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.
In this video, Mircea and the Host, Lukas Biewald, 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.
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