A Bayesian Network is a probabilistic graphical model that represents a set of variables and their conditional dependencies using a directed acyclic graph (DAG). It combines principles from graph theory and probability theory to model uncertainty, causality, and inference in...

Knowledge Distillation is a model compression technique where a smaller model (student) learns to replicate the behavior of a larger, more complex model (teacher). Instead of relying solely on original training data, the student also learns from the teacher’s output...

Group Relative Policy Optimization (GRPO) is a reinforcement learning (RL) algorithm designed to enhance the reasoning capabilities of large language models (LLMs). Introduced in the DeepSeekMath project, GRPO modifies traditional policy optimization methods by eliminating the need for a value...

Stable Diffusion is an open-source text-to-image model developed by Stability AI. It generates high-quality images from natural language prompts using a latent diffusion process. Unlike earlier models, Stable Diffusion runs efficiently on consumer GPUs and supports greater control through features...

In the context of AI, machine learning, and data systems, indexing refers to the process of organizing data—often unstructured or high-dimensional—in a way that makes it fast and efficient to retrieve relevant information. It is particularly critical in retrieval-augmented generation...

A Generative Adversarial Network (GAN) is a class of machine learning models designed for generative tasks, where the goal is to create new data that mimics the characteristics of a given dataset. A GAN consists of two neural networks—a generator...

DeepSeek is an open-source large language model (LLM) developed by a Chinese AI research team. Designed to compete with models like GPT-3.5, DeepSeek is trained on a massive corpus of Chinese and English data. Its performance spans a range of...

Claude is a family of large language models (LLMs) developed by Anthropic. These models are designed to be helpful, honest, and harmless. Named after Claude Shannon, they focus on aligning AI behavior with human values. Claude models use reinforcement learning...

In Natural Language Processing (NLP), chunking refers to the process of segmenting a sentence into syntactically correlated parts, or “chunks,” such as noun phrases (NPs), verb phrases (VPs), and prepositional phrases (PPs). It sits between part-of-speech (POS) tagging and full...