- Focus on more challenging ML problems
- Semi-supervised learning
- Domain adaptation
- Generative models
- Reinforcement learning
- NLP
- ELMO
- BERT
- Fear about AI
- GDPR, trust and privacy
- Cambridge analytica
- Facial recognition
- Tons of open sourced tooling, models
- Focus on trust and transparency
- Bias
- Regulation
- GDPR and transparency, interpretability
- What will other countries do regarding regulation?
- AI for good
- Better voice and conversational results
- AI assistants
- Voice interfaces
- NLP advances
- More focus on product development, less on research
- Deep learning will explode in production product / service development
- Computer vision, NLP, speech recognition will be table stakes
- Increased accessibility of DL to software engineers / developers
- More testing/tooling
- Better training for data scientists
- Better integrations and infrastructure
- AutoML
- Organizational / Cultural Shifts
- New roles for data-based leadership - CDO, CAIO, etc.,
- Strategy - AI becoming first-class concern
- Competitive Analysis - AI and data assessments mandatory
- Fragmentation into distinct subfields - AI, analytics, data science, prognostics
- A changing relationship between humans and automation
- AI + robotics - first steps
- Pervasive AI + IoT - first steps
- The importance of creative expertise for humans
- How to school your child today to prep for tomorrow
- Narrowly-scoped, highly-specific job functions at most risk