Roman Yampolskiy on Shoggoth, Scaling Laws, and Evidence for AI being Uncontrollable
Roman Yampolskiy joins the podcast again to discuss whether AI is like a Shoggoth, whether scaling laws will hold for more agent-like AIs, evidence that AI is uncontrollable, and whether designing human-like AI would be safer than the current development path.
Roman Yampolskiy joins the podcast again to discuss whether AI is like a Shoggoth, whether scaling laws will hold for more agent-like AIs, evidence that AI is uncontrollable, and whether designing human-like AI would be safer than the current development path. You can read more about Roman's work at http://cecs.louisville.edu/ry/ Timestamps: 00:00 Is AI like a Shoggoth? 09:50 Scaling laws 16:41 Are humans more general than AIs? 21:54 Are AI models explainable? 27:49 Using AI to explain AI 32:36 Evidence for AI being uncontrollable 40:29 AI verifiability 46:08 Will AI be aligned by default? 54:29 Creating human-like AI 1:03:41 Robotics and safety 1:09:01 Obstacles to AI in the economy 1:18:00 AI innovation with current models 1:23:55 AI accidents in the past and future
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.
