Prompting
PulseAugur coverage of Prompting — every cluster mentioning Prompting across labs, papers, and developer communities, ranked by signal.
2 天有情绪数据
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微调 vs. RAG：LLM应用开发的框架
构建LLM应用需要选择微调（fine-tuning）或检索增强生成（Retrieval-Augmented Generation, RAG）中的一种，对于需要频繁更新信息的应用，RAG是更优选择。微调更适合需要特定输出格式或风格的任务，因为它会修改模型的权重。对于既需要最新知识又需要一致行为的应用，建议结合使用这两种技术。RAG通常比微调的每次查询延迟和成本略高，但微调有前期训练成本。
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Prompting expert shares 5-year insights on effective AI communication
An author with five years of experience in AI prompting shares insights on how to effectively communicate with AI models. The core message is that most users are not inherently bad at using AI, but rather struggle with …
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AI alignment research expands to userland harnesses beyond model weights
A new perspective on AI alignment suggests focusing on "userland alignment," which involves developing aligned harnesses and prompting strategies for AI models rather than solely concentrating on the models themselves. …
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Master AI prompting with practical tips for enhanced productivity
This article offers practical advice on enhancing AI prompting skills, aiming to help users achieve better results from artificial intelligence tools. It suggests techniques to refine prompts for improved accuracy and e…