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.
By Benjamin Fresz, Vincent Philipp G\"obels, Safa Omri, Danilo Brajovic, Andreas Aichele, Janika Kutz, Jens Neuh\"uttler, Marco F. Huber
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.
By Jan Novacek, Ali Ahari, Tobias M\"uller, Sebastian Reiter, Alexander Viehl, Oliver Bringmann