Whilst we patiently wait for the day that Womble-shaped robots replace human tennis players at Wimbledon, we can admire the IBM powered AI technology that the organisers of the Wimbledon tennis tournament use to enhance the experience for TV and phone viewers.
As can be expected, the technology tracks the ball, analyses player gestures, crowd cheers/booing but can’t yet discern the more subtle player behaviour such as serving an ace or the classic John McEnroe ‘smash your racket on the ground’ stunt. Currently a large number of expert human side kicks are required for recording these facets and manually uploading them into the huge Watson driven analytics system.
Phone apps are possibly the best places to see the results of the IBM Slammtracker system and are perfect for the casual tennis train spotter. It would be interesting to see the intrinsic AI bias at work – whether it can compensate for the greater intensity of the cheer for the more popular celebrities rather than the skill, or fluke shot, of the rank outsider. We also wonder if it will be misogynistic – will it focus on men rather than women in the mixed doubles or the other way round? Will it be racist? Also, when will the umpires be replaced with 100% AI?
Finally, whilst we at Hackaday appreciate the value of sport and exercise and the technology behind the apps, many of us have no time to mindlessly watch a ball go backwards and forwards across our screens, even if it is accompanied by satisfying grunts and the occasional racket-to-ground smash. We’d much rather entertain ourselves with the idea of building the robots that will surely one day make watching human tennis players a thing of the past.
Making a copy of a purchased game used to be as simple as copying a disk. As the game industry grew, so did fear of revenue loss which drove investment in countermeasures. These mainly consisted of preventing the easy duplication of magnetic diskettes, or having users jump through tiresome hoops like entering specific words from the printed manual. These measures rarely posed much of a challenge to the dedicated efforts of crackers, but the copy protection in the classic 80s game Dungeon Master for the Atari ST and Amiga was next-level. It implemented measures that went well beyond its contemporaries, and while it was eventually defeated, it took about a year to happen. In an era where games were cracked within days or even hours of release, that was remarkable.
Dungeon Master was a smash hit at the time, and while the details of its own brand of what we would now call DRM may not be new, this video presentation by [Modern Vintage Gamer] (YouTube link) does a wonderful job of stepping through everything it did, and begins with an informative tour of copy protection efforts of the era for context.
The video is embedded below, but if you’d like to skip directly to the details about Dungeon Master, that all starts just past eight minutes in. What we now call DRM clearly had roots that preceded the digital world of today; an absurd timeline in which even cat litterboxes can have DRM.
Continue reading “Copy Protection In The 80s, Showcased By Classic Game Dungeon Master”
People take their tabletop games very, very seriously. [Andrew Lauritzen], though, has gone far above and beyond in pursuit of a fair game. The game in question is Star War: X-Wing, a strategy wargame where miniature pieces are moved according to rolls of the dice. [Andrew] suspected that commercially available dice were skewing the game, and the automated machine-vision dice tester shown in the video after the break was the result.
The rig is a very clever design that maximizes the data set with as little motion as possible. The test chamber is a box with clear ends that can be flipped end-for-end by a motor; walls separate the chamber into four channels to test multiple dice on each throw, and baffles within the channels assure randomization. A webcam is positioned below the chamber to take a snapshot of each “throw”, which is then analyzed in OpenCV. This scheme has the unfortunate effect of looking at the dice from the table’s perspective, but [Andrew] dealt with that in true hacker fashion: he ignored it since it didn’t impact the statistics he was interested in.
And speaking of statistics, he generated a LOT of them. The 62-page report of results from his study is an impressive piece of work, which basically concludes that the dice aren’t fair due to manufacturing variability, and that players could use this fact to cheat. He recommends pooled sets of dice to eliminate advantages during competitive play.
This isn’t the first automated dice roller we’ve seen around these parts. There was the tweeting dice-bot, the Dice-O-Matic, and all manner of electronic dice throwers. This one goes the extra mile to keep things fair, and we appreciate that.
Continue reading “Automated Dice Tester Uses Machine Vision To Ensure A Fair Game”
In the old days, hardware was a limiting factor and Basic made it pretty easy to whip out some text or crude graphics. Our favorite was a high low game that guesses your number. But everyone had some little game they’d create so they said they could. Today’s games, though, have good graphics and music and 3D shapes and a host of other things you didn’t have to contend with back then. Game Builder, though, makes it pretty simple. You can work on a game by yourself, or with friends, or with the general public. Everyone involved can play the game, but they can also edit the game. The tool runs under Steam so even though it is marked for PC or Mac, it will also run on Linux if you have Steam installed properly.
Continue reading “Game Builder Lets Kids — Even Old Kids — Build Games”
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’re a fan of DOS games from the 1990s, you’ve almost certainly used DOSBox to replay them on a modern computer. It allows you to run software in a virtual environment that replicates an era-appropriate computer. That’s great for historical accuracy, but doesn’t do you much good if you’re trying to leverage modern computing power to breathe some new life into those classic titles. For that, you need to dig in a little deeper.
For the last two and a half years, [Nikolai Wuttke] has been doing exactly that for 1993’s Duke Nukem II. The end result is RigelEngine, an open source drop-in replacement for the original game binary that not only runs on a modern Windows, Linux, or Mac OS machine, but manages to improve on the original in a number of ways. An accomplishment made even more impressive once you learn that the original source code for the game has been lost to time, and that he had to do everything blind.
In a blog post chronicling his progress so far, [Nikolai] explains the arduous process he used to make sure his re-implementation was as accurate as possible to the original game. He spent untold hours studying the original game’s disassembled code in Ida Pro, handwriting out pages of notes and pseudocode as he tried to understand what was happening behind the scenes. Once a particular enemy or element of the game was implemented in RigelEngine, he’d record the gameplay from his version and compare it to the original frame by frame so he could fine tune the experience.
So what’s the end result of more than two years of work and over 25K lines of code? Thanks to the incredible advancements in computing power since the game’s release nearly 30 years ago, [Nikolai] has managed to remove the need for loading screens. His engine is also capable of displaying an unlimited number of particle effects on the screen at once, and multiple sound effects can now be played simultaneously. In the future he’s looking to implement smooth character movement (in the original game, movement was in 8 pixel increments) and adaptive volume for sound effects based on their distance from Duke. Ultimately, RigelEngine should be able to replace the original graphics with new high resolution textures once some issues with the rendering buffer gets sorted out.
It’s hard to overstate how important some of these classic games are to those who grew up playing them. With John Romero still releasing DLC for the original DOOM and hackers disassembling nearly 40 year old games to fix bugs, it doesn’t seem like they’re in any danger of being forgotten.
Continue reading “Hail To The King, Baby: Reverse Engineering Duke”
Should you happen to have an HP7440A or similar plotter hanging around, you could have a quick game of Flappy Bird — or Plotty Bird as [WesleyAC] calls it. Just be sure you have some blank paper. The whole thing fits in about 200 lines of Rust code and — according to the author — gets to about 20 frames per second.
Watching the thing go, it appears that it draws a random set of pipes and then traces your flight path on the same page in real time.
Continue reading “1980s Plotter Plays Flappy Bird”