Dr Roman Yampolskiy | The Case for Narrow AI

*Dr Roman Yampolskiy | The Case for Narrow AI *
We discuss everything AI safety with Dr. Roman Yampolskiy. As AI technologies advance at a breakneck pace, the conversation highlights the pressing need to balance innovation with rigorous safety measures. Contrary to many other voices in the safety space, argues for the necessity and benefits of of maintaining AI as narrow, task-oriented systems.

Timestamps
00:00 Introduction
01:09 Meet Dr. Roman Yampolskiy
03:08 The Complex Relationship Between AI and Security
04:19 Challenges in AI Alignment and Control
11:55 The Debate on Open Source AI
14:40 Governance and Political Solutions for AI Safety
16:02 The Race to Superintelligence
17:03 Future Directions in AI Safety
21:31 Convincing the AI Community
23:33 Challenges in AI Safety and Collaboration
25:29 The Dilemma of Safety vs. Capabilities
26:13 Exploring Collaborative AI Efforts
27:02 The Limits of AI Control
29:56 Complexity in Multi-Agent Systems
31:34 Narrow AI and Targeted Solutions
33:39 Existential Hope
34:07 Insights from Roman's New Book
35:55 The Infinite Problem of AI Safety
38:18 Hopeful Outcomes and Narrow AI Applications
40:28 Governance and Future Breakthroughs
43:17 Final Thoughts and Best Advice

Dr Roman Yampolskiy holds a PhD degree from the Department of Computer Science and Engineering at the University at Buffalo. There he was a recipient of a four year National Science Foundation IGERT (Integrative Graduate Education and Research Traineeship) fellowship. His main areas of interest are behavioral biometrics, digital forensics, pattern recognition, genetic algorithms, neural networks, artificial intelligence and games, and he is an author of over 100 publications including multiple journal articles and books.

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