InAI AdvancesbyMalcolm Lett·Aug 10Can an AI Learn the Planning Algorithm? Part 1Foundations of Algorithmic LearningA response icon3A response icon3
InMIT ScopebyMIT Science Writing·Jan 21New Test Reveals Limits In AI’s Ability To Understand ScienceLarge language models don’t understand scientific principles.A response icon1A response icon1
Nandini·Jan 2CNNs & Inductive Biases: Why Architecture MattersWhat I learned once I stopped treating models as black boxes
Muhammad Faheem·Dec 22, 2025The Evolution of Vision Architectures: From CNNs to Vision Transformers and Swin TransformersFrom Inductive Bias to Scalable Self-Attention in Modern Computer Vision
Robert Encarnacao·Jul 15, 2025The Kepler Trap: When AI Mimics UnderstandingIn the early 1600s, Johannes Kepler mapped the heavens with astonishing precision. Night after night, he charted the planets’ dance around…
Anjali P·Jul 5, 2025What I Learned About Transformers That Nobody Really Talks AboutI’ve been diving deep into transformer architectures lately, and I keep running into this idea that feels important but somehow gets…
George Bird·Jun 16, 2025The Hidden Inductive Bias at the Heart of Deep LearningHi, I’m George, and I’m the author of a recent position paper outlining this very topic: how a little-known inductive bias seems to have…
InTowards AIbySigurd Roll Solberg·May 9, 2025What Models Prefer to Learn: A Geometric Framing of Architecture and RegularizationIntro
domwu·Apr 18, 2025Why Attention is a “Learned Pooling” and the Inductive Biases of CNNsImagine a Convolutional Neural Network (CNN) as a pixel-whisperer, deftly transforming a chaotic photo of a cat into a tidy map of edges…
