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Compliance API integrations, SCIM, and GPT controls to support compliance programs, data security, and user access at scale
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Discover how prover-verifier games improve the legibility of language model outputs, making AI solutions clearer, easier to verify, and more trustworthy for both humans and machines.
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OpenAI and Los Alamos National Laboratory are working to develop safety evaluations to assess and measure biological capabilities and risks associated with frontier models.
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CriticGPT, a model based on GPT-4, writes critiques of ChatGPT responses to help human trainers spot mistakes during RLHF
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We’re partnering with TIME and its 101 years of archival content to enhance responses and provide links to stories on Time.com
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Highlighting innovative research and AI integration in cybersecurity
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We present a holistic approach to building a robust and useful natural language classification system for real-world content moderation.
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Consistency models are a nascent family of generative models that can sample high quality data in one step without the need for adversarial training.
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Diffusion models have significantly advanced the fields of image, audio, and video generation, but they depend on an iterative sampling process that causes slow generation.
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Paf adopted ChatGPT Enterprise across its entire company, with engineers using custom GPTs on a daily basis to speed up routine development tasks. Paf also integrated ChatGPT Enterprise into the grit:...
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Color Health is working with OpenAI to pioneer a new way of accelerating cancer patients’ access to treatment. Their new Cancer Copilot application uses GPT-4o to identify missing diagnostics and cr...
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Nakasone brings cybersecurity experience to growing Board of Directors; will join the Board’s Safety and Security Committee
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OpenAI and Apple announce partnership to integrate ChatGPT into Apple experiences.
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OpenAI welcomes Sarah Friar (CFO) and Kevin Weil (CPO)
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Exploring the technology behind our text-to-speech model.
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Using new techniques for scaling sparse autoencoders, we automatically identified 16 million patterns in GPT-4's computations.
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We outline our architecture that supports the secure training of frontier models.