Medium Article: https://medium.com/@jsmith0475/advancing-parameter-efficient-fine-tuning-a-comparative-analysis-of-lora-and-qlora-in-large-d449f0743481
Dr. Jerry Smith's Medium article explores Low-Rank Adaptation (LoRA) and Quantized 
Low-Rank Adaptation (QLoRA), parameter-efficient fine-tuning methods for large language models. These techniques significantly reduce the computational resources needed for fine-tuning, democratizing AI development by making it accessible to researchers and organizations with limited computing power. The article details the technical mechanisms of LoRA and QLoRA, presents empirical evidence supporting their effectiveness, and discusses their practical applications across various sectors like healthcare and finance. Ultimately, the article argues that these methods are revolutionizing AI, overcoming the computational barriers that previously limited innovation.

Advancing Parameter-Efficient Fine-Tuning: A Comparative Analysis of LoRA and QLoRA in Large Language Models

Medium Article: https://medium.com/@jsmith0475/building-human-facing-agentic-systems-the-psychology-and-sociology-of-super-intelligence-1571cf565d51

Dr. Jerry Smith's January 2025 Medium article explores the psychological, sociological, and ethical implications of "human-facing agentic systems," AI powered by large language models (LLMs). These systems, leveraging multi-headed attention mechanisms, aim to collaborate with humans, not merely serve as tools. The article emphasizes the potential for both empowerment and manipulation inherent in these systems, highlighting the crucial role of self-interest, emotion, and identity in human-AI interaction. Smith concludes with a call for responsible development guided by transparency, inclusivity, and justice, warning against the potential for these systems to become instruments of control.

Building Human-Facing Agentic Systems: The Psychology and Sociology of Super Intelligence

In-Depth Explorations of Neuroscience-Inspired Architectures Revolutionizing AI.

Advancing Parameter-Efficient Fine-Tuning: A Comparative Analysis of LoRA and QLoRA in Large Language Models

Dr. Jerry A. Smith

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