Mircea Neagovici is VP, AI and Research at UiPath, where his team works on task mining and other ways of combining robotic process automation (RPA) with machine learning for their B2B products.

Mircea and Lukas talk about the challenges of allowing customers to fine-tune their models, the trade-offs between traditional ML and more complex deep learning models, and how Mircea transitioned from a more traditional software engineering role to running a machine learning organization.

Show notes (transcript and links): http://wandb.me/gd-mircea-neagovici

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⏳ Timestamps:

0:00 Intro

1:05 Robotic Process Automation (RPA)

4:20 RPA and machine learning at UiPath

8:20 Fine-tuning & PyTorch vs TensorFlow

14:50 Monitoring models in production

16:33 Task mining

22:37 Trade-offs in ML models

29:45 Transitioning from software engineering to ML

34:02 ML teams vs engineering teams

40:41 Spending more time on data

43:55 The organizational machinery behind ML models

45:57 Outro

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Connect with Mircea:

📍 LinkedIn: https://www.linkedin.com/in/mirceaneagovici/

📍 Careers at UiPath: https://www.uipath.com/company/careers

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💬 Host: Lukas Biewald

📹 Producers: Cayla Sharp, Angelica Pan, Sanyam Bhutani, Lavanya Shukla

Mircea Neagovici — Robotic Process Automation (RPA) and ML 46:22 Share

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Mircea Neagovici — Robotic Process Automation (RPA) and ML