Simple question that Microsoft Phi-4 Large Language Model (LLM) cannot answer https://gnu.support/large-language-models-llm/Simple-question-that-Microsoft-Phi-4-Large-Language-Model-LLM-cannot-answer.html
On the night of March 21, 2025, in Kampala, Uganda, a family faced an unexpected challenge when their prepaid electricity expired at midnight. The father needed to ensure his eldest son could attend school on time but found himself without power and with no phone battery left for mobile payment. After contemplating various solutions suggested by the Microsoft Phi-4 Large Language Model (LLM), such as borrowing a neighbor's phone or charging in public, he realized that asking his wife—who was awake—to use her charged phone to pay via mobile money would be simplest. This experience highlighted an irony: while LLMs can process complex data and suggest detailed solutions, they often miss straightforward answers like leveraging family resources. This underscores the gap between artificial intelligence's capabilities and human intuition in everyday problem-solving situations. The incident emphasized that innovation isn't just about creating new technologies but recognizing simple existing solutions within one’s immediate environment. -- Jean Louis --- via emacs-tangents mailing list (https://lists.gnu.org/mailman/listinfo/emacs-tangents)
