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Author laments natural language dominance, calls for structured data internet

The author expresses a strong desire for a more structured, machine-readable internet, lamenting the current reliance on natural language for encoding information. They highlight existing projects like Wikidata and OpenStreetMap as examples of successful structured data initiatives, contrasting them with the limitations of plain text in social media and search. The piece criticizes Large Language Models (LLMs) as an inefficient, backward solution to this problem, suggesting that improving data structure would be a more direct approach. AI

IMPACT Suggests that a shift towards structured data could be a more efficient approach to information processing than current LLM-based methods.

RANK_REASON Opinion piece discussing the limitations of natural language data encoding and advocating for structured data, criticizing LLMs as an inefficient solution.

Read on Mastodon — fosstodon.org →

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

Author laments natural language dominance, calls for structured data internet

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0 / 100
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Commentary
Opinion piece discussing the limitations of natural language data encoding and advocating for structured data, criticizing LLMs as an inefficient solution.
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Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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opinion, other
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Standard
On-topic for AI-industry coverage; kept in the public index.
Story freshness
79 days old
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    The whole # LLM thing has been so funny because it's such a backwards solution to nearly all of humanity's information being encoded as natural language. Instea

    The whole # LLM thing has been so funny because it's such a backwards solution to nearly all of humanity's information being encoded as natural language. Instead of improving how we store information, we just build a Rube Goldberg-ish machine that tries to "understand" human lang…