OpenAI and Los Alamos National Laboratory Announce Research Partnership on Biosafety Evaluations
OpenAI and Los Alamos National Laboratory (LANL) have announced a research partnership focused on developing safety evaluations for frontier AI models. The collaboration specifically targets assessing and measuring biological capabilities and risks. LANL brings national-lab-level biosecurity expertise to the effort, which aligns with OpenAI's broader preparedness framework for catastrophic risk domains.
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OpenAI and Anthropic Share Findings from Joint Safety Evaluation
OpenAI and Anthropic conducted a first-of-its-kind cross-lab safety evaluation, testing each other's frontier models across dimensions including misalignment, instruction following, hallucinations, and jailbreaking resistance. The collaboration represents a novel form of inter-lab safety research cooperation. Findings highlight both progress and ongoing challenges in AI safety, and establish a potential template for future cross-organizational evaluations.
Preparing for future AI risks in biology
OpenAI has published a post outlining its proactive approach to assessing and mitigating biosecurity risks from advanced AI systems capable of biological applications. The piece describes capability evaluations and safeguards designed to prevent misuse of AI in biology and medicine. This reflects OpenAI's ongoing effort to get ahead of dual-use risks before capabilities reach dangerous thresholds.
OpenAI Expands External Safety Testing Ecosystem
OpenAI published a post describing its use of independent experts to evaluate frontier AI systems through third-party testing. The initiative aims to strengthen safety validation, verify safeguards, and increase transparency around capability and risk assessments. The announcement signals a continued push toward external accountability mechanisms for frontier model evaluation.
OpenAI publishes action plan for AI-powered biodefense and biological resilience
OpenAI released a policy and strategy document outlining an action plan for using AI to strengthen biodefense and biological resilience. The piece positions AI as a tool for countering biological threats at national and global scale. This represents OpenAI's public stance on a high-stakes dual-use domain where AI capabilities intersect with biosecurity policy.
Moving AI Governance Forward: OpenAI and Leading Labs Make Voluntary Safety Commitments
OpenAI and other leading AI laboratories announced voluntary commitments aimed at reinforcing AI safety, security, and trustworthiness. The commitments represent a coordinated industry response to governance concerns ahead of anticipated regulatory action. This move signals alignment among frontier labs on baseline safety standards, though the voluntary nature leaves enforcement questions open.
Strengthening America's AI Leadership with the U.S. National Laboratories
OpenAI has announced a partnership to deploy its latest reasoning models with U.S. National Laboratories, giving the nation's leading scientists access to frontier AI capabilities for scientific research. The collaboration positions OpenAI's reasoning model line as a tool for high-stakes government scientific work. This represents a significant enterprise and government deployment milestone for OpenAI's o-series reasoning models.
OpenAI proposes federal governance blueprint for frontier AI safety and national security
OpenAI published a policy blueprint calling for a U.S. federal framework to govern frontier AI, covering safety, resilience, and national security dimensions. The proposal outlines OpenAI's vision for democratic oversight of the most capable AI systems. As a tier-1 primary source from a leading lab, this represents a significant public policy position that will likely influence regulatory discussions.
Measuring AI's capability to accelerate biological research
OpenAI introduces a real-world evaluation framework designed to measure how AI systems can accelerate biological research in wet lab settings. The work uses GPT-5 to optimize a molecular cloning protocol as a concrete demonstration case. The framework explicitly addresses both the potential benefits and biosecurity risks of AI-assisted experimentation, positioning this as a dual-use capability assessment.