Llm Glossary

Browse 70 llm terms defined in plain English, from the cultural dictionary of computing.

70 Llm Terms

Adapter Layer
A small trainable module inserted into a larger pre-trained model for parameter-efficient adaptation. It influences how models are trained, evaluated, or...
Agentic Workflow
An AI system design where a language model autonomously plans, executes, and iterates on tasks using tools (code execution, web search, APIs) in a loop. Unlike...
AI Agent
An AI system that autonomously pursues goals by planning actions, executing tools (code, APIs, web browsing), observing results, and iterating. Unlike simple...
Causal Language Model
A language model trained to predict the next token using only preceding context. It influences how models are trained, evaluated, or served, and it can...
Chain of Thought Prompting
A prompting technique that encourages a model to produce intermediate reasoning steps before the final answer. It influences how models are trained, evaluated,...
Context Window
The maximum number of tokens (input + output) that a language model can process in a single interaction. Determines how much text the model can 'see' at once....
Context Window
The maximum amount of text (measured in tokens) that a language model can process in a single interaction. Everything the model can 'see' and 'remember' during...
DPO
Abbreviation for direct preference optimization, a preference-based fine-tuning method for language models. It influences how models are trained, evaluated, or...
Foundation Model
A large AI model pre-trained on broad data that can be adapted to a wide range of downstream tasks through fine-tuning or prompting. GPT-4, Claude, Llama —...
Function Calling
A model interaction pattern where the model emits structured arguments that a program routes to tools or APIs. It influences how models are trained, evaluated,...
Gemini
Google's family of multimodal AI models, succeeding the PaLM series, capable of processing and generating text, code, images, audio, and video. Gemini launched...
Gemma
A family of lightweight generative models released by Google for research and application development. It influences how models are trained, evaluated, or...
GPT-4
OpenAI's fourth-generation Generative Pre-trained Transformer, a large multimodal model capable of processing both text and images. Released in March 2023,...
GPT Architecture
The decoder-only transformer architecture used in the GPT family of autoregressive language models. It influences how models are trained, evaluated, or served,...
Groq
A company that designs custom AI inference chips (Language Processing Units, or LPUs) optimized for running large language models at extreme speed. Groq's...
Guardrails
Validation layers applied to AI model inputs and outputs to enforce safety, accuracy, and compliance constraints. Can include content filters, format...
Hallucination
Hallucination in artificial intelligence refers to a model generating content that is factually incorrect, fabricated, or nonsensical while presenting it with...
In-Context Learning
A model behavior where examples placed in the prompt shape predictions without updating model weights. It influences how models are trained, evaluated, or...
LangChain
An open-source framework for building applications powered by large language models. LangChain provides abstractions for chaining together LLM calls, tool...
Large Multimodal Model
A large model trained to understand or generate across multiple modalities such as text, image, or audio. It influences how models are trained, evaluated, or...
LLM Agent
LLM Agent is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models and research...
LLM Evaluation
LLM Evaluation is an evaluation concept used to measure model quality, robustness, or efficiency. It is commonly used for comparing systems before release or...
LLM Fine-Tuning
LLM Fine-Tuning is a stage of model optimization where weights or behaviors are adjusted from data or feedback. It is commonly used for foundation-model...
LLM Inference
LLM Inference is the phase where a trained model processes new inputs to produce predictions or generations. It is commonly used for production APIs, batch...
LLM Routing
LLM Routing is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models and...
LLM Safety
LLM Safety is a safety or governance control for limiting harmful, noncompliant, or insecure model behavior. It is commonly used for production AI systems that...
Local LLM
Local LLM is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models and research...
Long Context
Long Context is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models and...
LoRA
Low-Rank Adaptation — a parameter-efficient fine-tuning technique that freezes the pre-trained model weights and injects small trainable matrices (adapters)...
mixture of agents
An architecture where multiple LLM agents collaborate by having each agent process the outputs of others in iterative rounds, leveraging the phenomenon that...
Multimodal AI
AI systems that can process and generate multiple types of data — text, images, audio, video, and code — within a single model. GPT-4V, Claude 3, and Gemini...
Multimodal Tokenizer
Multimodal Tokenizer is a unit or control marker used when text is segmented and generated by language models. It is commonly used for prompt assembly,...
Ollama
A tool for running large language models locally on personal hardware. Ollama packages model weights, configuration, and a runtime into a simple command-line...
OpenAI
OpenAI is an AI company and research lab that develops foundation models, developer APIs, and products such as ChatGPT. It is commonly used for building...
Output Token
Output Token is a unit or control marker used when text is segmented and generated by language models. It is commonly used for prompt assembly, decoding...
Pair Programming (AI)
Using an AI coding assistant (GitHub Copilot, Cursor, Claude) as a real-time programming partner that suggests code, explains errors, and generates...
PII Detection
PII Detection is a safety or governance control for limiting harmful, noncompliant, or insecure model behavior. It is commonly used for production AI systems...
Prompt Caching
Prompt Caching is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat systems,...
Prompt Chaining
Prompt Chaining is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat systems,...
Prompt Engineering
The practice of crafting input text (prompts) to elicit desired outputs from a language model. Part art, part science, part dark magic. Ranges from 'please be...
Prompt Engineering Detail
Prompt Engineering Detail is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat...
Prompt Injection
An attack where malicious instructions are embedded in user input to override an LLM's system prompt or instructions. Direct injection modifies the prompt...
Prompt Injection Detail
Prompt Injection Detail is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat...
Prompt Template
Prompt Template is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat systems,...
Prompt Tuning
Prompt Tuning is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat systems,...
Responsible AI
Responsible AI is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models and...
Retrieval-Augmented Generation
An architecture that improves LLM outputs by first retrieving relevant documents from an external knowledge base, then including them in the prompt as context....
Rubber Duck (AI)
Using an LLM as a rubber duck — explaining your bug to ChatGPT or Claude instead of a plastic duck. The AI actually responds, which is either more helpful or...
Safety Classifier
Safety Classifier is a safety or governance control for limiting harmful, noncompliant, or insecure model behavior. It is commonly used for production AI...
Safety Filter
Safety Filter is a safety or governance control for limiting harmful, noncompliant, or insecure model behavior. It is commonly used for production AI systems...
Stop Token
Stop Token is a unit or control marker used when text is segmented and generated by language models. It is commonly used for prompt assembly, decoding control,...
Structured Output
Constraining an LLM's output to conform to a specific format like JSON Schema, XML, or a grammar. Achieved through guided decoding (constraining token...
Subword Tokenization
Subword Tokenization is a unit or control marker used when text is segmented and generated by language models. It is commonly used for prompt assembly,...
Super Alignment
Super Alignment is a safety or governance control for limiting harmful, noncompliant, or insecure model behavior. It is commonly used for production AI systems...
system prompt
System prompt is the initial set of instructions given to a large language model (LLM) that defines its behavior, personality, constraints, and capabilities...
System Prompt Detail
System Prompt Detail is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat...
Temperature
A parameter that controls the randomness of a language model's output. Low temperature (near 0) makes outputs deterministic and conservative; high temperature...
Temperature
A parameter that controls the randomness of a language model's output. Lower temperatures (0.0–0.3) make outputs more deterministic and focused; higher...
Token
The basic unit of text that a language model processes — roughly 3/4 of an English word on average. Text is split into tokens by a tokenizer before being fed...
Token Budget
Token Budget is a unit or control marker used when text is segmented and generated by language models. It is commonly used for prompt assembly, decoding...
Tokenization Detail
Tokenization Detail is a unit or control marker used when text is segmented and generated by language models. It is commonly used for prompt assembly, decoding...
Token Limit
Token Limit is a unit or control marker used when text is segmented and generated by language models. It is commonly used for prompt assembly, decoding...
tokens per second
The standard throughput metric for language model inference, measuring how many tokens a model can generate per second. Higher TPS enables more responsive user...
Tokens Per Second Detail
Tokens Per Second Detail is a unit or control marker used when text is segmented and generated by language models. It is commonly used for prompt assembly,...
tool use
The capability of a language model to invoke external functions, APIs, or services during response generation. Rather than relying solely on its training data,...
Tool Use
The ability of an LLM to invoke external tools (functions, APIs, databases, code interpreters) to accomplish tasks beyond text generation. The model decides...
Value Alignment
Value Alignment is a safety or governance control for limiting harmful, noncompliant, or insecure model behavior. It is commonly used for production AI systems...
Vibe Coding
Vibe Coding is a software development approach where the programmer describes what they want in natural language and lets an AI assistant generate the actual...
Zero-Shot Learning
The ability of a model to perform a task it was never explicitly trained on, by leveraging its general knowledge. GPT answering questions about a topic it...
Zero-Shot Prompting
Zero-Shot Prompting is a prompting technique or prompt-side control used to shape large-model behavior at inference time. It is commonly used for chat systems,...

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