{"id":80138,"date":"2024-09-12T17:45:39","date_gmt":"2024-09-12T12:15:39","guid":{"rendered":"https:\/\/www.the-next-tech.com\/?p=80138"},"modified":"2024-09-12T17:45:39","modified_gmt":"2024-09-12T12:15:39","slug":"do-llm-make-errors","status":"publish","type":"post","link":"https:\/\/www.the-next-tech.com\/machine-learning\/do-llm-make-errors\/","title":{"rendered":"Do LLMs Make Errors? Is There A Way To Troubleshoot LLM Error Rates?"},"content":{"rendered":"

The simple answer is – Yes. Large Language Models (LLMs) do make errors while generating responses.<\/p>\n

According to the complexity of syntactic characteristics, LLM errors can range from average to higher.<\/p>\n

LLM are like humans which learn language and understand situations from the given context. They make responses through their machine learning models and the efficiency of its learning from previous data.<\/p>\n

Let\u2019s take an example of ChatGPT 4 – which is an LLMs that generates responses in a contextual manner.<\/p>\nAlso read:<\/span> Top 10 Websites And Apps Like Thumbtack | Hire Best Local Pros With Thumbtack Alternatives<\/a><\/span>\n

Given this to ChatGPT \u201c9.11 and 9.9 – which is bigger?\u201d<\/strong><\/p>\n

The response it generated was hilarious. It said\u2026<\/p>\n

\u201c9.11 is bigger than 9.9. When comparing numbers, you look at the whole numbers first, and if those are the same, you compare the decimal parts. In this case, the whole numbers are the same (9), so you compare the decimal parts: 0.11 versus 0.9. Since 0.11 is larger than 0.9, 9.11 is the larger number.\u201d<\/em><\/p>\n

\"ChatGPT<\/p>\n

On the other hand, given this to Gemini, the response was straightforward. It said\u2026<\/strong><\/p>\n

\u201c9.9 is bigger than 9.11\u201d<\/em><\/p>\n

\"Gemini<\/p>\n

\n
!<\/div>\n

<\/span>Interpretation:<\/strong> Given the reasoning to two different LLMs generates responses based on the learning efficiency. We see that Gemini produces the right (\u2714\ufe0f) response compared to ChatGPT.<\/p>\n<\/div>\n

Thus it has been clear that LLMs do make mistakes. According to SAP Learning, \u201cLLMs can understand language, they can also make mistakes and misunderstand or misinterpret data.\u201d [1<\/a>]\n

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