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AI technologies in digital future

Explore the latest AI research directions, definitions, classification, and applications. Learn about AI levels, weaknesses in machine learning, and state-of-the-art examples like IBM Watson and MIT GAN. Discover innovative AI projects like emotion recognition by voice and psycho-physiological correction. Uncover potential AI applications in marketing, healthcare, and public safety.

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AI technologies in digital future

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  1. AI technologiesin digital future MykytaKlymenko Institute of AI problemsMES and NAS of Ukraine

  2. Report plan Current AI research directions Main definitions, AI classification Overview of actual developments in the AI field Prerequisites for transition to a new stage of AI Future AI application possibilities

  3. AI nowadays

  4. Current AI research directions Thought processes modeling Knowledge representation and applying of it Natural language processing Robotics Machine creativity Machine learning

  5. Artificial intelligence is an algorithm of creative tasks fulfillment, formed by the artificial consciousness According to the decision of the First International Conference «Artificial Intelligence – 2000» and the Tenth Conference «Artificial Intelligence – 2010»

  6. AI levels Artificial narrow intelligence (ANI) Artificial general intelligence (AGI) Artificial superintelligence (ASI)

  7. Data became the key to AI

  8. Weaknesses of machine learning

  9. The state-of-the-art machine learning examples IBM Watson 2011 – demo 2019 – use cases

  10. The state-of-the-art machine learning examples MIT GAN Generative adversarial networks

  11. Institute of artificial intelligence problemsMES and NAS of Ukraine

  12. Institute of artificial intelligence problemsMES and NAS of Ukraine IntelligentHelmetforpsycho-physiologicalcorrection

  13. Institute of artificial intelligence problemsMES and NAS of Ukraine Target objects detecting and tracking in video stream

  14. Institute of artificial intelligence problemsMES and NAS of Ukraine The method of emotion recognition by voice Recognised emotions: Interest Joy Anger Fear Guilt Suffering Application possibilities: Marketing research Patient monitoring Public safety

  15. Institute of artificial intelligence problemsMES and NAS of Ukraine The method of emotion recognition by voice Unsolved problems: Dependence on speech context(semantic analysis) Mixed emotions (simultaneous demonstration)

  16. AI application possibilities (ASI) Perception based machine learning Social data processing NeuroNet Noosphere

  17. Thank you for your attention! Institute of artificial intelligence problemsMES and NAS of Ukraine http://ipai.net.ua ipai.kiev@gmail.com

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