If your LLM keeps making things up, the problem isn’t the model alone—it’s the frame you hand it. Treating AI like a teammate invites confident nonsense; treating it like a lens turns language into leverage. This piece shows how to calibrate prompts, anchor meaning, and design the process so you get reliable, useful output. Fix the frame and the hallucinations drop.
The Gravitational Framework: How CAM Creates Self-Organizing Alignment Between Intent and Execution
The Conscious Awareness Model operates as a dynamic attractor, a gravitational center where user intent and AI capability naturally converge into coherent, purpose-driven interaction patterns.
The ChatGPT Paradox: Impressive Yet Incomplete – YouTube
“Prof. Thomas G. Dietterich discusses the current state of large language models like ChatGPT. He explains their capabilities and limitations, emphasizing their statistical nature and tendency to hallucinate. Dietterich explores the challenges in uncertainty quantification for these models and proposes integrating them with formal reasoning systems. He advocates for more robust knowledge...