AI Glossary

An AI DAN prompt (short for "Do Anything Now") is a type of prompt injection attack designed to bypass an AI model’s built-in ethical and security restrictions.

AI email security is the use of artificial intelligence technologies to safeguard email communication from cyber threats.

AI native refers to products, services, or organizations that are inherently designed around artificial intelligence, embedding it as a foundational component rather than as an add-on.

AI TRiSM is a set of policies and technologies that govern AI models to mitigate risks while maintaining trust and transparency.

Artificial intelligence is the simulation of human intelligence by machines to perform tasks such as learning, reasoning, and decision-making.

Behavioral AI combines artificial intelligence techniques with behavioral science to analyze and interpret human actions, preferences, and patterns.

Deep learning is a type of ML using neural networks with many layers to analyze complex data patterns

Generative adversarial networks (GANs) are a class of machine learning models that generate highly realistic synthetic data, including images, text, and video.

Generative AI refers to artificial intelligence systems designed to produce original and realistic content by learning patterns and structures from vast datasets.

Jailbreaking AI is the process of bypassing built-in safety mechanisms in AI models to force them to generate restricted or unethical outputs.

Large language models (LLMs) are advanced machine learning models trained on extensive text datasets to understand and generate human-like language.

Machine learning is a subset of AI focused on algorithms that enable systems to learn and improve from experience without being explicitly programmed.

Malicious AI encompasses the intentional misuse or weaponization of artificial intelligence to conduct activities that harm individuals, organizations, or societies.

Natural language processing (NLP) is a field of artificial intelligence that focuses on enabling computers to understand, interpret, and respond to text or speech in a way that feels natural to humans.

Natural language understanding (NLU) enables AI to extract meaning, context, and intent from text, powering advanced cybersecurity threat detection.

A neural network is a type of machine learning model designed to recognize complex patterns through layers of interconnected neurons.

Predictive analytics is a branch of AI and machine learning that analyzes historical data to forecast future outcomes.

Sentiment analysis is a branch of natural language processing (NLP) that enables AI to determine the emotional tone behind text-based communications.

Supervised learning involves training an AI model on a dataset that includes both input data and corresponding labeled outputs.

Unsupervised learning enables AI to identify hidden patterns and anomalies without labeled data, enhancing cybersecurity and threat detection.