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How countries can end the capability overhang
Our latest report reveals stark differences in advanced AI adoption across countries and outlines new initiatives to help nations capture productivity gains from AI.
Datadog uses Codex for system-level code review
OpenAI and Datadog brand graphic with the OpenAI wordmark on the left, the Datadog logo on the right, and a central abstract brown fur-like texture panel on a white background.
Continuously hardening ChatGPT Atlas against prompt injection
OpenAI is strengthening ChatGPT Atlas against prompt injection attacks using automated red teaming trained with reinforcement learning. This proactive discover-and-patch loop helps identify novel exploits early and harden the browser agent’s defenses as AI becomes more agentic.
Evaluating chain-of-thought monitorability
OpenAI introduces a new framework and evaluation suite for chain-of-thought monitorability, covering 13 evaluations across 24 environments. Our findings show that monitoring a model’s internal reasoning is far more effective than monitoring outputs alone, offering a promising path toward scalable control as AI systems grow more capable.
Deepening our collaboration with the U.S. Department of Energy
OpenAI and the U.S. Department of Energy have signed a memorandum of understanding to deepen collaboration on AI and advanced computing in support of scientific discovery. The agreement builds on ongoing work with national laboratories and helps establish a framework for applying AI to high-impact research across the DOE ecosystem.
The state of enterprise AI
A data-driven look at enterprise AI adoption, showing how organizations move from experimentation to real productivity gains and new capabilities.
Evaluating AI’s ability to perform scientific research tasks
OpenAI introduces FrontierScience, a benchmark testing AI reasoning in physics, chemistry, and biology to measure progress toward real scientific research.
Measuring AI’s capability to accelerate biological research
OpenAI introduces a real-world evaluation framework to measure how AI can accelerate biological research in the wet lab. Using GPT-5 to optimize a molecular cloning protocol, the work explores both the promise and risks of AI-assisted experimentation.
Strengthening cyber resilience as AI capabilities advance
OpenAI is investing in stronger safeguards and defensive capabilities as AI models become more powerful in cybersecurity. We explain how we assess risk, limit misuse, and work with the security community to strengthen cyber resilience.
The state of enterprise AI
Key findings from OpenAI’s enterprise data show accelerating AI adoption, deeper integration, and measurable productivity gains across industries in 2025.
How confessions can keep language models honest
OpenAI researchers are testing “confessions,” a method that trains models to admit when they make mistakes or act undesirably, helping improve AI honesty, transparency, and trust in model outputs.
Mixpanel security incident: what OpenAI users need to know
OpenAI shares details about a Mixpanel security incident involving limited API analytics data. No API content, credentials, or payment details were exposed. Learn what happened and how we’re protecting users.
GPT-5 and the future of mathematical discovery
UCLA Professor Ernest Ryu and GPT-5 solved a key question in optimization theory, showcasing AI’s role in accelerating mathematical discovery.
Early experiments in accelerating science with GPT-5
OpenAI introduces the first research cases showing how GPT-5 accelerates scientific progress across math, physics, biology, and computer science. Explore how AI and researchers collaborate to generate proofs, uncover new insights, and reshape the pace of discovery.
Strengthening our safety ecosystem with external testing
OpenAI works with independent experts to evaluate frontier AI systems. Third-party testing strengthens safety, validates safeguards, and increases transparency in how we assess model capabilities and risks.
Understanding neural networks through sparse circuits
OpenAI is exploring mechanistic interpretability to understand how neural networks reason. Our new sparse model approach could make AI systems more transparent and support safer, more reliable behavior.
Understanding prompt injections: a frontier security challenge
Prompt injections are a frontier security challenge for AI systems. Learn how these attacks work and how OpenAI is advancing research, training models, and building safeguards for users.
Introducing IndQA
OpenAI introduces IndQA, a new benchmark for evaluating AI systems in Indian languages. Built with domain experts, IndQA tests cultural understanding and reasoning across 12 languages and 10 knowledge areas.
gpt-oss-safeguard technical report
gpt-oss-safeguard-120b and gpt-oss-safeguard-20b are two open-weight reasoning models post-trained from the gpt-oss models and trained to reason from a provided policy in order to label content under that policy. In this report, we describe gpt-oss-safeguard’s capabilities and provide our baseline safety evaluations on the gpt-oss-safeguard models, using the underlying gpt-oss models as a baseline. For more information about the development and architecture of the underlying gpt-oss models, see the original gpt-oss model model card.
Advancing organizational transformation for business innovation
DNP rolled out ChatGPT Enterprise across ten core departments, achieving 95% faster patent research, 10x processing volume, 87% automation, and 70% knowledge reuse in three months.