10 questions · two minutes
1. You read a new paper about a model that breaks records in image recognition. What do you do?
2. You need to check whether a new technique genuinely improves a model. How do you design the experiment?
3. A week of training hasn’t improved the model. How do you react?
4. You’re in an international project team – you read papers, write reports and present results in English. How do you find it?
5. Your team gets a problem from an outside organisation – say, predicting machine failures – but the data is incomplete. What do you do?
6. What experience of machine learning do you bring from your Bachelor’s or from work?
7. How do you make sure someone else could repeat your experiments?
8. What gives you more satisfaction when working on AI projects?
9. Your model achieves an excellent score, but you can’t explain why it makes the decisions it does. What next?
10. What motivates you most to pursue a Master’s degree in AI Lab?
