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

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Kandungan disediakan oleh TWIML and Sam Charrington. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh TWIML and Sam Charrington atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

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.

  continue reading

744 episod

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iconKongsi
 
Manage episode 445185988 series 2355587
Kandungan disediakan oleh TWIML and Sam Charrington. Semua kandungan podcast termasuk episod, grafik dan perihalan podcast dimuat naik dan disediakan terus oleh TWIML and Sam Charrington atau rakan kongsi platform podcast mereka. Jika anda percaya seseorang menggunakan karya berhak cipta anda tanpa kebenaran anda, anda boleh mengikuti proses yang digariskan di sini https://ms.player.fm/legal.

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.

  continue reading

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