• Seattle Skeptics on AI
Seattle Skeptics on AI

Tag: internet-scale data

How Large Language Models Learn: Self-Supervised Training at Internet Scale
How Large Language Models Learn: Self-Supervised Training at Internet Scale

Tamara Weed, Sep, 30 2025

Large language models learn by predicting the next word across trillions of internet text samples using self-supervised training. This method, used by GPT-4, Llama 3, and Claude 3, enables unprecedented language understanding without human labeling - but comes with major costs and ethical challenges.

Categories:

Science & Research

Tags:

large language models self-supervised learning LLM training transformer models internet-scale data

Recent post

  • How Generative AI Is Transforming Manufacturing SOPs, Work Instructions, and QC Reports
  • How Generative AI Is Transforming Manufacturing SOPs, Work Instructions, and QC Reports
  • SLAs and Support: What Enterprises Really Need from LLM Providers in 2025
  • SLAs and Support: What Enterprises Really Need from LLM Providers in 2025
  • Vibe Coding Adoption Metrics and Industry Statistics That Matter
  • Vibe Coding Adoption Metrics and Industry Statistics That Matter
  • Ethical Review Boards for Generative AI Projects: How They Work and What They Decide
  • Ethical Review Boards for Generative AI Projects: How They Work and What They Decide
  • 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

Categories

  • Science & Research

Archives

  • December 2025
  • November 2025
  • October 2025
  • September 2025
  • August 2025
  • July 2025

Tags

vibe coding generative AI large language models AI coding tools prompt engineering AI compliance AI governance LLM security AI coding transformer models AI implementation GitHub Copilot Parapsychological Association psi research paranormal studies psychic phenomena parapsychology no-code apps knowledge worker productivity AI app builder

© 2026. All rights reserved.