- OpenAI
ChatGPT for business just got better—with connectors to internal tools, MCP support, record mode SSO to Team, and flexible pricing for Enterprise
- Sora - OpenAI
We’re teaching AI to understand and simulate the physical world in motion, with the goal of training models that help people solve problems that require real-world interaction Introducing Sora, our text-to-video model Sora can generate videos up to a minute long while maintaining visual quality and adherence to the user’s prompt
- Introducing GPT-4o and more tools to ChatGPT free users
In line with our mission, we are focused on advancing AI technology and ensuring it is accessible and beneficial to everyone Today we are introducing our newest model, GPT‑4o, and will be rolling out more intelligence and advanced tools to ChatGPT for free
- Teaching with AI - OpenAI
Teaching with AI We’re releasing a guide for teachers using ChatGPT in their classroom—including suggested prompts, an explanation of how ChatGPT works and its limitations, the efficacy of AI detectors, and bias
- GPT-3 powers the next generation of apps - OpenAI
Over 300 applications are delivering GPT-3–powered search, conversation, text completion, and other advanced AI features through our API
- Creating an AI-powered Magic Studio | OpenAI
Building Magic Studio, an integrated AI suite Using the creative power of GPT‑4 to power several of the tools within Magic Studio : Magic Write (opens in a new window) is an AI writing tool powered by OpenAI's API
- New tools for building agents - OpenAI
Integrated observability tools (opens in a new window) to trace and inspect agent workflow execution These new tools streamline core agent logic, orchestration, and interactions, making it significantly easier for developers to get started with building agents
- MuseNet - OpenAI
We’ve created MuseNet, a deep neural network that can generate 4-minute musical compositions with 10 different instruments, and can combine styles from country to Mozart to the Beatles MuseNet was not explicitly programmed with our understanding of music, but instead discovered patterns of harmony, rhythm, and style by learning to predict the next token in hundreds of thousands of MIDI
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