A Reddit user has shifted their perspective on smaller AI models, moving away from evaluating them based on their knowledge recall to assessing their ability to utilize external tools. The user notes that while smaller models (around 5 billion active parameters) may not possess extensive internal knowledge, they can be trained to effectively call upon external documentation or codebases instead of inventing plausible but incorrect answers. This approach is seen as more valuable for practical applications where information can be dynamically retrieved and audited, though a challenge remains in ensuring models recognize when they don't know something and need to use a tool. AI
IMPACT Suggests a new evaluation metric for LLMs, focusing on tool use over knowledge recall, which could influence future model training and benchmarking.
RANK_REASON User opinion piece on evaluating AI models.
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