Episode

ML Models for Safety-Critical Systems with Lucas García - #705

Podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Published
Oct 14, 2024
Duration seconds
4566
Processing state
failed
Canonical source
https://twimlai.com/podcast/twimlai/ml-models-for-safety-critical-systems/
Audio
https://pscrb.fm/rss/p/traffic.megaphone.fm/MLN4250685356.mp3?updated=1728934919
JSON
/v1/public/podcasts/twiml-ai-podcast/episodes/ml-models-for-safety-critical-systems-with-lucas-garc-a-705
Markdown
/podcast/twiml-ai-podcast/ml-models-for-safety-critical-systems-with-lucas-garc-a-705.md

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Summary

Today, we're joined by Lucas García, principal product manager for deep learning at MathWorks to discuss incorporating ML models into safety-critical systems. We begin by exploring the critical role of verification and validation (V&V) in these applications. We review the popular V-model for engineering critical systems and then dig into the “W” adaptation that’s been proposed for incorporating ML models. Next, we discuss the complexities of applying deep learning neural networks in safety-critical applications using the aviation industry as an example, and talk through the importance of factors such as data quality, model stability, robustness, interpretability, and accuracy. We also explore formal verification methods, abstract transformer layers, transformer-based architectures, and the application of various software testing techniques. Lucas also introduces the field of constrained deep learning and convex neural networks and its benefits and trade-offs. The complete show notes for this episode can be found at https://twimlai.com/go/705.