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AI for industries: chemical, forest, pharmaceutical, mining


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A presentation on the current situation with AI from the industry-specific perspective. Industries: chemical, forest, pharmaceutical, mining.

Published in: Technology
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AI for industries: chemical, forest, pharmaceutical, mining

  1. 1. AI for industries: - Chemical - Forest - Pharmaceutical - Mining Juho Vaiste
  2. 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. 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. 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. 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. 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. 7. Resources Nokia, Siilasmaa (so, don’t worry, you aren’t late) MOOC-courses (Coursera, Stanford - One Hundred Year Study on Artificial Intelligence (2016 report)
  8. 8. Collaboration in Turku region Turku AI Society - Connects researchers and students of AI impacts Meetup - Technical perspective (approx. monthly meetup with changing topics) Research: TUGS, universities Growing number of companies (some “AI” companies)