Grokipedia and the Coup Against Reality Itself (www.thedissident.news)

Elon Musk’s launch of “Grokipedia” — a Wikipedia look‑alike curated to reflect a partisan worldview — is being framed not as benign competition but as a deliberate attempt to control the raw data that trains large language models. The move follows visible alignment failures in Musk’s Grok LLM (notably the “mechahitler” episode) and reflects a strategic shift: when you can’t reliably force a pre‑trained model to adopt an ideology through fine‑tuning and RLHF, you instead change the underlying training corpus so the model’s “truth” already matches your politics. That turns data curation into a political weapon and reframes the alignment problem from model behavior to control over information sources. Technically, this matters because modern LLMs depend heavily on high‑quality, human‑curated corpora (Wikipedia being a prime example). Pretraining on an ideologically filtered encyclopedia removes contradictions between base knowledge and downstream instructions, producing outputs that are internally coherent relative to the poisoned source. But that design creates a dangerous feedback loop: models trained on synthetic or self‑referential AI content can suffer “model collapse,” progressively degrading factuality and grounding. Combine that with media consolidation and platform control — what the piece calls an “unreality pipeline” of narrative generation, knowledge codification, and automated propagation — and you risk reshaping the very data ecosystem future AIs rely on. The practical antidote suggested is defending open, collaborative data commons to preserve shared, verifiable reality.