Medium Article: https://medium.com/@jsmith0475/chatgpt-is-too-smart-for-the-fda-until-now-8beb59745153

"ChatGPT Is Too Smart for the FDA — Until Now," by Dr. Jerry A. Smith, addresses the critical problem of non-reproducibility in large language models (LLMs), which prevents their adoption in highly regulated fields like pharmaceutical manufacturing. The author introduces cognitive anchoring, a novel gauge-theoretic framework that stabilizes transformer architectures by synchronizing their parallel attention heads using structured constraints derived from principles similar to those in Maxwell's equations. This method ensures that identical inputs yield consistent, deterministic outputs, achieving significant improvements in symbolic consistency and reducing complexity in analytical report generation. The work establishes a necessary foundation for trustworthy AI compliant with FDA data integrity standards (ALCOA+ and 21 CFR Part 11) by demonstrating that LLMs can be constrained to meet mandatory reproducibility requirements.