Claude.ai – in its own words:
“LLMs (Large Language Models) like myself often struggle with simple counting questions like "How many Rs are in strawberry?" for a few key reasons:
1. Lack of visual representation: We don't "see" words as images or sequences of letters. Instead, we process language as patterns of tokens and statistical relationships.
2. No explicit counting mechanism: We don't have a built-in ability to count individual characters or perform precise character-level analysis.
3. Trained on patterns, not literal counting: We're trained to predict likely sequences of words and understand meaning, not to perform character-level operations.
4. Contextual understanding vs. literal interpretation: We excel at understanding context and meaning, but may struggle with tasks that require literal, character-by-character analysis.
5. Overconfidence in quick answers: We might quickly generate an answer based on our statistical understanding of common words, rather than carefully analyzing the specific question.
For this specific question, an LLM might confidently answer "2" because it's a common word and that feels intuitively correct, without actually counting. Or it might give inconsistent answers across multiple attempts.
To accurately answer such questions, LLMs would need specific training on character-level tasks or integration with more precise counting mechanisms.”
interesting…