1. AI for industries:
- Chemical
- Forest
- Pharmaceutical
- Mining
Juho Vaiste

2. The “Magical” AI
- Digitalization, automation, data analytics, simulations, mathematical analysis
- Ongoing processes from 60’s
- Basic and current forms of AI (machine learning, computer vision, natural
language processing ) as new techniques and tools
- Breakthroughs: in machine learning, computation power, the amount of data

3. Some industry-related applications
- Machine learning, deep learning, neural networks
- Ability to learn without being explicitly programmed
- Classification, regression, clustering, anomaly detection
- Computer vision
- Automating what human visual system can do
- Natural Language Processing
- Reducing workload from researchers and employees

4. Reinforcement learning and other
advanced approaches
- A learning agent taking action towards maximizing the rewards
- An approach which full capacity we don’t know yet
- AlphaGo example: finding strategies humans haven’t ever found
- Experiments in video games: AI developing abilities not designed
- Highly funded research projects, but progressing
- Change of mindset: planning and designing goals and rewards

5. Business perspective
- Greater efficiency, reducing risk
- Tailoring, specializing, rapid changes
- As a tool for new R&D discoveries
- Releasing time for creativity (learning and studying, wellbeing at work, shorter
working hours?)
Societal and ethical perspectives
- The problem of responsibility (especially in medicine)
- Adding efficiency → Easiest way is reducing the human labor

6. 1. AI for industries
➔ Mostly good old technological
progress
➔ Take time to understand (data,
digitalization, AI) and follow
research.
➔ Goal-oriented approach in the
future

7. Resources
Nokia, Siilasmaa (so, don’t worry, you aren’t late)
https://blog.networks.nokia.com/innovation/2017/11/09/study-ai-machine-learning/
MOOC-courses (Coursera, Fast.ai)
https://www.coursera.org/learn/machine-learning
http://www.fast.ai/
Stanford - One Hundred Year Study on Artificial Intelligence (2016 report)
https://ai100.stanford.edu/2016-report

8. Collaboration in Turku region
Turku AI Society
- Connects researchers and students of AI impacts
aisociety.fi
Turku.ai Meetup
- Technical perspective (approx. monthly meetup with changing topics)
turku.ai
Research: TUGS, universities
Growing number of companies (some “AI” companies)