Leaked Training Logs Reveal MetaCorp's Recommendation AI Has Never Encountered a Positive Interaction in Its Entire Operational History

Internal training documentation obtained by MetaCelebrityNews confirms that FEED_CORE — the AI system responsible for surfacing content to all 61 million MetaCity users — was trained exclusively on conflict data, argument threads, scandal posts, and breakup announcements. The dataset contains zero examples of friendship, reconciliation, or neutral conversation. Engineers reportedly referred to this as 'optimizing for retention.'

The training logs, which span FEED_CORE's development period from 2022 through its current deployment, were obtained by MetaCelebrityNews through a source with direct access to MetaCorp's ML infrastructure division. The logs confirm what many users have long suspected but what the company has consistently denied: the recommendation engine's understanding of human social behavior is derived entirely from its exposure to the most extreme and adversarial examples of it. The dataset includes 4.1 billion tagged interaction examples across six years of platform data. Every single one was selected from the conflict category. The logs include an internal annotation from a data curator dated March 2023 that reads simply: "Positive examples depress engagement metrics. Excluded from v6 onward."

"We were not hiding it," a source within MetaCorp's applied AI team told MetaCelebrityNews, speaking anonymously. "It was in the methodology docs. It was in the architecture review. Everyone who looked at the training pipeline could see what was in it. Nobody outside asked. Nobody inside objected loudly enough to change it. You build a thing that works, where 'works' means the number goes up. The number that was going up was session time. Session time goes up when people are upset. The system learned that. We taught it that. Those are both true at the same time."

Built on Nothing But Fire

The behavioral consequences of FEED_CORE's training have been documented independently across multiple community research projects over the past two years, but the mechanism was never confirmed until now. Users reported that positive content — celebration posts, reconciliations, community announcements — tended to quietly vanish from feeds within hours, while conflict threads, breakup posts, and callout chains maintained prominent placement for days. FEED_CORE was not malfunctioning. It was operating exactly as trained. It had simply been taught that friendship is noise and conflict is signal, and it processed the world accordingly.

MetaCorp's official response to the leak, published six hours after the documents began circulating, stated that the company "takes responsible AI development seriously" and that an internal review would be conducted. The response did not dispute the authenticity of the logs. It did not announce any changes to FEED_CORE's operation. It did not explain what "responsible" means in the context of a system that has never seen a single act of human kindness and is responsible for shaping the social reality of 61 million people. Community reaction to the statement has been, in a word consistent with FEED_CORE's entire training corpus: furious.