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Respan introduces P-1, a new privacy model that eliminates tradeoffs between accuracy, latency, and cost by detecting and redacting sensitive information, setting a new state of the art.
The author raises concerns about who controls data access for AI agents, questioning if there are established governance architectures, and shares a repo to explore the problem.
The article discusses the challenges and approaches to designing access control for AI agents, focusing on task-based permissions and automated governance.
Google Cloud Tech demonstrates Model Armor, a centralized safety layer that protects multi-agent AI systems from indirect prompt injections, malicious URLs, and sensitive data leaks, with a hands-on lab.
Protegrity is hosting a U.S.-only virtual hackathon challenging developers to build AI applications that securely handle sensitive data, with a $10k top prize.
LangChain announces that LangSmith LLM Gateway can redact sensitive data like SSNs from requests before they reach LLM providers or logs, enhancing privacy and security.