Dan Hendrycks joins the podcast again to discuss X.ai, how AI risk thinking has evolved, malicious use of AI, AI race dynamics between companies and between militaries, making AI organizations safer, and how representation engineering could help us understand AI traits like deception.
Dan Hendrycks joins the podcast again to discuss X.ai, how AI risk thinking has evolved, malicious use of AI, AI race dynamics between companies and between militaries, making AI organizations safer, and how representation engineering could help us understand AI traits like deception. You can learn more about Dan's work at https://www.safe.ai Timestamps: 00:00 X.ai - Elon Musk's new AI venture 02:41 How AI risk thinking has evolved 12:58 AI bioengeneering 19:16 AI agents 24:55 Preventing autocracy 34:11 AI race - corporations and militaries 48:04 Bulletproofing AI organizations 1:07:51 Open-source models 1:15:35 Dan's textbook on AI safety 1:22:58 Rogue AI 1:28:09 LLMs and value specification 1:33:14 AI goal drift 1:41:10 Power-seeking AI 1:52:07 AI deception 1:57:53 Representation engineering
Basil Halperin discusses how financial markets and economic indicators, such as interest rates, can provide insights into AI development timelines and the potential economic impact of transformative AI.
Benjamin Todd discusses the evolution of reasoning models in AI, potential bottlenecks in compute and robotics, and offers advice on personal preparation for AGI, including skills, networks, and resilience, with projections through 2030.
Calum Chace discusses the potential for AI to transform employment, exploring universal income, fully-automated economies, AI-driven education, and the ethical challenges of attributing consciousness to machines.
