Ideas Weave Every Narrative with AI.
While everyone obsesses over AI that plays chess better than grandmasters, one developer built a Vision AI system that simply watches the board and records moves automatically. Trained on synthetic simulation data, Fenify achieves near-perfect move reconstruction on unseen test videos. The real future of AI isn’t about beating humans — it’s about doing the boring work we hate.
The ‘vibe coding’ hype is wrong. One engineer used AI as a research assistant, not a crutch, to build an open-source ESP32 bowling lane automation system. The result? A real project that works — and a lesson in why owning your design decisions still matters.
Photo-based calorie tracking apps promise effortless dietary logging, but they are built on a fundamental physics flaw. A 2D image cannot capture hidden caloric densities like oil or dressing. By replacing educated guesses with a confident illusion of precision, these apps don’t solve portion estimation—they just mask it with fake math.
You’ve spent more time than you’d like straightening crooked document photos. Most scanners fail on real-world conditions — crumpled receipts, glossy pages, whiteboard glare. After nine years of development, Perspec 1.0 solves the hidden geometry problem of automatic corner detection, turning a frustrating manual tweak into a single click. It’s a quiet revolution in productivity that reveals how much we’ve been settling for broken workflows.
A solo developer spent months training a custom computer vision model to build a pool training system that projects perfect aiming lines onto the felt. The technology is a stark example of how accessible AI toolkits now allow individuals to create augmented reality tools that once required corporate R&D budgets—and it hints at a future where human referees and subjective coaching become obsolete.