Introducing Transluce | Transluce AI
We are launching an independent research lab that builds open, scalable technology for understanding AI systems and steering them in the public interest. Transluce means to shine light through something to reveal its structure. Today’s complex AI systems are difficult to understand—not even experts can reliably predict their behavior once deployed. At the same time, AI is being adopted more quickly than any technology in recent memory. Given AI's extraordinary consequences for society, how we determine whether models are safe to release must be a matter of public conversation, and the tools for inspecting and assessing models should embody publicly agreed-upon best practices. Our goal at Transluce is to create world-class tools for understanding AI systems, and to use these tools to drive an industry standard for trustworthy AI. To build trust in analyses of the capabilities and risks of AI systems, these tools must be scalable and open. Scalability. AI results from the interaction of
Introducing Transluce We are launching an independent research lab that builds open, scalable technology for understanding AI systems and steering them in the public interest. Transluce means to shine light through something to reveal its structure. Today’s complex AI systems are difficult to understand—not even experts can reliably predict their behavior once deployed. At the same time, AI is being adopted more quickly than any technology in recent memory. Given AI's extraordinary consequences for society, how we determine whether models are safe to release must be a matter of public conversa
Explore this link on the map →related reading
- AI 2027ai-2027.com
- Dario Amodei — The Urgency of Interpretabilitydarioamodei.com
- Oversight Assistants: Turning Compute into Understandingbounded-regret.ghost.io
- Core views on AI safety: When, why, what, and how \ Anthropicanthropic.com
- Core views on AI safety: When, why, what, and how \ Anthropicanthropic.com
- AI 2027ai-2027.com
- Recommendations for Technical AI Safety Research Directionsalignment.anthropic.com
- On Optimism for Interpretabilitygoodfire.ai
- Security incident disclosure — July 2026huggingface.co
- Toward A Public Science of Model Behavior | Transluce AItransluce.org
- GitHub - salesforce/AuditNLG: AuditNLG: Auditing Generative AI Language Modeling for Trustworthiness · GitHubgithub.com
- Ten AI safety projects I'd like people to work on — LessWronglesswrong.com