[[/public:T-719-NXAI:nxai-25:main|T-719-NXAI-2025 Main]] \\
[[/public:t-719-nxai:nxai-25:lecture_notes|Links to Lecture Notes]]

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====T-719-NXAI====

=====Learning outcomes =====
After taking the course, diligently attending the classes, and doing assignments, thoroughly reading the readings, and actively participating in discussions, students should...



===Knowledge===

...be able to describe and explain:

  * Where AI came from and what its aims are
  * The limitations of contemporary AI methodologies
  * The difference between “narrow AI” and general intelligence
  * Ongoing next-generation projects in industry and academia
  * Architectural requirements for building agents
  * The role of cognitive architecture in AI, robotics, and general machine intelligence
  * Describe potential solutions to advancing the field of AI
  * List key methodological difficulties in building advanced AI systems

===Skills===

...posses the following skills:

  * Running existing experimental AI systems
  * Programming a GMI-oriented system
  * Foresee how AI might evolve over the next few years -- even decades -- based on a variety of scientific, economic and political assumptions 

===Competence===

...have acquired the following competences:

  * Explain key components of some AML/GMI architectures, and how these relate to the creation of truly intelligent machines of the future
  * Explain key components of next-gen AI architectures
  * Describe the key cognitive processes that lack a scientific theoretical backing
  * Explain what is involved in a scientific approach to researching intelligence
  * Identify exaggeration and misunderstandings about AI in the media and online forums
  * Detect bull#*%^& in articles and general conversations about AI

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//2025(c)K.R.Thórisson//