Why AI Learns Consensus Over Truth

Send us Fan Mail In this episode we explore why frontier large language models frequently prioritize popular consensus and plausible-sounding explanations over objective truth. Built primarily on massive web crawls—where high-authority sources like encyclopedias, patents, and peer-reviewed journals represent only 2% to 5% of training data—today's models are trained to mirror popular web content and conversational style rather than verify factual accuracy. We break down the underlying mechani...