Artificial Intelligence

The simulation of human intelligence processes by computer systems, including learning, reasoning, and self-correction. AI encompasses a broad range of techniques from rule-based systems to deep neura...

A fundamental algorithm in neural network training that calculates the gradient of the loss function with respect to each weight by propagating the error backward through the network layers, enabling...

A field of artificial intelligence that enables computers to interpret and understand visual information from the world, such as images and videos, by extracting meaningful data using deep learning al...

A subset of machine learning that uses artificial neural networks with multiple layers (deep neural networks) to learn hierarchical representations of data. Deep learning excels at tasks like image re...

The use of Graphics Processing Units for general-purpose computing tasks, particularly matrix operations central to machine learning. GPUs can process thousands of operations in parallel, making them...

A type of artificial intelligence that can create new content such as text, images, music, code, and video by learning patterns from existing data. Models like GPT, DALL-E, and Stable Diffusion are pr...

A type of AI model trained on vast amounts of text data that can understand, generate, and reason about human language. LLMs like GPT-4, Claude, and Llama use transformer architectures with billions o...

A branch of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed. Machine learning algorithms use statistical techniques to identify pa...

A subfield of AI focused on the interaction between computers and human language. NLP enables machines to read, understand, interpret, and generate human language, powering applications like chatbots,...

A computing system inspired by the biological neural networks of the human brain. Neural networks consist of layers of interconnected nodes (neurons) that process information using weighted connection...

The practice of crafting and optimizing input prompts to guide AI language models toward desired outputs. Prompt engineering involves techniques like few-shot learning, chain-of-thought reasoning, and...

Retrieval-Augmented Generation: a technique that enhances AI language models by retrieving relevant information from external knowledge sources before generating a response. RAG combines the power of...

A deep learning architecture introduced in the 2017 paper "Attention Is All You Need" that relies on self-attention mechanisms instead of recurrence. Transformers are the foundation of modern LLMs lik...