Algorithms

AI Detectors Are Making AI Better at Lying. Here’s How.

AI detectors like Pangram aren’t the solutionโ€”they’re fueling an arms race. Every advance in detection teaches the next generation of AI how to sound more human. This isn’t a bug; it’s a Red Queen effect that makes online trust a fading luxury. The only way out is to stop relying on classifiers and build verifiable provenance instead.

AI Just Did Something No Human Could Do for 2,000 Years

AI has decoded the unreadable Herculaneum scrolls buried by Vesuvius in 79 AD. But the real breakthrough isn’t the content โ€” it’s that the same method can read any damaged text, transforming archaeology from a manual craft into a data-driven field. These aren’t just ancient words; they’re proof that the most powerful use of AI might be looking backward.

The ‘No Views’ Trap: Why Your Best Work Stays Invisible

Low views don’t mean low quality. They reveal how algorithmic curation buries depth in favor of dopamine. The Mimeng Principle shows that true originality starts invisible โ€” and that obscurity is often a filter, not a failure. Stop judging your work by metrics designed for mass consumption, and start trusting the slow path to the right audience.

The Most Dangerous Assumption in AI: Treating All Randomness the Same

Most people treat randomness as a property of the world. It’s not. There are two fundamentally different kinds: aleatory (inherent) and epistemic (ignorance). Confusing them leads to catastrophic errors in models, from AI to climate prediction. This article reveals the distinction that will change how you think about uncertainty forever.

Your Hacker News Post Was Killed. It Wasnโ€™t an Accident.

Hacker News silently kills a third of new submissions within minutes. Most users assume it’s deserved, but the opaque system creates a hidden elite of ‘vouch-ers’ who decide what gets a second chance. If your post vanished without explanation, it might not be your faultโ€”it might be a flaw in the platform’s design.