Artificial Intelligence (AI)

The Agentic Era refers to the next phase of artificial intelligence, where AI systems, known as ‘agents’, can independently perform complex tasks and make decisions without direct human instruction. These autonomous agents are designed to understand goals, plan steps, and

An AI classifier is a type of machine learning model used to organise data into specific categories or labels based on patterns it identifies. It is commonly used in tasks like spam email detection, image recognition, or sentiment analysis. By

The AI Development Lifecycle refers to the structured process of creating, deploying, and maintaining artificial intelligence models. It involves key stages such as data collection, model training, testing, deployment, and ongoing optimisation. This lifecycle ensures AI systems are effective, reliable,

AI models are computer programmes trained on extensive data to recognise patterns. They use machine learning to make predictions, generate content, or automate complex tasks. In digital marketing, they’re crucial for personalising user experiences, optimising campaigns, and improving efficiency.

AlphaGo is an AI program developed by Google DeepMind that plays the board game Go, a complex strategy game. It made history in 2016 by defeating world champion Lee Sedol, showcasing the power of machine learning and neural networks. AlphaGo

Andrew Yan-Tak Ng is a leading figure in artificial intelligence co-founded Google Brain and Coursera. His work has been pivotal in advancing machine learning, making AI more accessible to developers and businesses. Ng’s influence is significant in the integration of

Context engineering is the process of deciding what information an AI model receives, and how that information is organised, so it can perform a task effectively. This can include instructions, conversation history, retrieved documents, tools, memory and other relevant data.

A context window is the amount of information an AI model can consider while generating a response, essentially its working memory for a particular interaction. It can include your prompts, previous messages, documents, instructions and other information provided to the

Deep learning is a field within artificial intelligence (AI) and a specialised subset of machine learning that uses artificial neural networks with multiple layers to analyse vast amounts of data. It enables tasks such as image recognition, language translation, and

General AI, also known as Artificial General Intelligence (AGI), refers to highly advanced AI systems capable of performing any intellectual task that a human can do. Unlike narrow AI, which is designed for specific tasks, general AI can adapt, learn,

Generative AI refers to a type of artificial intelligence that creates new content such as text, images, audio, or video based on the data it has been trained on. Using algorithms like machine learning, it can generate human-like responses, designs,

Google DeepMind is an artificial intelligence research lab owned by Alphabet Inc. It focuses on creating machine learning algorithms and AI systems capable of solving complex problems, such as healthcare advancements and optimising energy use. Known for achievements like AlphaGo,

Grounding means connecting an AI model’s response to specific, verifiable sources of information rather than relying only on what the model learned during training. These sources could include documents, databases, websites or company data. Grounding can make AI responses more

An AI hallucination happens when an AI model generates information that sounds convincing but is inaccurate, unsupported or completely fabricated. This can include invented facts, sources, statistics or explanations. Hallucinations are one reason why important AI-generated information should still be

A Large Language Model (LLM) is an advanced type of artificial intelligence designed to understand and generate human-like text. Trained on vast amounts of data, LLMs can perform tasks such as answering questions, creating content, and analysing text. Widely used

Machine learning (ML) is a field within artificial intelligence (AI) that enables computers to learn from data and improve their performance over time without being explicitly programmed. It’s widely used in areas like recommendation systems, fraud detection, and predictive analytics.

Marketing engineering is the systematic application of data, technology, and computational models (rather than gut instinct alone) to sharpen marketing decisions, build automated workflows, and manage operational infrastructure.

Model Context Protocol (MCP) is an open standard that allows AI applications to connect with external data sources, tools and services in a consistent way. Instead of building a completely different integration for every system, MCP provides a standardised method

Meta Andromeda is a powerful AI retrieval engine built to work at scale. In milliseconds, it processes tens of millions of ad candidates to deliver the most relevant ads to each individual user: precisely, efficiently, and without compromise.

The Model Context Protocol (MCP) is a framework defining how AI models efficiently manage and interpret contextual information. This ensures AI applications, especially in digital marketing, produce highly relevant and accurate outputs. It’s crucial for boosting performance and precision when

Model Context Protocol (MCP) is an open standard that lets AI applications connect securely to external data sources and tools via MCP servers. Instead of relying only on what you type into a prompt, an MCP-enabled assistant can fetch the

Multi-agent systems refer to a network of independent agents (software or robots) that work together to solve complex problems or achieve common goals. Each agent operates autonomously but communicates and collaborates with others within the system. These systems are widely

Narrow AI, also known as Weak AI, refers to artificial intelligence designed to perform specific tasks or solve particular problems. Unlike general AI, it operates within a limited scope, such as virtual assistants, recommendation systems, or facial recognition. It’s highly

Natural Language Generation (NLG) is an AI technology that converts structured data into human-like written or spoken text. As a subfield of Natural Language Processing (NLP), it powers everything from chatbots and voice assistants to automated reporting and dynamic content.

Natural Language Processing (NLP) is a branch of artificial intelligence that enables computers to understand, interpret, and respond to human language. It powers technologies like chatbots, voice assistants, and language translation tools. NLP helps businesses analyse text or speech data,

A prompt or command is an input or instruction given to a computer program, AI model, or chatbot to generate a specific response or perform a task. In digital marketing, prompts are often used to guide AI tools in creating

Prompt engineering is the process of crafting precise and effective prompts to guide AI models, like ChatGPT, in generating accurate and relevant responses. It involves understanding how AI interprets input and optimising prompts to achieve desired outcomes. This skill is

A prompt library is a curated collection of pre-written instructions or questions used to guide AI models. These libraries streamline content creation, ensuring consistent and high-quality outputs for various digital marketing tasks. They save time by providing ready-to-use prompts for

Prompt literacy refers to the ability to craft clear, effective prompts when interacting with AI tools like chatbots or generative AI models. It involves understanding how to phrase questions or commands to get accurate and relevant responses. As AI becomes

Retrieval-Augmented Generation (RAG) is a technique where an AI system first retrieves relevant information from an external source and then uses that information to generate its response. Instead of relying solely on the model’s existing knowledge, it can work with

Shadow AI refers to artificial intelligence tools or systems used within an organisation without the approval or knowledge of IT or management. These unauthorised AI solutions often arise when teams seek faster, more flexible tools to meet their needs, but

The Turing Test, proposed by Alan Turing in 1950, evaluates a machine’s ability to exhibit human-like intelligence. If a machine can engage in a conversation indistinguishable from a human, it is said to have passed the test. This concept is

Vibe coding is an AI-driven software development approach that allows users to build applications by describing their desired outcome in natural language. Instead of writing code line-by-line, developers prompt a Large Language Model (LLM) with the high-level ‘vibe’ or intent,