Quantum AI refers to the integration of quantum computing and artificial intelligence to enhance the performance and scalability of AI systems. By leveraging quantum principles such as superposition and entanglement, quantum AI aims to accelerate tasks like optimization, pattern recognition,...

DALL·E is a generative AI model developed by OpenAI that creates images from natural language prompts. Introduced in 2021, DALL·E gained attention for its ability to produce imaginative and contextually accurate visuals from abstract or unusual descriptions. It marked a...

Long Short-Term Memory (LSTM) is a type of recurrent neural network (RNN) architecture specifically designed to model sequences and handle long-range dependencies. Introduced by Hochreiter and Schmidhuber in 1997, LSTM overcomes the limitations of traditional RNNs by preventing the vanishing...

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...