[James Stanley] enjoys chess, isn’t terribly good at it, and has some dubious scruples. At least, that’s the setup for building Sockfish, a shoe-to-Pi interface to let you cheat at chess. We’re pretty sure only the first point is true, but the build is impressive all the same. It’s a pair of 3D printed shoe inserts, with two pressure-sensitive inputs on each insert, coupled with a vibration motor in each. Tap out your opponent’s moves during the game, and the Stockfish software will buzz instructions back to you. Just follow the instructions, and you too can be a chess master.
In practice things went a bit awry, as poking in encoded move data with one’s feet isn’t the easiest task, and discerning the subtle tickles on the toes is error-prone at best. [James] arranged a match against an unsuspecting friend (in the name of science), and managed to fat-finger (fat-toe?) the inputs on both games, leading to Sockfish instructing him to make illegal moves.
This seemed like too much cheating, even for [James], so he played the rest of each game on his own abilities, winning one of the two. Once the deed was done, our anti-hero gladly doffed his shoes to show off his gadgetry. After some debate, they concluded the device might “bring the game into disrepute” if used for greater evil. Naturally [James] is already working on an improved version.
Thanks to [Abe Tusk] for the tip!
Finally, a useful application for machine vision! Forget all that self-driving nonsense and facial recognition stuff – we’ve finally got an AI that can count cards at the blackjack table.
The system that [Edje Electronics] has built, dubbed “Rain Man 2.0” in homage to the classic title character created by [Dustin Hoffman] for the 1988 film, aims to tilt the odds at the blackjack table away from the house by counting cards. He explains one such strategy, a hi-low count, in the video below, which Rain Man 2.0 implements with the help of a webcam and YOLO for real-time object detection. Cards are detected in any orientation based on their suit and rank thanks to an extensive training set of card images, which [Edje] generated synthetically via some trickery with OpenCV. A script automated the process and yielded a rich training set of 50,000 images for YOLO. A Python program implements the trained model into a real-time card counting application.
Rain Man 2.0 is an improvement over [Edje]’s earlier Tensor Flow card counter, but it still has limitations. It can’t count into a six-deck shoe as the fictional [Rain Man] could, at least not yet. And even though cheater’s justice probably isn’t all cattle prods and hammers these days, the hardware needed for this hack is not likely to slip past casino security. So [Edje] has wisely limited its use to practicing his card counting skills. Eventually, he wants to turn Rain Man into a complete AI blackjack player, and explore its potential for other games and to help the visually impaired.
Continue reading “Let The Cards Fall Where They May, With A Robotic Rain Man”
If you don’t have the patience to play through the original Prince of Persia perhaps you should just cheat? [BLuRry] has made this easy for us, by building Prince of Persia cheats into JACE, the Java Apple Computer Emulator.
He shows off the emulator and the cheats he added in the video after the break. We saw the ability to teleport anywhere, kill enemies immediately, and open gates and exits. All of this happens with the click of a mouse. But there’s also a configuration screen used to enable the cheats that offers a handful of other cheat options that weren’t original to the game. [BLuRry] managed to roll these cheats into the emulator after some thoughtful study of the original source code which [Jordan Mechner] recently released after the once-lost floppy discs storing the ancient digital gem were discovered.
You know, we always see people running doom on various types of hardware. Maybe we should start using PoP as our go-to novelty game?
Continue reading “Cheat Your Way Through The Original Prince Of Persia”