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Discussing politics with a chatbot: How political beliefs shape prompt formulation for generative AI

By generating comprehensive and highly personalized answers to user prompts, AI chatbots such as ChatGPT and Gemini can serve as alternatives to search engines and substantially transform online information seeking. However, little research has examined how users interact with these tools to find information, particularly about politics. In this experiment, we examine how Swiss citizens (N = 563)…

We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.

Read the original at arxiv.org →

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👻 Haunted Code Reviewer: Building an AI Code Reviewer with a Ghostly Twist | Hacktoberfest 2026

This is a submission for the "Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine" ( https://dev.to/challenges/hacktoberfest-week4-2026-10-26 ) What I Built 👻 Haunted Code Reviewer is…

  • Haunted Code Reviewer is an AI-powered web app for code feedback with ghostly commentary.
  • Built using Python, Streamlit, and Hugging Face Inference API with Llama 3.1 8B Instruct model.
  • Open Innovation allowed app development on mobile using GitHub Codespaces and Community Cloud.

Ghostlight AI — Stories from the Other Side

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine What I Built 👻 Ghostlight AI — Stories from the Other Side For the Ghost in the Machine challenge, I…

  • Ghostlight AI is a Halloween/Día de los Muertos inspired AI storytelling experience
  • Features Ghost Story Generator and Memory Keeper components
  • Built with HTML5, CSS3, JavaScript, Transformers.js, and FLAN-T5 Small model

OpenAI's Model Spec Drops Most Style Rules and Tells GPT to Read Prompts for Intent

Book: LLM Observability Pocket Guide Also by me: Thinking in Go (2-book series) — Complete Guide to Go Programming + Hexagonal Architecture in Go My project: Hermes IDE | GitHub — an IDE for…

  • OpenAI revised Model Spec emphasizes five core values
  • Models instructed to read prompts for intended purpose
  • Unclear intent leads to safe, cross-interpretation answers

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