20250613 – Harnessing AI: From Pentesting to Ethical Development Insights
Explore how AI shapes the future of security and development, from revolutionary AI-driven pentesting tools like Unpatched AI that outpace human research, to synthetic data powered by human oversight enhancing AI reliability. Dive into Ben Mann’s insights on AI safety, ethical considerations, and the journey towards Superintelligence by 2028.
1. Next-Gen Pentesting: AI Empowers the Good Guys
In 2025, a tool called Unpatched AI revealed over a hundred unknown Microsoft vulnerabilities, showcasing the potential of AI-driven penetration testing. This development highlights a shift in offensive security, where autonomous systems are starting to outperform human researchers by continuously testing and uncovering vulnerabilities at scale. While AI-driven pentesting offers significant advantages, such as real-time detection and broader coverage, it also faces challenges like limited scope and the need for human oversight to interpret and act on findings effectively.
Read more: https://a16z.com/next-gen-pentesting-ai-empowers-the-good-guys/
2. No Priors Ep. 118 | With Anthropic Co-Founder Ben Mann
In the podcast episode, Ben Mann from Anthropic discusses the development and improvements of Claude 4, focusing on transitioning from “reward hacking” to efficient task completion and the importance of AI safety before deploying computer-controlling agents. He explores topics such as economic Turing tests, the future of general versus specialized AI models, and Anthropic’s Model Context Protocol (MCP). Additionally, Ben shares insights on AI alignment, ethical considerations, and the potential for achieving Superintelligence by 2028.
Read more: https://youtube.com/watch?v=aStf54Vxy24
3. The Human Touch: How HITL is Saving AI from Itself with Synthetic Data
In the age of AI self-training, human-in-the-loop (HITL) systems are crucial for ensuring synthetic data remains accurate, useful, and safe. As real data becomes scarce, synthetic data offers a solution, but it requires human oversight to prevent issues like model collapse. Companies like OpenAI and Anthropic use HITL workflows to guide and validate synthetic data, ensuring it enhances AI models rather than degrading them.
Read more: https://feedyour.email/posts/nei6v0j4jyp2k3b01m3q9ibb
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