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Human in the Loop
Human in the Loop refers to a system or process where human input, oversight, or intervention is required to assist or guide automated technologies, such as artificial intelligence, to ensure accuracy, make decisions, or handle complex tasks.
AI
Large Language Model
A Large Language Model is a type of artificial intelligence that can understand and generate human-like text by analyzing vast amounts of written language data.
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Machine learning bias
Machine learning bias refers to systematic errors in a machine learning model that result from incorrect assumptions in the learning process, often leading to unfair or inaccurate outcomes. This can occur due to biased training data or flawed algorithms, affecting the model's predictions or decisions.
AI
Model
A model in technology, especially in fields like artificial intelligence and machine learning, is a simplified representation or simulation of a real-world process or system. It is created using data and algorithms to make predictions or decisions without being explicitly programmed for the task.
AI
Natural language processing
Natural Language Processing (NLP) is a technology that allows computers to understand, interpret, and respond to human language in a way that is both meaningful and useful.
AI
Parameters
Parameters are variables in a system or model that can be adjusted to affect its behavior or output.
AI Cyber Security
Prompt defense
Prompt defense is a strategy or technique used to protect AI systems from generating harmful or inappropriate outputs by carefully designing and controlling the input prompts given to the AI.
AI
Prompt engineering
Prompt engineering is the process of designing and refining the input given to an AI model to achieve the desired output or response.
AI Cyber Security
Red Teaming
Red Teaming is a practice where a group simulates an attack on an organization's systems to identify vulnerabilities and improve security.
AI
Reinforcement learning
Reinforcement learning is a type of artificial intelligence where a computer learns to make decisions by trying different actions and receiving feedback in the form of rewards or penalties, similar to how humans learn from experience.
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Retrieval Augmented Generation
Retrieval Augmented Generation (RAG) is a method in artificial intelligence where a system retrieves relevant information from a database or external source to help generate more accurate and contextually relevant responses or content.
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Safety
Safety refers to the condition of being protected from harm or danger. In technology, it involves measures and practices to ensure that systems operate without causing injury, damage, or unintended consequences.
AI
Sentiment analysis
Sentiment analysis is a technology that uses computers to determine whether a piece of text expresses a positive, negative, or neutral emotion.
AI
Supervised learning
Supervised learning is a type of machine learning where a computer is trained using labeled data, meaning the input data is paired with the correct output. The goal is for the computer to learn the relationship between inputs and outputs so it can predict the output for new, unseen data.
AI
Toxicity
Toxicity in technology refers to harmful or negative behavior, language, or content, often found in online communities or platforms, that can create a hostile or unpleasant environment for users.
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Transformer
A Transformer is a type of artificial intelligence model used in natural language processing that can understand and generate human language by processing words in relation to each other, rather than one at a time.
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Transparency
Transparency in technology refers to the clarity and openness with which information, processes, and decisions are shared, allowing users to understand how systems work and how their data is used.
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Unsupervised learning
Unsupervised learning is a type of machine learning where a computer is trained to find patterns and relationships in data without being given specific instructions or labeled examples.
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Validation
Validation is the process of checking if something meets certain criteria or standards, ensuring it works correctly and as intended.
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Zero data retention
Zero data retention refers to a policy or practice where no user data is stored or retained after it is no longer needed for its immediate purpose, ensuring maximum privacy and security.