GPT-3 powers the next generation of apps
Over 300 applications are delivering GPT-3–powered search, conversation, text completion, and other advanced AI features through our API.
We’re testing SearchGPT, a temporary prototype of new search features that give you fast and timely answers with clear and relevant sources.
Over 300 applications are delivering GPT-3–powered search, conversation, text completion, and other advanced AI features through our API.
Scout24 has created a GPT-5 powered conversational assistant that reimagines real-estate search, guiding users with clarifying questions, summaries, and tailored listing recommendations.
Search Toolkit is a composable framework for building production search pipelines for AI applications.
The retrieval layer that helps AI systems navigate, read, and verify information inside even the most complex documents
We’re launching a pilot subscription plan for ChatGPT, a conversational AI that can chat with you, answer follow-up questions, and challenge incorrect assumptions.
Get fast, timely answers with links to relevant web sources
OpenAI plans to test advertising in the U. S.
Learn how startups use GPT-5. 6 to build faster, more cost-efficient AI agents with smarter model selection and new Responses API capabilities.
The study examines how conversational LLM agents—specifically ChatGPT, Claude, Grok, and DeepSeek—use Web search, combining real user interactions with controlled API experiments. It finds that agents differ in when they decide to search, how they craft queries, and which domains they favor, and that more frequent searching does not always improve answer quality. While most responses are grounded in search results, some claims are unsupported, raising attribution concerns.
Learn how to use ChatGPT, start your first conversation, and discover simple ways to write, brainstorm, and solve problems with AI.
Context engineering has emerged as a primary lever for improving AI systems without parameter updates. Recent work showing that textual gradients do not function as real gradients motivates treating automatic prompt optimization (APO) as black-box search.