Jerome LeudetJerome Leudet has a strong background in AI. After a masters in AI and VR, in early 2000s, he developed AIs in the gaming industry for more than a decade and worked in industrial simulation. With the rise of AI, he had the opportunity to start a PhD and study how synthetic data could be used for training neural networks. He founded AILiveSim on a mission to create rich interactive worlds to train and test algorithms. AILiveSim aims to solve the current and future problems with training intelligent systems.
How to make your AV training a success in a virtual world
There are several key factors that can contribute to the success of an autonomous development project using simulation. Besides an accurate and detailed virtual environment you should have a flexible and customizable simulation environment. It should allow developers to easily change and test different aspects of the environment and the autonomous system's behavior. This can include things like the algorithms used for decision-making and path planning, physical parameters of the vehicle or robot as well as sensor parameters. It is crucial for developers to not only have access to the data but have a higher control over it.