Artificial intelligence without secrets. Here you will find: news from the world of AI, a glossary of terms and interesting information about algorithms.
Introduction General explainability refers to the ability of a system or model to provide understandable and interpretable explanations for its decisions or actions. It is an important aspect of artificial intelligence and machine learning, as… Read More »General Explainability
Introduction Multimodal Artificial Intelligence (AI) refers to the integration of multiple modes of communication and perception, such as speech, text, images, and gestures, into AI systems. By combining these different modalities, multimodal AI aims to… Read More »Multimodal Artificial Intelligence
Introduction The Foundation Model (FM) is a state-of-the-art language model developed by OpenAI. It is designed to generate human-like text and has been trained on a vast amount of internet text data. The FM is… Read More »Foundation Model (FM)
Introduction Training data is a crucial component in the development of artificial intelligence systems. It refers to the information or examples that are used to train an AI model or algorithm. This data is carefully… Read More »Training Data
Introduction Introduction: In the context of binary classification, a true negative refers to a situation where a model correctly predicts the absence of a particular condition or event when it is indeed absent. It is… Read More »True Negative
Introduction Explainability (XAI) refers to the ability of an AI system to provide understandable and transparent explanations for its decisions or actions. It aims to bridge the gap between the complex inner workings of AI… Read More »Explainability (XAI)
Introduction Feature selection is a crucial step in machine learning and data analysis. It involves selecting a subset of relevant features from a larger set of available features to improve the performance of a model.… Read More »Feature Selection
Uncover the hidden connections with Causal inference. Introduction Causal inference is a branch of statistics and research methodology that aims to understand cause-and-effect relationships between variables. It involves determining whether a particular factor or intervention… Read More »Causal inference
Introduction Virtual assistants (VAs) are computer programs or artificial intelligence (AI) systems designed to provide assistance and perform tasks for users. They are capable of understanding and responding to natural language commands, allowing users to… Read More »Virtual assistants (VAs)
Introduction A Trusted Research Environment (TRE) is a secure and controlled environment that allows researchers to access and analyze sensitive data while ensuring the privacy and confidentiality of that data. It provides a framework for… Read More »Trusted Research Environment (TRE)