Current Trends in Artificial Intelligence

Semester
Spring 2020
Credit
6
Professor
Hugues Bersini, Johan Loeckx, Luc Steels (em.)
Course description

Artificial Intelligence is moving at an incredible pace. In this course, the latest progress  in state-of-the-art AI is introduced.  Over the course of ten guest lectures, experts in their field come to talk about their latest research.  

Next to the theoretical part, in the AI challenges students will apply learnt techniques in a team, to create an AI powered application! AI challenges aims to hone students’ soft skills like teamwork, empathy, communication and critical thinking while building functional products  in agile teams.  Some examples from previous years include:

  • a garbage collecting robot
  • thorndike: an app to explain reinforcement learning 
  • kitt.ai: the on-the-road assistant for homecare nurses
  • lolo: language learning 2.0
  • iowa: cultural event recommender app
Schedule
TimePlaceRoomDate Range
13:30 – 15:30ULB (Solbosch) IRIDIA classroom (seminar room on the 5th floor) Fridays, 2nd semester
  1. 14/2  Hugues Bersini (ULB)
  2. 21/2  Hugues Bersini (ULB)
  3. 28/2 Johan Loeckx (VUB)
    • ​topic: AI, a broader perspective
    • materials: slides
  4. 6/3 Céline Vens & Konstantinos Pliakos (KULAK)
  5. 13/3 Bart Bogaerts (VUB)
    • topic: Conflict-driven clause learning
    • materials: slides / video
  6. 27/3 Benoit Decorte
  7. 3/4 Gianluca Bontempi (ULB)
  8. 24/4 Kris Heylen (KULeuven)
  9. 8/5 Matvei Tsishyn (ULB)
  10. 15/5 Robin Devooght(ULB)

Prerequisites

Introduction to AI

Machine learning

Objectives

The student is able to participatie actively in a scientific debate.

The student is aware of current trends in Artificial Intelligence en has the competence to judge different approaches and technologies.

The student can enumerate strengths and weaknesses of different AI technologies and under what circumstances they can be applied.

The student will also learn about open research questions to stimulate their own explorations in the field.

Examination

Attendance in the lectures is obliged (Friday afternoon). Each absence needs to be e-mailed beforehand.

60% of the grades come from the Start up labs programming assignment.

The other 40% come from an oral exam about the lectures.