Tags: prompt engineering* + llm* + anthropic*

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  1. This article details an iterative process of using ChatGPT to explore the parallels between Marvin Minsky's "Society of Mind" and Anthropic's research on Large Language Models, specifically Claude Haiku. The user experimented with different prompts to refine the AI's output, navigating issues like model confusion (GPT-2 vs. Claude) and overly conversational tone. Ultimately, prompting the AI with direct source materials (Minsky’s books and Anthropic's paper) yielded the most insightful analysis, highlighting potential connections like the concept of "A and B brains" within both frameworks.
  2. An article discussing the concept of monosemanticity in LLMs (Language Learning Models) and how Anthropic is working on making them more controllable and safer through prompt and activation engineering.
  3. Anthropic has introduced a new feature in their Console that allows users to generate production-ready prompt templates using AI. This feature employs prompt engineering techniques such as chain-of-thought reasoning, role setting, and clear variable delineation to create effective and precise prompts. It helps both new and experienced prompt engineers save time and often produces better results than hand-written prompts. The generated prompts are also editable for optimal performance.

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