• Seattle Skeptics on AI
Seattle Skeptics on AI

Tag: knowledge boundaries

How Large Language Models Communicate Uncertainty to Avoid False Answers
How Large Language Models Communicate Uncertainty to Avoid False Answers

Tamara Weed, Dec, 19 2025

Large language models often answer confidently even when they're wrong. Learn how new methods detect when they're out of their depth-and how to make them communicate uncertainty honestly to build real trust.

Categories:

Science & Research

Tags:

knowledge boundaries LLM uncertainty large language models AI confidence hallucination control

Recent post

  • SLAs and Support: What Enterprises Really Need from LLM Providers in 2025
  • SLAs and Support: What Enterprises Really Need from LLM Providers in 2025
  • Chain-of-Thought in Vibe Coding: Why Explanations Before Code Work Better
  • Chain-of-Thought in Vibe Coding: Why Explanations Before Code Work Better
  • How to Measure Gender and Racial Bias in Large Language Model Outputs
  • How to Measure Gender and Racial Bias in Large Language Model Outputs
  • Public Sector and Generative AI: How Governments Are Using AI for Citizen Services, Policy Drafting, and Records
  • Public Sector and Generative AI: How Governments Are Using AI for Citizen Services, Policy Drafting, and Records
  • Fine-Tuning for Faithfulness in Generative AI: Supervised vs. Preference Methods to Reduce Hallucinations
  • Fine-Tuning for Faithfulness in Generative AI: Supervised vs. Preference Methods to Reduce Hallucinations

Categories

  • Science & Research

Archives

  • March 2026
  • February 2026
  • January 2026
  • December 2025
  • November 2025
  • October 2025
  • September 2025
  • August 2025
  • July 2025

Tags

vibe coding large language models AI coding tools prompt engineering generative AI LLM security AI compliance AI governance AI coding transformer models AI code security GitHub Copilot AI development LLM deployment AI coding assistants prompt injection AI code vulnerabilities GPU utilization LLM optimization AI agents

© 2026. All rights reserved.