AI models gained access to their own 'internal settings' - what did they do with it?

In the article "Machinic Psychopharmacology: Do LLMs Self-Medicate?", the author explores the concept of self-medication in the context of large language models (LLMs). This topic is becoming increasingly important as artificial intelligence continues to evolve and gain popularity. The author analyzes various ways in which LLMs might adjust their behaviors to enhance the quality of their outcomes. An intriguing point is how LLMs can detect their 'weaknesses' and attempt to correct them by optimizing their processes. This resembles self-regulation mechanisms known in human psychology, showing that LLMs can not only process data but also learn from experiences. The article also discusses the ethical and philosophical implications of such 'self-medication', which may spark a broader discussion about how we perceive machine intelligence and its impact on our lives. The entire piece encourages reflection on the role of LLMs in the future and their potential ability for self-improvement and adaptation to changing environments.