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User finds LLM-generated AI lacks practical coding advice

A user on Mastodon shared their experience with LLM-generated AI, noting that it has not offered practical solutions like handling disk-full scenarios. They attribute this limitation to the AI's training data, which they believe contains a significant amount of "garbage" information, echoing the old computing principle of "garbage in, garbage out." AI

RANK_REASON User opinion on LLM limitations, not a significant industry event.

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

User finds LLM-generated AI lacks practical coding advice

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0 / 100
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Meme
User opinion on LLM limitations, not a significant industry event.
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opinion, other
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Standard
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Breaking (< 6h)
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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    @ josh I have used some LLM-gen-AI myself, I admit. Not once has it suggested I think about fixing the code to handle disk-full scenarios. Why? Because *people*

    @ josh I have used some LLM-gen-AI myself, I admit. Not once has it suggested I think about fixing the code to handle disk-full scenarios. Why? Because *people* don't think about it! Going back to when I started working with computers in the 1980s, this principle has applied: “Ga…