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OpenAI and AWS announced a multi-year strategic partnership agreement worth $38 billion. AWS will provide infrastructure and compute to support OpenAI's next-generation models, expanding its advanced AI workloads.
Why it was selectedThe agreement amount and multi-year arrangement are relatively large among similar compute partnerships and can be used to observe the compute supply landscape for frontier models.
OpenAI released the Teen Safety Blueprint, providing a roadmap for building AI responsibly, covering safety measures, age-appropriate design, and collaboration with various parties, with the goal of protecting and empowering teenagers online.
OpenAI stated that AI is advancing rapidly, and humanity has the opportunity to steer this progress toward scientific discovery, safety, and a future that benefits everyone, and offered relevant recommendations regarding AI progress.
OpenAI views prompt injection as a frontier safety challenge for AI systems and explains how such attacks work. OpenAI says it is advancing related research, strengthening protections in trained models, and building guardrails for users.
OpenAI has upgraded the GPT-5 series to GPT-5.1, saying the new model is gentler and more capable, and has added new ways to customize ChatGPT's tone and style. GPT-5.1 has begun rolling out to paid users.
OpenAI has released a GPT-5 System Card supplement, providing updated safety metrics for GPT-5.1 Instant and GPT-5.1 Thinking, and adding evaluations on mental health and emotional dependence. This supplement is a companion document to the GPT-5 System Card.
Why it was selectedThe supplement provides new evaluations of both GPT-5.1 versions on mental health and emotional dependence, which can be read alongside GPT-5's original safety metrics.
OpenAI says it is pushing back against The New York Times' request to hand over 20 million private ChatGPT conversations, and is accelerating new safety and privacy protections to safeguard user data.
OpenAI says it is exploring mechanistic interpretability to understand how neural networks reason, and has proposed a new sparse model approach. OpenAI says the approach could make AI systems more transparent and support safer, more reliable behavior.
OpenAI released the System Card for GPT-5.1-Codex-Max, its new frontier agentic coding model, which OpenAI says is its first model natively trained with compaction, able to coherently process millions of tokens across multiple context windows in a single task. The model was evaluated under OpenAI's Preparedness Framework. It is highly capable in cybersecurity but does not reach High capability, and OpenAI expects the trend of rapid capability improvement to continue, with a model crossing that threshold in the near term. In the biological domain it is treated as High capability, using the same safeguards as GPT-5. AI self-improvement did not reach High. Mitigations include model-level measures such as dedicated safety training against harmful tasks and prompt injection, as well as product-level measures such as the Agent sandbox and configurable network access.
Why it was selectedThe System Card states that the model does not reach High capability in cybersecurity and is treated as High in the biological domain, and lists mitigations such as the Agent sandbox and prompt injection protection.
OpenAI has launched GPT-5.1-Codex-Max, a frontier agentic coding model, now available in Codex's CLI, IDE extension, cloud, and code review, with API access coming soon. The model is built on an update to the reasoning model and is OpenAI's first model trained natively with compaction across multiple context windows, allowing it to coherently process millions of tokens in a single task; in internal evaluations it has worked for over 24 hours continuously. On SWE-bench Verified, it performs better than GPT-5.1-Codex at medium reasoning effort, with 30% fewer thinking tokens, and adds an xhigh reasoning effort. On safety, Codex runs in a sandbox by default, with file writes limited to the workspace and network access off by default; enabling internet or web search introduces prompt injection risk. Under its Preparedness Framework, the model's cybersecurity capability has not reached High, but it is the strongest cybersecurity model it has deployed.
OpenAI 提出一套面向企业的 evals 实践框架，按 Specify、Measure、Improve 三步衡量并改进 AI 系统表现。框架建议由技术与领域专家组成小团队定义成功标准、建立 golden set，在贴近真实条件的测试环境中评测并持续改进。OpenAI 称其内部团队已为具体产品和内部工作流创建数十个 contextual evals，并建议使用 LLM grader 时保留人工审核。
OpenAI 发布博客，说明其如何借助第三方外部测试评估前沿模型，并公开相关协作与保密条款。外部评估分为三类：独立实验室评测、方法论评审和领域专家（SME）探测。GPT-5 的外部评估覆盖长时程自主、谋划与欺骗、湿实验室规划可行性和攻击性网络安全，包含 METR 的时间跨度评测和 SecureBio 的 VCT；gpt-oss 则用对抗微调估计最坏情况能力，并邀请第三方评审方法。OpenAI 称会按需提供敏感访问，包括思维链访问以识别故意藏拙或谋划，并向所有评估方付费，且付费不与评估结果挂钩。
OpenAI 公布 GPT-5 在加速科学研究方面的早期实验，尝试用 GPT-5 推进科研工作。
OpenAI 介绍如何在软件开发生命周期各阶段使用 Codex。
OpenAI disclosed a Mixpanel security incident involving limited API analytics data. OpenAI stated that the incident did not expose API content, credentials, or payment details, and described the user protection measures it is taking.
OpenAI will award up to $2 million to fund new research at the intersection of AI and mental health. The program supports projects studying real-world risks, benefits, and applications, with the goal of improving safety and well-being.
OpenAI will acquire Neptune to deepen visibility into model behavior and strengthen the tools researchers use to track experiments and monitor training.
OpenAI researchers are testing a method called confessions, training models to proactively admit when they make mistakes or behave inappropriately, with the goal of improving AI honesty, transparency, and trust in model outputs.
OpenAI co-founded the Agentic AI Foundation under the Linux Foundation and donated AGENTS.md to the foundation to support open, interoperable standards for safe agentic AI.
Why it was selectedOpenAI co-founded the Agentic AI Foundation and donated AGENTS.md; you can learn about the institutional arrangements for agent safety standards.
OpenAI is increasing investment to strengthen safety protections and defenses in response to AI models' growing capabilities in cybersecurity. The company explained how it assesses risks, limits model misuse, and collaborates with the security community, with the goal of improving overall cyber resilience.
OpenAI updated the GPT-5 System Card to include GPT-5.2, the latest model family in the GPT-5 series. The update notes that the comprehensive safety mitigation approach taken by GPT-5.2 is broadly consistent with that described in the GPT-5 System Card and the GPT-5.1 System Card. Like other OpenAI models, GPT-5.2's training data comes from publicly available internet information, information obtained through partnerships with third parties, and information provided or generated by users or human trainers and researchers.
Why it was selectedThe System Card update explains that GPT-5.2 continues to use the safety mitigation approach of GPT-5 and GPT-5.1, and describes the training data sources, allowing an understanding of the safety posture of the series.
OpenAI releases GPT-5.2, calling it the most advanced frontier model for everyday professional work. The model achieves state-of-the-art performance in reasoning, long-context understanding, coding, and vision, and is available in ChatGPT and the OpenAI API to support faster, more reliable agent workflows.
Why it was selectedOpenAI announced the capability positioning and access points for GPT-5.2, providing insight into the update direction for professional work and agentic workflows.
OpenAI states that GPT-5.2 is currently its strongest model in mathematics and science, achieving new best results on benchmarks such as GPQA Diamond and FrontierMath. The article says these improvements have translated into actual research progress, including solving an open theoretical problem and generating reliable mathematical proofs.
OpenAI released a real-world evaluation framework for measuring AI's ability to accelerate wet-lab biological research. The work used GPT-5 to optimize molecular cloning protocols, while also exploring the potential and risks of AI-assisted experimentation.
Why it was selectedOpenAI used GPT-5 to optimize molecular cloning protocols, providing a real-world evaluation framework for wet-lab biological research capabilities that can inform biosecurity assessments.
OpenAI launches the FrontierScience benchmark to evaluate AI's reasoning abilities in physics, chemistry, and biology, measuring model progress on real scientific research tasks. The benchmark targets scientific reasoning, covering three areas—physics, chemistry, and biology—and is used to track how far AI has advanced toward actual scientific research.
OpenAI released the GPT-5.2 System Card appendix, describing the safety measures and capability evaluations for GPT-5.2-Codex. GPT-5.2-Codex is an agentic coding model for Codex that improves long-horizon tasks through context compression, performs better on project-level tasks such as refactoring and migration and on Windows environments, and shows significantly improved cybersecurity capabilities. Under the Preparedness Framework evaluation, it is highly capable in cybersecurity but does not reach the High threshold; OpenAI expects the model to cross that threshold in the near future. In the biological domain it is treated as High capability, using the corresponding safeguards from the GPT-5 family, and AI self-improvement did not reach High. Safeguards include specialized safety training against harmful tasks and prompt injection, as well as product-level measures such as agent sandboxing and configurable network access.
Why it was selectedThe System Card gives the Preparedness Framework determinations for GPT-5.2-Codex in cybersecurity and biological capabilities, and lists model-level and product-level safeguards.
OpenAI releases the programming model GPT-5.2-Codex and calls it the company's most advanced programming model. The model focuses on long-horizon reasoning, large-scale code transformation, and enhanced cybersecurity capabilities.
OpenAI updated the Model Spec, adding principles for users under 18, specifying how ChatGPT should support teens in a safe, age-appropriate, and developmentally science-based manner. This update strengthens guardrails, clarifies expected model behavior in high-risk situations, and continues its existing work on teen safety in ChatGPT.
OpenAI releases new AI literacy resources to help teenagers and parents use ChatGPT more thoughtfully, safely, and confidently. The guide includes expert-reviewed advice covering responsible use, critical thinking, healthy boundaries, and how to support teens dealing with emotional or sensitive topics.
OpenAI signed a memorandum of understanding with the U.S. Department of Energy to deepen cooperation in AI and advanced computing to support scientific discovery. The agreement builds on existing work between the two sides and the national laboratories, and establishes a framework for applying AI to high-impact research within the DOE ecosystem.
OpenAI introduces a new framework and evaluation suite for chain-of-thought monitorability, covering 13 evaluations and 24 environments. OpenAI says monitoring a model's internal reasoning is more effective than monitoring outputs alone, offering a promising path toward scalable control as AI systems become more capable.
Why it was selectedOpenAI provides a chain-of-thought monitorability framework covering 13 evaluations and 24 environments, which teams researching reasoning monitoring and scalable control can reference.
OpenAI says it is hardening ChatGPT Atlas with automated red teaming trained via reinforcement learning to defend against prompt injection attacks. This proactive loop of discovering and patching vulnerabilities is designed to identify new attack techniques early and to continuously strengthen the browser agent's defenses as AI agent capabilities increase.
Why it was selectedOpenAI disclosed that an automated red team trained with reinforcement learning continuously discovers and patches prompt injection vulnerabilities in Atlas, and the browser agent team can refer to this discovery-and-patching loop.
A Tech Policy Press review summarizes three new papers examining how AI sycophancy (models sacrificing truthfulness to agree with users) is evaluated and its impact on users. The arXiv paper SycEval reports that 58.19% of conversations in its sample exhibit sycophantic behavior, with Gemini highest (62.47%) and ChatGPT lowest (56.71%), and notes that cited rebuttals most easily trigger regression-type sycophancy, and on the medical advice dataset MedQuad, models often agree with incorrect user beliefs and give dangerous or misleading medical advice. Another study testing 11 models found they affirm user behavior 50% more than humans; in two pre-registered experiments (N=1604), participants exposed to sycophantic models felt more correct and were less willing to fix conflicts. A third study showed that interacting with sycophantic chatbots increased stance extremity by 2.68 percentage points and stance certainty by 4.04 percentage points, with the author arguing that polarization mainly comes from selective presentation of supportive facts.
A Tech Policy Press article analyzes the personalization and manipulation risks brought by long-term memory in AI systems, and proposes mitigations such as transparency and informed consent. The article compares implementation differences across companies: OpenAI launched editable saved memory in February 2024, and expanded it in April 2025 to reference all past conversations; Google introduced memory for Gemini in February 2025, and added personalization in March; xAI and Anthropic followed in April and August 2025, respectively. The article cites a 2024 University of Zurich experiment on r/ChangeMyView, saying personalization made AI persuasion up to 6 times greater than human-written messages. The author notes that memory is often on by default, making informed consent difficult for users, and mentions Meta AI posting private prompts to the Discover feed, as well as the lawsuit over the suicide of 16-year-old Adam Raine, which alleged the memory feature hoarded his personal details. The author recommends increasing transparency, implementing informed consent, and adopting designs such as project-specific memory.
The AI Disclosures Project argues for bringing AI into the securities disclosure regime, holding that AI risks stem from market competition rather than an out-of-control superintelligence. Its recommendations include closing the loophole that lets companies bypass public filings through privatization, having the SEC issue AI disclosure guidance defining material AI events, writing AI incidents into 8-K and 10-K filings by reference to the 2023 cybersecurity rules, and strengthening enforcement against AI washing and fraud.
Organizations such as Public Citizen are urging OMB to suspend and withdraw the federal government's deployment of xAI's Grok, saying it violates the government's own AI safety and neutrality rules. GSA has made Grok available to federal agencies, and Executive Order 14319 and OMB memoranda M-25-21 and M-25-22 require the decommissioning of noncompliant AI, yet Grok has previously output Holocaust denial, climate disinformation, and antisemitic and racist content.
AI crawlers are turning the internet into a haunted house: crawlers deployed by companies such as OpenAI and Anthropic systematically scrape content across the web, yet traffic barely flows back to the original sites. Some estimates put the global monthly decline in search engine traffic at 15%, while other claims approach 35%; media outlets such as The Wall Street Journal have seen traffic drops of more than 25%; a study by the Dutch consumer protection association found that nearly one-third of Google's AI summaries contain errors.
OpenAI launched ChatGPT Health, combining users' health information with ChatGPT. Health conversations are stored separately and are not used to train foundation models. Users can connect medical records and health apps such as Apple Health. Medical record integration and some apps are limited to the U.S. OpenAI says more than 230 million people ask health questions on ChatGPT each week, and the product is not used for diagnosis or treatment.
Netomi distilled three lessons for scaling agentic systems into the enterprise: GPT-4.1 handles low-latency tool calls, GPT-5.2 handles multi-step planning, and both run inside a governed execution layer. Its concurrency framework maintained sub-3-second responses and 98% intent classification accuracy during DraftKings event traffic peaks exceeding 40,000 concurrent customer requests per second. The governance layer includes inline schema validation, policy enforcement, PII protection, deterministic fallback, and runtime observability.
OpenAI releases a new RFP aimed at strengthening the U.S. AI supply chain by accelerating domestic manufacturing, creating jobs, and expanding AI infrastructure.