The article titled "The AI That Learned to Understand Long After It Stopped Trying" discusses a small, strange discovery in machine learning known as grokking. It highlights how this phenomenon involves an AI developing understanding after ceasing to actively try. The piece was originally published on Towards Data Science.
By Utkarsh Mangal
The article discusses how AI detectors can mistakenly flag genuine reviews as problematic, leading to a decrease in the accuracy of sentiment models when those reviews are filtered out. It explores three methods the author tested to identify and mitigate this issue of ‘AI slop’ in training datasets.
By Abdullahi Dattijo
arXiv:2609.15369v1 Announce Type: new
Abstract: Word-level detectors identify unedited AI-generated text almost perfectly, but the literature documents their brittleness under rewording, and a word-l...
By Jochen Madler (Sitefire)
Research projects in the age of AI The post It’s the Lessons We Learned Along the Way. Or, Is It?
By Jacopo Tagliabue
The article "Beyond RAGs: Building Actually Truthful AI Harnesses" discusses the limitations of Retrieval-Augmented Generation (RAG) systems, emphasizing that retrieval alone does not guarantee evidence for AI claims. It explores methods for constructing AI systems that can substantiate their statements, moving beyond simple retrieval to more robust proof mechanisms. The piece highlights the importance of developing AI that can verify its own outputs rather than merely retrieve information.
By Ari Joury, PhD
They aren’t designed, you can’t help perceiving one anyway, and that makes them an engineering problem almost no one is solving. The post Where Does an AI’s Personality Actually Come From?
By Slava Polonski, PhD