Nemotron 3.5 Content Safety: Customizable Multimodal Safety for Global Enterprise AI
Read the original on Hugging Face Blog →The Flow has not summarised this story yet — read it at Hugging Face Blog.
The Flow has not summarised this story yet — read it at Hugging Face Blog.
Artificial general intelligence has the potential to benefit nearly every aspect of our lives—so it must be developed and deployed responsibly.
Ensuring that AI systems are built, deployed, and used safely is critical to our mission.
We describe our latest thinking in the hope of helping other AI developers address safety and misuse of deployed models.
arXiv:2609.05749v1 Announce Type: new Abstract: Work on the risks of artificial intelligence has focused predominantly on capability risk: the danger that systems become too powerful, too autonomous,...
arXiv:2609.20850v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) show remarkable advancements, their cross-modal capabilities introduce complex vulnerabilities that easi...
We’ve written a policy research paper identifying four strategies that can be used today to improve the likelihood of long-term industry cooperation on safety norms in AI: communicating risks and benefits, technical collaboration, increased transparency, and incentivizing standards. Our analysis shows that industry cooperation on safety will be instrumental in ensuring that AI systems are safe and beneficial, but competitive pressures could lead to a collective action problem, potentially causing AI companies to under-invest in safety.