Today, we’re introducing Forge, a system for enterprises to build frontier-grade AI models grounded in their proprietary knowledge.
We’re forming a new industry body to promote the safe and responsible development of frontier AI systems: advancing AI safety research, identifying best practices and standards, and facilitating information sharing among policymakers and industry.
Why we're building Mistral AI.
arXiv:2408. 02379v2 Announce Type: replace-cross Abstract: Developing and certifying safe - or so-called trustworthy - AI has become an increasingly salient issue, especially in light of upcoming regulation such as the EU AI Act.
OpenAI shares guidance on third-party AI evaluations, covering how to assess model capabilities, safeguards, and validity for frontier systems.
As part of our Executive Function series, Model ML CEO Chaz Englander discusses how AI-native infrastructure and autonomous agents are transforming financial services workflows.
The paper introduces an ontology-supported platform designed to facilitate the exchange, usage, and analysis of AI models and datasets. It addresses the need for effective management of AI assets in industrial settings by providing a structured framework that reduces semantic gaps. A real‑time critical systems use case demonstrates the platform’s practical utility.
OpenAI’s B2B Signals research shows how frontier enterprises deepen AI adoption, scale Codex-powered agentic workflows, and build durable competitive advantage.
A data-driven look at enterprise AI adoption, showing how organizations move from experimentation to real productivity gains and new capabilities.
arXiv:2609.37109v1 Announce Type: cross Abstract: The rapid, unpredictable advancements in AI system capabilities has seen regulators take adaptive and experimental approaches to policymaking. Establ...
arXiv:2606. 15708v1 Announce Type: new Abstract: Welcome to the ninth edition of the AI Index report.