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The company behind ChatGPT and GPT-4
OpenAI is the AI safety company and research lab that created ChatGPT, GPT-4, DALL-E, Whisper, and the Sora video generator.
Intelligence Coverage
OpenAI is an American AI research company founded in December 2015 by Sam Altman, Elon Musk, Greg Brockman, and others. Its mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. OpenAI created the GPT series of language models, ChatGPT, DALL-E image generator, Whisper speech recognition, Codex for programming, and Sora for video generation. It is one of the most influential and well-funded AI companies in history, valued at over $150 billion.
ChatGPT — world's most popular AI chatbot
GPT-4o — flagship multimodal model
DALL-E 3 — image generation
Sora — AI video generation
Whisper — speech-to-text
OpenAI API for developers
Custom GPTs
Enterprise solutions
Anthropic
Anthropic
Anthropic is an AI safety company founded by former OpenAI researchers, best known for creating the Claude AI assistant family.
Google AI
Google / Alphabet
Google AI encompasses DeepMind, Google Research, and the teams building Gemini, Google Search AI features, and AI-powered Workspace tools.
xAI
xAI
xAI is Elon Musk's AI company that created Grok, an AI assistant integrated into X (formerly Twitter) with real-time web access.
OpenAI founded
by OpenAI
ChatGPT — world's most popular AI chatbot
GPT-4o — flagship multimodal model
DALL-E 3 — image generation
Sora — AI video generation
OpenAI today
Active platform with 11+ years of development
OpenAI Developer Forum
Official OpenAI community forum for developers building with the OpenAI API. Covers GPT-4o, Assistants API, fine-tuning, function calling, and ChatGPT integration questions. Monitored by OpenAI staff who respond to bugs and feature requests. Essential resource for OpenAI API developers.
OpenAI API
OpenAI's REST API provides access to GPT-4o, o3, DALL-E 3, Whisper, TTS, and Embeddings models. Features include Assistants API with tool use, Batch API for async workloads, fine-tuning, and structured outputs. The most widely used AI API with SDKs for Python, Node.js, and more.
OpenAI Cookbook
Official collection of example code, tutorials, and guides for working with the OpenAI API. Covers embeddings, fine-tuning, function calling, RAG, Assistants, batch processing, and production best practices. Maintained by OpenAI engineers with regular updates for new features.
RAG (Retrieval-Augmented Generation)
A technique that combines a language model with real-time document retrieval to produce grounded, up-to-date answers.
MCP (Model Context Protocol)
An open standard by Anthropic that lets AI assistants connect to external tools, data sources, and services through a unified protocol.
Agentic AI
AI systems that can autonomously plan, take multi-step actions, use tools, and achieve goals without step-by-step human instruction.
Vector Database
A database purpose-built to store and query high-dimensional vector embeddings, enabling semantic similarity search at scale.
Fine-Tuning
Training a pre-trained language model on a smaller, task-specific dataset to improve its performance on a particular domain or task.
Embeddings
Dense numerical vector representations of text, images, or other data that capture semantic meaning in a form machines can compare.
Prompt Engineering
The discipline of designing and refining input prompts to elicit more accurate, reliable, and useful responses from AI language models.
LLM (Large Language Model)
A deep learning model trained on vast quantities of text that can generate, summarise, translate, and reason about language at human level or above.
AI Intelligence Review
DeepAITool Editorial TeamLast Updated
Jun 2, 2026
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