Keywords: Artificial, intelligence, art, AGI , Recurrent Neural Network
We observe the success of artificial neural networks in simulating human performance on a number of tasks: such as image recognition, natural language processing, etc. However,
there are limits to state of-the-art AI that separate it from human-like intelligence. Humans can learn a new skill without forgetting what they have already learned and they can improve their activity and gradually become better learners. Today’s AI algorithms are limited in how much previous knowledge they are able to keep through each new training phase and how much they can reuse. In practice this means that it is necessary to build and adjust new algorithms to every new particular task. This is closer to a sophisticated data processing than to real intelligence. This is why research concerning generalisation are becoming increasingly important. Processes such as intuition, emotions, planning, thinking and abstraction are a part of processes, which occur in the human brain. Abstraction allows for making analogies, coding relations and relations between relations.
- Robert Lisek, Poland, Artistic Development and design Director, Institute for Research in Science and Art en.wikipedia.org/wiki/Robert_B._Lisek
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