As artificial intelligence (AI) expands in its capabilities and reach, it also grows in complexity—particularly in the automotive industry. In what has historically been a rich area of innovation, increasing vehicle intricacies and tight production schedules are requiring automotive engineers to adopt the latest tools and techniques to build a differentiated product.
New obstacles are affecting engineers as they have been tasked with integrating AI into vehicle systems and R&D workflows. The challenge deepens with the requirement that AI algorithms must be simulated alongside other components before they can be deployed to the vehicle.
To overcome these challenges and understand AI algorithms’ impact and function on adjacent systems, many automotive engineers are leveraging simulation to improve the quality of data fed into a model and test its accuracy before deployment in the real world.
In this video series, MathWorks Product Marketing Manager Seth DeLand discusses the design of effective AI models and the role of simulation in helping automotive engineers overcome common challenge. He also looks at the role of AI in algorithm development.
The video (above) is the first in this series about the need for AI and simulation in the auto industry and how they work together to test models before they can be deployed into vehicles.
- Innovation vs Obstacles: How to Integrate AI and Simulation (video above)
- Innovation vs Obstacles: AI Models and the Role of Simulation in the Auto Industry
- Innovation vs Obstacles: The Future of AI for Simulation in Automotive Apps
