217 related articles

An in-depth look at AI interpretability research: from chain of thought and probes to sparse autoencoders, exploring how scientists understand neural network internals and assess AI alignment and safety.

Can Global Workspace Theory (GWT) explain the internal mechanisms of large language models? This article explores how residual streams and attention in Transformers map to cognitive science's 'information broadcast' framework.

Exploring how AI builds cognitive computational models from human spatial reasoning experiments, analyzing LLM spatial cognition gaps and Embodied AI applications.

A reported 3-word prompt jailbreak of Claude Opus 5 sparks debate. We analyze the technical nature of LLM jailbreaks, alignment fragility, and defense-in-depth strategies for enterprise AI security.

A reported 3-word jailbreak of Claude Opus 5 sparks debate. We analyze LLM jailbreak mechanics, alignment fragility, and defense-in-depth strategies for AI security.

A federal judge questions the U.S. government's ban on Anthropic AI products, citing insufficient justification. Analysis of the legal dispute, industry impact, and regulatory implications.

A federal judge questions the U.S. government's ban on Anthropic AI products, citing insufficient justification. Analysis of the legal dispute, industry impact, and regulatory implications.

Deep dive into Google DeepMind's Gemini Robotics 2: how whole-body intelligence unifies perception, reasoning, and motor control, and the challenges of bringing embodied AI from lab to commercial deployment.

Deep dive into Google DeepMind's Gemini Robotics 2: how whole-body intelligence unifies perception, reasoning, and motor control, and the challenges from lab demos to commercial deployment.

In-depth analysis of two mainstream approaches for RGB and thermal camera image registration: homography via feature matching and stereo calibration with image rectification, covering cross-modal principles and engineering trade-offs.

Quadruped robots achieve 5+ m/s running speed with payload and off-road capability. Explore how RL Sim-to-Real methods break the impossible triangle of speed, load, and terrain adaptability.

Explore how open weight models achieve both global AI democratization and maintain U.S. competitiveness. Learn the differences between open weight, open source, and closed models, and their strategic impact.

Explore how open weight models simultaneously enable global AI accessibility and maintain U.S. competitiveness. Learn the differences between open weight, open source, and closed source models.

Starting from a viral Reddit meme, we dive deep into AI neural network weights — what they are, why they can't be read visually, and how open weights drive technological democratization.

A systematic guide to standardized datasets for RAG retrieval experiments, covering BEIR, MS MARCO, Natural Questions, and TREC benchmarks for dense, sparse, and hybrid retrieval evaluation.

Formal Languages vs. Programming Language Principles—which course matters more for computational linguistics and NLP? A deep analysis from Chomsky Hierarchy to Lambda calculus to modern LLM theory.

How a Tarski-style attack challenges LLM truth probes from the foundations of logic. Is the linear representation hypothesis valid, or is the "truth direction" in AI activations just a statistical illusion?

AE Studio uses AI to fuse historical shipping archives, marine geographic data, and satellite remote sensing to locate shipwreck treasures via machine learning models.

AE Studio uses AI to fuse historical shipping archives, ocean geographic data, and satellite remote sensing to locate underwater shipwreck treasures via machine learning models.

Deep analysis of a Gemini jailbreak technique—the Observer and Accomplice method—examining how it exploits contextual manipulation and reasoning chain inconsistencies to bypass AI safety alignment.