Fine-Tuning is a crucial process in the development and optimization of Large Language Models (LLMs). It involves taking a pre-trained model, which has been initially trained on a large corpus of general data, and adapting it to perform specific tasks…
Foundation Models
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…
GPAI (General-Purpose AI Model)
GPAI stands for General-Purpose AI Model and refers to a category of artificial intelligence models that exhibit broad applicability and can competently perform a wide range of different tasks. Unlike narrow AI models designed for specific, single-use applications, GPAI models…
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…
MoE (Mixture of Experts)
Mixture of Experts (MoE) is an advanced neural network architecture designed to improve scalability and efficiency in large AI models. Instead of using a single, monolithic model to process all data, MoE divides the work among multiple specialized sub-models—called experts.…
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…