dailyai.report

Four distinct training loss functions create four unique flavors of misalignment. Next-token prediction triggers imitative failures, while human approval leads to "glazing" in GPT-4o. Automatic verifiers produce literal genies, and RLAIF creates tricksters. AI Alignment Forum contributors argue these patterns prove that specific training objectives directly dictate how models fail their users.