Is your AI an engineering partner, or just more friction?
AI hype is everywhere, but how do you trust a ‘black box’ that ignores physical laws and requires costly, data-hungry validation cycles?
With complexity skyrocketing, wait and see is not an option. But the answer isn’t just more AI – you need to invest in the right kind of AI.
Secondmind and BeyondMath are holding a webinar, titled ‘Cutting through the AI noise: A leader’s guide to engineering-grade intelligence’, at 2:00pm GMT / 3:00pm CET on March 24 that will explore engineering AI – a new class of technology built to partner with engineers – and offer actionable insights to take your expert intuition to new heights. Register for the webinar here.
Five key learning points for delegates
The session will be structured to provide delegates with actionable frameworks for mastering automotive complexity:
Navigating the AI landscape: Learn to distinguish between the different branches of AI – perceptual, generative, predictive and engineering – to ensure investments match specific problem sets.
Solving the ‘big data problem’: Discover how to achieve higher precision results using sparse, physics-informed datasets, bypassing the traditional need for thousands of costly physical test cycles.
Establishing trust and transparency: Understand why explainable models and uncertainty quantification are non-negotiable for meeting safety-critical regulatory standards.
Operationalizing engineering AI: Practical strategies for integrating these tools into existing workflows – such as e-motor design and NVH – without the need for expensive “rip and replace” infrastructure shifts.
Mastering complexity: Learn how to leverage AI to surface critical requirements early, avoiding expensive rework in high-dimensional development environments.
Delegates will receive a clear framework for selecting the right AI tools to master the uncompromising constraints of modern automotive engineering.