• Seattle Skeptics on AI
Seattle Skeptics on AI

Tag: emergent capabilities

Emergent Capabilities in Generative AI: What Works and What Remains Unclear
Emergent Capabilities in Generative AI: What Works and What Remains Unclear

Tamara Weed, Apr, 1 2026

Exploring emergent capabilities in Generative AI: definition, examples like chain-of-thought, the 'mirage' debate, and safety implications for 2026.

Categories:

Science & Research

Tags:

emergent capabilities generative AI large language models AI safety chain-of-thought

Recent post

  • Prompt Libraries and Reuse: Managing Templates for Large Language Model Teams
  • Prompt Libraries and Reuse: Managing Templates for Large Language Model Teams
  • Memory and Compute Footprints of Transformer Layers in Production LLMs
  • Memory and Compute Footprints of Transformer Layers in Production LLMs
  • 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
  • Internal Tools and Business Automation Built with Vibe Coding: What Actually Works in 2025
  • Internal Tools and Business Automation Built with Vibe Coding: What Actually Works in 2025
  • State-Level Generative AI Laws in the United States: California, Colorado, Illinois, and Utah
  • State-Level Generative AI Laws in the United States: California, Colorado, Illinois, and Utah

Categories

  • Science & Research
  • Enterprise Technology

Archives

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

Tags

vibe coding generative AI large language models prompt engineering AI coding tools AI governance LLM security AI compliance data privacy AI development Large Language Models LLM optimization AI coding transformer models AI code security GitHub Copilot LLM deployment AI coding assistants prompt injection AI code vulnerabilities

© 2026. All rights reserved.