Jargon Buster

Instances where a Generative AI model generates output that is not grounded in its input data, i.e., it "makes things up". This is particularly common in tasks like text generation from large language models, where the model might generate plausible sounding but incorrect or nonsensical information.

A large language model is a machine learning model that uses a huge amount of data to perform natural language processing tasks. LLMs can generate, translate, summarise, and predict text. They can also answer questions and perform other tasks. LLMs can automate tasks like content creation, personalise ads, and analyse customer data.

A subset of AI that involves algorithms allowing machines to learn patterns from data and make decisions without explicit programming.

The process of tailoring ads to individual users based on their behaviour, preferences, and demographic information is often powered by machine learning and AI.

The buying and selling of online ad inventory through automated methods rather than human actions, often using AI. This includes but is not limited to Real-Time Bidding (RTB).

A way of transacting media that allows an individual ad impression to be put up for bid in real time. This is done through a programmatic on-the spot auction, which is similar to how financial markets operate. RTB allows for addressable advertising; the ability to serve ads to consumers directly based on their demographic, psychographic, or behavioural attributes. AI plays a key role in bid adjustments and targeting.

The process of optimising ads and content for voice search, is an area where AI plays a significant role in understanding natural language queries.

AI models and techniques that provide human-understandable explanations of their decisions, enhancing transparency and trust.

A popular deep learning model for real-time object detection that can identify multiple objects in images or video.