Our Blog

This article explains why large language models seem intelligent but actually lack real understanding, and warns that treating fluent text as true intelligence can distort how we build AI products and policies.

An approachable explanation of why data is the real engine of AI and how organizations turn raw information into usable ML systems.

A preview of CES that predicts a flood of AI branded gadgets, mixing genuine innovation with heavy marketing noise.

Google is expanding an AI powered Flight Deals assistant and adding more travel planning tools directly into Search.

Practical techniques for turning ChatGPT into a flexible idea partner instead of a boring answer machine.

This article goes inside Anthropic small societal impacts team, whose job is to study how AI systems could harm the world and to push the company toward safer decisions in the middle of an intense AI race.

Wikipedia has quietly produced one of the clearest resources on how to recognize text written by AI models.

An exploration of how like buttons create huge preference datasets that train AI and reshape the online attention economy.

Reddit moderators and long time users are overwhelmed by low effort AI generated posts that feel human at first glance but drain trust from the platform.

Meta has strong AI research and infrastructure but struggles to turn that into compelling consumer products.

The V JEPA model watches ordinary video and learns simple rules about how objects move, giving AI a kind of physical intuition that could help robots and agents.

High school students and teachers are shifting from pure coding to data literacy, statistics, and critical thinking about AI.