Creating games is very difficult. And building games is challenging. The process of build requires to compile the code and all the data required in the game in a specific sequence involving many dependencies. As such monitoring the outcome is essential, but not sufficent. What if we were able to predict the outcome of a build ? What if we were able to decrease the required computing resources while increasing our iteration capability ? #Ubisoft #Ubisoftlaforge #innovation
Let's breakdown: ‘Build Outcome Prediction’ 🎮🧱🔮 The work behind your favorite game is endlessly complex, especially in the "build" phase, where everything comes together to form the game you play. Our R&D group, 'Ubisoft La Forge' have been taking this process to the next level with ‘Build Outcome Prediction’ tech. 🎮🚀 Picture a complex domino arrangement, where one wrong tile could topple your entire masterpiece. That's the challenge in game development. Build Outcome Predictions act like an expert overseeing your setup, analyzing patterns and predicting outcomes to ensure your game builds flawlessly every time. 👨🏫👩🏫 This method not only predicts the success or failure of game builds but also significantly reduces time and resources by optimizing the build process through: 📊 Build Batching: Group changes to maximize efficiency during busy periods. ✈ Build Preflight: Test risky changes locally to prevent errors from escalating. By incorporating machine learning techniques, we can detect subtle patterns and correlations that humans might miss, offering a unique advantage in game development! Learn more about our recent tooled approach, RavenBuild, which will be presented at this years FSE conference. This approach outperforms existing methods, improving prediction accuracy and reducing the risk of costly build failures: 🔗 https://lnkd.in/e_MR9tWY
