Foundation Models are large-scale pre-trained models that serve as a base for a wide range of downstream tasks in artificial intelligence (AI). These models are trained on extensive datasets and are designed to capture broad and generalizable patterns in data,…
Generalization
In the context of artificial intelligence (AI), generalization refers to the ability of a machine learning model to provide accurate outputs for inputs it has not previously seen during its training phase. The goal of a well-trained model is not…
Generative AI
Generative AI refers to a subset of artificial intelligence (AI) techniques focused on creating new content, such as text, images, audio, or even video. Unlike traditional AI models, which are designed to recognize patterns and make predictions based on existing…
HyDe
HyDE (Hypothetical Document Embeddings) is a method used to improve the performance of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs), particularly in handling queries from new or unseen domains. Background: Many existing embedding retrievers struggle to generalize well to…
LLM
A Large Language Model (LLM) is a type of artificial intelligence model designed to generate human-like text based on a given input. These models are a form of machine learning and are trained on a diverse range of internet text.…
Machine Learning (ML)
Machine Learning (ML) is a subset of artificial intelligence (AI) that involves the development and application of algorithms that allow computers to learn from and make decisions or predictions based on data. It focuses on the design of systems that…
Multimodal Deep Learning
Multimodal Deep Learning is a subset of artificial intelligence (AI) and machine learning (ML) techniques that focuses on integrating and processing information from multiple types of data, or modalities, such as text, images, audio, and video. This approach allows models…
Multivariate analyses
Multivariate analyses are statistical methods that are used to investigate the relationship between several variables. In contrast to univariate analyses, which focus on only one variable, multivariate analyses look at several variables simultaneously. Multivariate analyses can be used to identify…
Predictor variable
A predictor variable is an independent variable in a statistical model that is used to make predictions about a dependent variable. In data science, predictor variables are often used to create predictive models based on historical data. These models can…
Reinforcement Learning
Reinforcement Learning (RL) is a type of machine learning where an agent learns to make decisions by performing actions in an environment to maximize some notion of cumulative reward. Unlike supervised learning, where the model learns from labeled data, RL…