LLMs can solve hard problems

LLMs, or Large Language Models, have proven to be effective in solving complex problems, as demonstrated by a recent project. The project aimed to generate transcripts of podcast episodes, index them with a local search engine, and present the results on a static website. By utilizing LLMs, specifically Claude 3.5 'Sonnet', the team was able to accurately identify speakers in podcast transcripts, overcoming the challenge of speaker diarization. The LLM processed large amounts of text data, extracting speaker names efficiently, which was a difficult task to achieve through traditional programming methods. Additionally, LLMs were employed to generate episode synopses, showcasing their versatility in handling diverse tasks with ease. The successful implementation of LLMs in this project highlights their practical applications beyond mere hype, offering valuable solutions to complex problems in various domains.