The conference will be dedicated to the reliability of AI in mathematical modelling (surrogate modelling and hybrid modelling), the strengthening of training, adversarial networks, and the stability of AI, including the difficulties of learning to transfer and merge data as well as the balance of AI. The AI standardization, verification, testing, ethical issues, and neuromorphic systems will become part of the overall conference idea.

01.07.2020 — 03.07.2020 (08:30 — 19:00)

Venue: Moscow, Skolkovo Innovation Centre, Bolshoy Boulevard, 30c1
Ribrics: Industry events

Scientists from different fields will come together to solve the problems of AI reliability in numerous applications, ranging from engineering disciplines to medical diagnostics and legal issues. Progress requires significant changes, along with a holistic approach.

Main Topics:

  • Fundamental limitations of data-driven AI (adversarial networks, cybersecurity of AI, etc.);
  • Verification and approaches to correct AI errors;
  • Data-based modelling and mathematical modelling;
  • Problems and risks of AI in medicine, banking, and law;
  • Emergent trends and fundamental issues of reliable AI (ethics of AI, singularity of AI, etc.);
  • Global aspects of AI.
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