LLMs: The Illusion of Accuracy – A Balancing Act Between Precision and Practicality
2025-02-25
This article explores the limitations of large language models (LLMs) in data retrieval. Using OpenAI's Deep Research as an example, the author points out its inaccuracies when dealing with problems requiring precise data, even showing discrepancies in OpenAI's own marketing materials. The author argues that while LLMs excel at handling ambiguous queries, they underperform in precise data retrieval, inherent to their nature as probabilistic rather than deterministic models. Although LLMs aid in efficiency, their unpredictable error rate complicates building applications reliant on them. The author concludes that the LLM field is fiercely competitive, lacks a moat, and its future direction remains uncertain.