ty for 4 years of bangers

this is crazy... the guy reverse-engineered his Meta Ray-Bans 3 with Opus 5.5 into a 3,000+ Elo chess engine he built AI chess cheat glasses on Opus 5.5 + Jev and open-sourced the whole workflow here's how it works step by step: step 1 → install it on your Mac with one command: npx chesshacker setup. It downloads Stockfish from GitHub and verifies the checksum step 2 → put on Meta Ray-Bans and video-call your own Mac on WhatsApp. The glasses see the board, the Mac sees what the glasses see step 3 → the Mac grabs frames straight from the call window. About 1 per second while it waits for the opponent, 1 every 3 seconds on your turn step 4 → Jev runs a cheap pre-check on every frame: is the board readable, is a hand over it, did a piece move? No change means no expensive AI call step 5 → only then Opus 5.5 reads the board. The app compares it with the position it already knows and accepts a move only if it's legal step 6 → Stockfish thinks for half a second and picks the best reply, with an eval like +1.5 or "mate in 3" step 7 → macOS speaks it through a virtual mic into the WhatsApp call: "Rook a to d1". You hear it in your ear step 8 → on the Mac a command center shows everything live: whose turn it is, the suggested move with a confidence bar, the move list and a log under the hood: → if Opus loses track of the board, the glasses say "Lost track of the board" and you fix it with undo or by typing the move → if Stockfish crashes, it restarts once and says "Something went wrong. Still trying" → every game is saved as a PGN file, API keys live in the macOS Keychain → an overlay draws the suggested move as an arrow on the live video, ready for OBS Clone his workflow below Then read the guide on how to reverse-engineer anything with Opus 5.5.

Yesterday 908 Replies... This is my highest till date.....

A small X algorithm change worth understanding 👀 Fresh posts could get a fairer chance to be considered for your For You feed. Here’s what changed: X’s public code update on 22 October enabled a “fair-share” filter. When there are too many candidate posts for the scoring budget, it reduces each candidate group proportionally. In simple English: groups near the back of the queue don’t have to absorb all the cuts. The published scoring budget is 2,800 candidates. That means posts being considered—not 2,800 posts shown in your feed. Why might smaller creators care? Fresh posts with little engagement could benefit from getting through this selection stage. But getting considered still doesn’t guarantee being shown. Ranking and visibility checks still apply. Also, those “likes = 0.66 points” lists need context. The weights apply to predicted behaviour, not fixed points added for every action. My take: an encouraging change to how posts get considered. The actual effect on small-account reach still needs measuring. 📊

Finally my game Cozy Colony is available to Pre-register on Play Store. Go to Play Store and pre-register my game 🙏🏻 Just search for Cozy Colony #cozycolony