LLMs lack hyperlocal municipal data, explains disputed Texas power outage debate
csuwildcat · x · 2026-11-12
In a dispute over Texas power outage causes, csuwildcat explains that LLMs are trained mostly on public web-scale text and lack granular hyperlocal data—circuit-level utility vegetation-management records, private work orders and backlog data are generally not digitized at scale. Models can cite news coverage but lack proprietary local maintenance logs, which is why AI anecdotes about tree-related outages in Texas Hill Country are unreliable. He flagged this limitation upfront before posting citations.
More from Models
- Polymarket odds put Chinese AI lab at #1 by year-end at just 6% — Polymarket · 2026-11-12
- FutureHouse's deslopper trains Kosmos to write indistinguishably from human experts — proteinrosh · 2026-11-12
- Developers say Gemini 4 Carbon is notably better at favicon design and micro-interactions — AI_Andrew · 2026-11-12
- Gemini Decision 1 tops knowledge and reasoning evals on calibration, at a steep cost — ArtificialAnlys · 2026-11-12
- Gemini Decision 1 costs $345 per 1M tasks, 3x pricier than leader Drex Max v1.1 — ArtificialAnlys · 2026-11-12
- Google's Gemini Decision 1 scores 66 on AA Decision Index, trails leaders at 3x the cost — ArtificialAnlys · 2026-11-12