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A new approach to boosting the efficiency of Large Language Models (LLMs) is being explored, focusing on compressed text representations and contextually relevant word clouds. A Reddit user has proposed a system where LLMs process a reduced set of ‘important’ words and their relationships, instead of linearly processing all tokens. This method, drawing inspiration from speed reading techniques, aims to significantly decrease RAM usage by enabling denser information storage. The concept involves identifying key connective words and building a context cloud around them to reconstruct the overall meaning, potentially leading to substantial performance gains. The full discussion can be found on Reddit. [Reddit Post: https://old.reddit.com/r/artificial/comments/1pdbioi/discussion_would_this_be_an_upgrade_in_efficiency/]