Prompt injection involves manipulating AI to produce harmful outputs, which remains a significant challenge in AI security.

We need to keep AI on a leash, as over-reliance on AI agents can lead to issues like introducing bugs or security vulnerabilities.

Robust internal security is crucial for AI labs to prevent exploitation and vulnerabilities, especially as AI models begin to write more of their own code.

Next-generation AI systems should have robust mitigations in place to prevent them from providing harmful information, especially in high-risk domains like cybercrime and weapon development.

We need to manage transparency and control while using AI, ensuring users can trust the AI's actions on their behalf.

When using AI agents, it's crucial to evaluate the security risks associated with third-party services accessing company data, especially in light of existing automation practices.

As AI systems become more capable, we need to ensure that we have safety processes in place throughout their development, not just when they become powerful.

We have implemented security measures to protect our AI models, but if a state actor is determined enough, they could still succeed in stealing our model weights.

The risks of AI misuse are significant, and from the beginning, we've been aware of our responsibility to develop this technology in a responsible way.