AI search
AI search (also called AI-powered search, generative search, or an answer engine) is a class of search engine and search feature that uses large language models (LLMs) and generative AI to produce a direct
Artificial Intelligence
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Showing 1-24 of 24 articles
Agentic Context Engineering
Agentic Context Engineering (ACE) is a framework for scalable and efficient context adaptation in large language models (LLMs) that lets an AI system improve itself by treating its own context as an evolving
Claude Sonnet 4.5
Claude Sonnet 4.5 is a multimodal large language model (LLM) developed by Anthropic and released on September 29, 2025, which Anthropic described at launch as "the best coding model in the world." It is a…
Computer-use agent
A computer-use agent (CUA) is a category of AI agent in artificial intelligence that performs tasks by directly operating a general-purpose computer's graphical user interface (GUI) the way a human does, by…
Context window
A context window is the finite token sequence that a language model can process for one invocation.
ELIZA
ELIZA is the first widely known chatbot, a natural language processing program written by Joseph Weizenbaum at the Massachusetts Institute of Technology (MIT) between 1964 and 1967 and described in a January…
Grounding (artificial intelligence)
Grounding in artificial intelligence is the process of anchoring an AI system's outputs to verifiable
HotpotQA
HotpotQA is a large-scale, multi-hop question answering dataset of about 112,779 crowd-authored question-and-answer pairs over English Wikipedia, whose answers cannot be found in any single paragraph and…
Large Language Model
A large language model (LLM) is an artificial intelligence system built on a transformer neural network with billions to trillions of parameters, trained on massive text corpora to predict the next token in a…
Latent Dirichlet allocation
Latent Dirichlet allocation (LDA) is a generative probabilistic model that discovers the hidden thematic structure in a collection of documents by treating each document as a mixture of a small number of…
MTEB (Massive Text Embedding Benchmark)
MTEB, short for Massive Text Embedding Benchmark, is the standard public leaderboard for evaluating text embedding models across many task types at once.
Machine Translation
Machine translation (MT) is the automatic translation of text or speech from one human language into another.
MathArena
MathArena is a public, continuously updated leaderboard and evaluation platform that measures the performance of large language models on mathematics competition problems released after each model's training…
Meta Prompting
Meta prompting (also spelled meta-prompting) is an advanced prompt engineering technique where large language models (LLMs) are used to generate, refine, critique, select, or optimize prompts for themselves or…
NLU
Natural Language Understanding (NLU) is the subfield of artificial intelligence and natural language processing that turns unstructured human language into structured representations a computer can act on…
Natural Language Processing
Natural language processing (NLP) is the study and development of computational methods for analyzing, representing, retrieving, transforming, and generating human language.
OCR Models
OCR Models are artificial intelligence (AI) systems that convert images of typed, handwritten, or printed text into machine-readable digital text through Optical Character Recognition (OCR).
Post-training
Post-training is the stage of large language model (LLM) development that comes after pre-training and turns a raw, general-purpose base model into an aligned, instruction-following AI assistant.
Pre-training
Pre-training is a stage of machine learning in which a model learns parameters from a source dataset or source objective before those parameters are reused or adapted for a target use.
SimpleBench
SimpleBench is a text-only benchmark for large language models created by Philip, the host of the AI Explained YouTube channel, with collaborator Hemang.
Structured output
Structured output is a set of techniques and API features that constrain a large language model (LLM) to emit responses that exactly conform to a predefined format or schema, such as JSON, XML, or a custom…
Supervised fine-tuning
Supervised fine-tuning (SFT) is supervised training applied to a model that has already been trained.
Text-to-Speech
Text-to-speech (TTS) refers to artificial intelligence systems that convert written text into natural-sounding spoken audio.
Tool use
Tool use in artificial intelligence is the ability of a model-based system to request, coordinate, and use capabilities outside the model's ordinary token-generation process.