Glossary of AI Terms

Adaptive AI: AI systems that can adapt their behavior based on changes in their environment or in the data they process.

AI and Sustainability: The use of AI in promoting environmental sustainability, such as through optimizing energy use, predicting environmental changes, or aiding in sustainable resource management.

AI Training (Training People About AI): Educating individuals on AI concepts, technologies, and applications.

AI Training (Training against an LLM): The process of providing data and learning experiences to a large language model (LLM) to improve its performance.

AI Inference: The process of using a trained AI model to make predictions based on new data

AI-Enhanced Interviews: The use of AI technology, such as natural language processing and machine learning, to aid in the process of conducting interviews.

AI Programmatic Ad Buying: The use of AI in programmatic ad buying helps automate the decision-making process of where ads are placed, optimizing for the best audience and price in real-time.

Bias – a disproportionate weight in favor of or against an idea or thing, usually in a way that is closed-minded, prejudicial, or unfair.

Big Data: Extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

Cloud Platforms (Importance to AI): Cloud platforms provide the necessary computational power and data storage for AI, making them crucial for the development and deployment of AI applications.

Content Personalization: Tailoring digital content to individual user preferences based on data about their behaviors and interests.

Deepfakes: Synthetic media where a person in an existing image or video is replaced with someone else’s likeness, often using artificial intelligence.

Data Journalism: A journalism specialty reflecting the increased role that numerical data plays in the production and distribution of information in the digital era.

Ethics: Moral principles that govern a person’s behavior or the conducting of an activity, often used in the context of professional standards.

Predictive Analytics: Techniques that use statistical algorithms and machine learning to identify the likelihood of future outcomes based on historical data.

Social Influence: The effect that people have on the beliefs, feelings, and behaviors of others, through direct or indirect means.

Virtual Reality: A simulated experience that can be similar to or completely different from the real world, often used for entertainment or education.

Natural Language Processing (NLP): A branch of artificial intelligence that helps computers understand, interpret, and manipulate human language.

Machine Learning: A type of artificial intelligence that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so.

Sentiment Analysis: Using AI to determine the emotional tone behind a series of words, to gain an understanding of the attitudes, opinions, and emotions expressed within an online mention.

News Recommendation Engines: AI systems that suggest news articles and content to users based on their past reading behavior and preferences.

Media Bias Detection: The process of analyzing media content to identify potential bias in reporting.

Virtual Studios: A virtual space where production can take place without the need for a physical set, often using green screen technology and computer-generated imagery.

Speech Recognition: Technology that can recognize spoken words, which can then be converted into text.

Language Translation: The process of translating words or text from one language into another, increasingly facilitated by AI.

Chatbots: Computer programs designed to simulate conversation with human users, especially over the Internet.

Virtual Assistants: AI-powered software agents that can perform tasks or services for an individual, often in the context of scheduling, reminders, or online searches.

Large Language Model: A type of artificial intelligence model designed to understand, generate, and manipulate human language at a large scale.

Artificial Intelligence: The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

GenAI: A term that may refer to General AI (Artificial General Intelligence), denoting the type of AI that has the ability to understand, learn, and apply its intelligence broadly, similar to human intelligence.

Machine Learning: A subset of AI that involves the study of computer algorithms that improve automatically through experience and by the use of data.

Deep Learning: A subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled.

Neural Networks: A series of algorithms that attempt to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates.

AI Certificate: A certification indicating that an individual has acquired certain knowledge or skills in artificial intelligence.

AI Ad Bidding (Programmatic): The use of AI in programmatic advertising to automatically bid on ad inventory in real time, optimizing for the best ad placements and prices.

Forecast (Predictive AI): Using AI to predict future conditions or occurrences, typically in the context of business intelligence.

Translation: The process of translating words or text from one language into another.

Speech-to-Text: Technology that can convert spoken language into written text.

Image Generation: The process of creating visual images, often using computer software.

Ideation: The formation of ideas or concepts.