<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>teleforce</author><text>Shannon is the closest equivalent to Einstein in contribution but for engineering fields.&lt;p&gt;He pioneered several foundational research in the engineering field including communication entropy, cryptography, chess engine, robotic intelligence, digital boolean, LLM and modern AI in general. An outstanding engineer, or engineer&amp;#x27;s engineer in a true sense of word.</text><parent_chain><item><author>ImageXav</author><text>If anyone is on the fence about reading this, or worried about their ability to comprehend the content, I would tell you to go ahead and give it a chance. Shannon&amp;#x27;s writing is remarkably lucid and transparent. The jargon is minimal, and his exposition is fantastic.&lt;p&gt;As many other commentators has mentioned, it is impressive that such an approachable paper would lay the foundations for a whole field. I actually find that many subsequent textbooks seem to obfuscate the simplicity of the idea of entropy.&lt;p&gt;Two examples from the paper really stuck with me. In one, he discusses the importance of spaces for encoding language, something which I had never really considered before. In the second, he discusses how it is the redundancy of language that allows for crosswords, and that a less redundant language would make it harder to design these (unless we started making them 3D!). It made me think more deeply about communication as a whole.</text></item></parent_chain></comment><story><title>A Mathematical Theory of Communication [pdf]</title><url>https://people.math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>jessriedel</author><text>Agreed. This is one of the all time great papers in that it both launched an entire field (information theory) and remains very accessible and pedagogical. A true gem.</text><parent_chain><item><author>ImageXav</author><text>If anyone is on the fence about reading this, or worried about their ability to comprehend the content, I would tell you to go ahead and give it a chance. Shannon&amp;#x27;s writing is remarkably lucid and transparent. The jargon is minimal, and his exposition is fantastic.&lt;p&gt;As many other commentators has mentioned, it is impressive that such an approachable paper would lay the foundations for a whole field. I actually find that many subsequent textbooks seem to obfuscate the simplicity of the idea of entropy.&lt;p&gt;Two examples from the paper really stuck with me. In one, he discusses the importance of spaces for encoding language, something which I had never really considered before. In the second, he discusses how it is the redundancy of language that allows for crosswords, and that a less redundant language would make it harder to design these (unless we started making them 3D!). It made me think more deeply about communication as a whole.</text></item></parent_chain></comment><story><title>A Mathematical Theory of Communication [pdf]</title><url>https://people.math.harvard.edu/~ctm/home/text/others/shannon/entropy/entropy.pdf</url></story>