Summary
In this blog post, Murat Demirbas, a distributed systems researcher, reflects on the impact of large language models (LLMs) on his work and the field at large. He provides a collection of his writings on LLMs, emphasizing their strengths, weaknesses, and his consistent view that while LLMs can produce fast, competent output, they often lack depth for experts. He discusses LLMs as valuable tools for managing mundane tasks, allowing for more focus on critical work. The post also highlights intersections between AI and formal methods in systems research, illustrating how LLMs are integrated into academic and practical work.