A large language model (LLM) is a neural network trained on vast text to predict the next token — enabling chat, summarization, classification, and code generation via API or on-device models.

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AI & LLMs

GPT-4o

GPT-4o is an AI and LLM concept for building multimodal features on OpenAI's GPT-4o model family so product teams ship reliable intelligence features faster.

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AI & LLMs

Claude Model

Claude Model is an AI and LLM concept for integrating Anthropic Claude models for long-context and safety-sensitive tasks so product teams ship reliable intelligence features faster.

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AI & LLMs

Gemini Model

Gemini Model is an AI and LLM concept for calling Google Gemini models for text, code, and vision workloads so product teams ship reliable intelligence features faster.

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AI & LLMs

OpenAI API

OpenAI API is an AI and LLM concept for accessing OpenAI models through authenticated HTTP APIs from your backend so product teams ship reliable intelligence features faster.

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AI & LLMs

Chat Completions API

Chat Completions API is an AI and LLM concept for sending role-based message arrays to generate assistant replies so product teams ship reliable intelligence features faster.

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AI & LLMs

Responses API OpenAI

Responses API OpenAI is an AI and LLM concept for using OpenAI's Responses API for stateful agent-style interactions so product teams ship reliable intelligence features faster.

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AI & LLMs

Assistants API

Assistants API is an AI and LLM concept for managing persistent assistants with files, tools, and thread history so product teams ship reliable intelligence features faster.

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AI & LLMs

Guide

Embeddings Model

An embeddings model converts text into a numeric vector so similar meanings sit close together — powering semantic search, recommendations, and RAG retrieval.

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AI & LLMs

Vector Embedding

Vector Embedding is an AI and LLM concept for representing meaning as numeric vectors for nearest-neighbor lookup so product teams ship reliable intelligence features faster.

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AI & LLMs

Semantic Search

Semantic Search is an AI and LLM concept for finding content by meaning rather than exact keyword overlap so product teams ship reliable intelligence features faster.

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AI & LLMs

Guide

RAG Retrieval Augmented Generation

Retrieval augmented generation (RAG) retrieves relevant snippets from your data, then asks an LLM to answer using that context — reducing hallucinations versus pure chat.

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AI & LLMs

Chunking Strategy RAG

Chunking Strategy RAG is an AI and LLM concept for splitting documents into retrieval-friendly segments with overlap and metadata so product teams ship reliable intelligence features faster.

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AI & LLMs

Vector Database

Vector Database is an AI and LLM concept for indexing embeddings for fast approximate nearest-neighbor search at scale so product teams ship reliable intelligence features faster.

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AI & LLMs

Pinecone

Pinecone is an AI and LLM concept for hosting managed vector indexes for RAG and recommendation workloads so product teams ship reliable intelligence features faster.

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