<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>Rastonbury</author><text>Thanks for the link, the outputs really reminded me of Westworld&amp;#x27;s &amp;quot;Doesn&amp;#x27;t look like anything to me&amp;quot;</text><parent_chain><item><author>n2d4</author><text>This is a glitch token [1]! As the article hypothesizes, they seem to occur when a word or token is very common in the original, unfiltered dataset that was used to make the tokenizer, but then removed from there before GPT-XX was trained. This results in the LLM knowing nothing about the semantics of a token, and the results can be anywhere from buggy to disturbing.&lt;p&gt;A common example is usernames that participated on the r&amp;#x2F;counting subreddit, where some names appear hundreds of thousands of times. OpenAI has fixed most of them for the hosted models (not sure how, I could imagine by tokenizing them differently), but looks like you found a new one!&lt;p&gt;[1] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.lesswrong.com&amp;#x2F;posts&amp;#x2F;aPeJE8bSo6rAFoLqg&amp;#x2F;solidgoldmagikarp-plus-prompt-generation&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.lesswrong.com&amp;#x2F;posts&amp;#x2F;aPeJE8bSo6rAFoLqg&amp;#x2F;solidgoldm...&lt;/a&gt;</text></item></parent_chain></comment><story><title>GPT-3.5 crashes when it thinks about useRalativeImagePath too much</title><url>https://iter.ca/post/gpt-crash/</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>awestroke</author><text>Using &amp;#x2F;r&amp;#x2F;counting to train an LLM is hilarious.</text><parent_chain><item><author>n2d4</author><text>This is a glitch token [1]! As the article hypothesizes, they seem to occur when a word or token is very common in the original, unfiltered dataset that was used to make the tokenizer, but then removed from there before GPT-XX was trained. This results in the LLM knowing nothing about the semantics of a token, and the results can be anywhere from buggy to disturbing.&lt;p&gt;A common example is usernames that participated on the r&amp;#x2F;counting subreddit, where some names appear hundreds of thousands of times. OpenAI has fixed most of them for the hosted models (not sure how, I could imagine by tokenizing them differently), but looks like you found a new one!&lt;p&gt;[1] &lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.lesswrong.com&amp;#x2F;posts&amp;#x2F;aPeJE8bSo6rAFoLqg&amp;#x2F;solidgoldmagikarp-plus-prompt-generation&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.lesswrong.com&amp;#x2F;posts&amp;#x2F;aPeJE8bSo6rAFoLqg&amp;#x2F;solidgoldm...&lt;/a&gt;</text></item></parent_chain></comment><story><title>GPT-3.5 crashes when it thinks about useRalativeImagePath too much</title><url>https://iter.ca/post/gpt-crash/</url></story>