This document discusses opportunities and challenges in knowledge discovery, engineering, and management. It identifies four opportunities: the growth of machine learning, new capabilities from cloud computing and data storage, advances in deep learning and GPUs, and integrating different types of data. It also outlines four challenges: machine learning only solving specific problems, gaps between roles like scientists and engineers, unrealistic expectations around innovation, and shortages of skilled workers.

1. Challenges and opportunities in Knowledge Discovery,
Engineering, and Management

2. Opportunity 1: growth of usage machine learning in academia and industry

3. Opportunity 2: the cloud (also offering new kinds of data storage)

4. Opportunity 3: deep learning and GPUs

5. Opportunity 4: integration of administrative and industrial data

6. Challenge 1: only very specific problems solved by machine learning

7. Challenge 2: gap between scientists, data scientists, and software engineers

8. Challenge 3: Expectations too high, not understanding innovation

9. Challenge 4: shortage of skilled people