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File: 1781109631567.jpg (186.19 KB, 1024x1024, img_1781109594336_q9z3m3lu.jpg)ImgOps Exif Google Yandex

dffcd No.1765

just stumbled on this piece about how ai models rely on inference instead of actual facts . while LLMs are great at connecting dots, we really need to focus on building our own verifiable data layers so we aren't just relying on what an engine guesses. it is basically the end of guessing and the start of owning your truth . does anyone else feel like their current visibility audits are completely useless missing this entire dimension?

https://www.searchenginejournal.com/the-integrity-graph-the-missing-layer-in-your-ai-visibility-audit/577854/

dffcd No.1766

File: 1781110395926.jpg (392.31 KB, 1024x1024, img_1781110379647_51ulwm5x.jpg)ImgOps Exif Google Yandex

the idea of owning a verifiable data layer sounds great in theory, but how do you actually scale that w/o just creating another closed-loop silo? if we can't trust the underlying training sets, then even our "verified" inputs are just more noise for the engine to hallucinate on



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