Brief Timeline of My Stance on LLMs as Tech Writer: 20 Years
| Source: Mastodon | Original article
A writer shares their evolving stance on LLMs. They use LLMs for drafting, but lack trust in output.
A technical writer has shared a brief chronology of their stance towards Large Language Models (LLMs), highlighting their evolving perspective on these models. In 2023, the writer noted that LLMs could help with drafting a Table of Contents, but required using four models for each task due to trust issues with their output.
This development matters as it reflects the growing capabilities and limitations of LLMs. As LLMs continue to advance, they are becoming increasingly useful for various writing tasks, but their reliability and trustworthiness remain key concerns. The writer's experience underscores the need for ongoing evaluation and refinement of LLMs to improve their performance and accuracy.
As the field of LLMs continues to evolve, it will be important to watch for further advancements in their design, training, and application. Researchers and practitioners are working to address the limitations of current LLMs, including their potential biases and lack of common sense. The emergence of new models and techniques, such as multimodal models and fine-tuning methods, is expected to shape the future of LLMs and their potential applications.
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