions with current and potential customers, often using technology to organize, automate, and synchronize sales, marketing, customer service, and technical support.
- Custom Software Development Custom software development is the process of designing, creating, deploying, and maintaining software applications tailored to meet specific user or organizational requirements.
D
E
F
- Few-Shot Learning Few-shot learning is a machine learning paradigm where a model learns to make predictions from a very small number of labeled examples per class.
- Fine-tuning Fine-tuning is the process of taking a pre-trained machine learning model and further training it on a specific, smaller dataset to adapt it for a particular task or domain.
- Foundation Model A foundation model is a large-scale machine learning model trained on broad data that can be adapted to a wide range of downstream tasks.
G
- GAN A generative adversarial network (GAN) is a class of machine learning framework where two neural networks contest with each other in a zero-sum game to generate new, synthetic instances of data that resemble a training set.
- Gradient Descent Gradient descent is an iterative optimization algorithm that minimizes a function by moving in the direction of steepest descent, defined by the negative gradient.
H
- Hallucination (AI) Hallucination in AI refers to the generation of plausible but factually incorrect or nonsensical content by a language model.
- Headless CMS A headless CMS is a content management system that separates content creation and storage from front-end presentation, delivering content via APIs.
I
- In-Context Learning In-context learning is a method where a language model performs a task by conditioning on a set of input-output examples provided in the prompt, without updating its parameters.
- Inference Inference is the process of using a trained machine learning model to make predictions or decisions on new, unseen data.
- Influencer Marketing Influencer marketing is a form of social media marketing that uses endorsements and product mentions from individuals who have a dedicated social following and are viewed as experts within their niche.
J
K
L
- Large Language Model (LLM) A large language model (LLM) is a neural network trained on vast text corpora to generate coherent, context-aware text by predicting subsequent tokens.
- LoRA (Low-Rank Adaptation) LoRA (Low-Rank Adaptation) is a parameter-efficient fine-tuning method that approximates weight updates in pre-trained neural networks using low-rank decomposition.
M
- MCN (Multi-Channel Network) A multi-channel network (MCN) is an organization that partners with online content creators to provide services such as audience development, monetization, and production support.
- Mechanistic Interpretability Mechanistic interpretability is the field of research that reverse-engineers neural networks into human-understandable algorithms and mechanisms.
- MENA Creator Economy The MENA Creator Economy refers to the ecosystem of content creators, platforms, and monetization tools operating across the Middle East and North Africa region.
- Mixture of Experts (MoE) A machine learning architecture that divides a model into multiple specialized sub-networks (experts) and activates only a subset per input, enabling larger model capacity with lower computational cost.
- Mobile App Development Mobile app development is the process of creating software applications that run on mobile devices such as smartphones and tablets.
- Model Card A model card is a standardized document that discloses the intended use, performance, and limitations of a machine learning model.
- Model Distillation Model distillation is a technique where a smaller, simpler model (student) is trained to replicate the behavior of a larger, more complex model (teacher).
- Multimodal Model A multimodal model is a machine learning system that processes and integrates information from multiple data types, such as text, images, audio, and video.
N
P
- Pre-training Pre-training is an initial phase in machine learning where a model is trained on a large, general dataset to learn broad features before being fine-tuned for a specific task.
- Prompt Engineering Prompt engineering is the process of designing and refining input queries to large language models to elicit desired outputs.
- Prompt Injection Prompt injection is a security exploit where an attacker inserts malicious instructions into a prompt to override a language model's intended behavior.
Q
R
- RAG (Retrieval Augmented Generation) Retrieval Augmented Generation (RAG) is a technique that combines a retrieval step with a generative language model to produce responses grounded in external knowledge.
- Recruitment Funnel A recruitment funnel is a model that visualizes the stages candidates pass through from initial awareness to hiring, tracking conversion rates at each step.
- Red Teaming (AI) Red teaming in AI is a structured adversarial testing process where a team simulates attacks to identify vulnerabilities, biases, or harmful outputs in an AI system.
- Reinforcement Learning Reinforcement learning is a machine learning paradigm where an agent learns to make decisions by interacting with an environment to maximize cumulative reward.
- RLHF Reinforcement learning from human feedback (RLHF) is a machine learning technique that uses human preferences to fine-tune a model's behavior.
S
- SaaS (Software as a Service) Software as a Service (SaaS) is a software licensing and delivery model in which applications are hosted by a provider and made available to customers over the internet.
- Self-Supervised Learning Self-supervised learning is a machine learning paradigm where a model learns representations from unlabeled data by solving pretext tasks that generate supervisory signals from the data itself.
- Short-Form Video Short-form video is a type of digital video content typically lasting from a few seconds to a few minutes, designed for quick consumption and often optimized for mobile viewing.
- Supervised Learning Supervised learning is a machine learning paradigm where a model is trained on a labeled dataset to learn a mapping from inputs to outputs.
- Synthetic Data Synthetic data is artificially generated information that mimics real-world data, created algorithmically rather than collected from actual events or users.
T
- Talent Management Talent management is the systematic process of attracting, developing, retaining, and deploying individuals to meet organizational goals.
- TikTok LIVE Monetization TikTok LIVE Monetization refers to the process by which creators earn revenue during live video broadcasts through virtual gifts, brand partnerships, and other platform-supported income streams.
- Token / Tokenization Tokenization is the process of splitting text into smaller units called tokens, which are the basic input elements for language models.
- Training Training is the process of optimizing a machine learning model's parameters using data to minimize error on a specified objective.
- Transfer Learning Transfer learning is a machine learning technique where a model developed for one task is reused as the starting point for a model on a second task.
- Transformer The Transformer is a neural network architecture that processes sequential data using self-attention mechanisms, eschewing recurrence for parallel computation.
U
- UGC (User-Generated Content) User-generated content (UGC) is any form of content, such as text, images, videos, or reviews, created and published by unpaid contributors or fans of a brand or platform.
- Unsupervised Learning Unsupervised learning is a type of machine learning where algorithms identify patterns and structures in data without using labeled outputs or explicit guidance.