Dr. Tim Scarfe and Dr. Keith Duggar discuss OpenAI's new models and their capabilities. They critically analyse claims about AI reasoning, explore the limitations of current language models, and debate the nature of intelligence and computation. Throughout, they emphasize the importance of human oversight in AI applications and discuss potential future developments in the field. MLST is sponsored by Brave: The Brave Search API covers over 20 billion webpages, built from scratch without Big Tech biases or the recent extortionate price hikes on search API access. Perfect for AI model training and retrieval augmentated generation. Try it now - get 2,000 free queries monthly at http://brave.com/api. We edited about an hour off this conversation, see full one on patreon - https://www.patreon.com/posts/tim-and-keith-on-112091132 TOC: 00:00:00 1. Introduction and AI hype cycles 00:02:09 2. Computational limits of AI systems 00:03:57 3. Neural Networks vs. Turing Machines 00:11:55 4. Computational models in AI 00:13:03 5. What is Reasoning? 00:21:08 6. Chain-of-thought prompting 00:26:02 7. AI code generation and complexity 00:34:24 8. AI assistance vs. human problem-solving 00:35:04 9. Limitations of AI in reasoning and problem-solving 00:46:27 10. Knowledge acquisition and inference in AI 00:53:36 11. Comparing AI and human reasoning capabilities 00:58:58 12. LLMs as cognitive tools 01:00:32 13. Testing o1-preview on a logic puzzle 01:20:48 14. AI-assisted coding: strengths and limitations