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1. Patch the Planet: a Daybreak initiative to support open source maintainers

   OpenAI introduces Patch the Planet, a Daybreak initiative helping open-source maintainers find, validate, and fix vulnerabilities with AI and expert review.

2. Daybreak: Tools for securing every organization in the world

   OpenAI introduces new Daybreak tools, including Codex Security and GPT-5.5-Cyber, to help organizations find, validate, and patch vulnerabilities at scale.

3. Codex-maxxing for long-running work

   Learn how Jason Liu uses Codex to preserve context, manage complex projects, and help work continue beyond a single prompt.

4. Samsung Electronics brings ChatGPT and Codex to employees

   Samsung Electronics deploys ChatGPT Enterprise and Codex to employees worldwide, marking one of OpenAI’s largest enterprise AI rollouts.

5. New usage analytics and updated spend controls for enterprises

   OpenAI introduces new spend controls and usage analytics for ChatGPT Enterprise, helping organizations manage costs and scale AI with confidence.

6. Improving health intelligence in ChatGPT

   Learn how GPT-5.5 Instant improves ChatGPT’s health and wellness responses with stronger reasoning, better context, clearer communication, and physician-informed evaluations.

7. Using AI to help physicians diagnose rare genetic diseases affecting children

   Researchers used an OpenAI reasoning model to help diagnose rare diseases, identifying 18 new diagnoses in previously unsolved cases.

8. A near-autonomous AI chemist improves a challenging reaction in medicinal chemistry

   OpenAI and Molecule.one show how a near-autonomous AI chemist using GPT-5.4 improved a key drug-making reaction, advancing medicinal chemistry research.

9. Introducing LifeSciBench

   Introducing LifeSciBench, an expert-authored, expert-reviewed benchmark for evaluating how AI systems handle real-world life science research tasks and decisions.

10. Predicting model behavior before release by simulating deployment

    OpenAI introduces Deployment Simulation, a method to predict AI model behavior before deployment using real conversation data to improve safety and evaluation accuracy.