Andrey Nechesov, Evgenii Vityaev, Dmitry Sviridenko, Sergey Goncharov
Artificial intelligence systems are now integral to virtually every facet of our
lives, exhibiting an ability to reason and solve problems within defined formal
frameworks. However, challenges remain, particularly the issue of hallucination—where AI systems generate incorrect or misleading information. This paper
proposes a task-based approach to building reliable AI systems, focusing on the
task itself and the criteria necessary for its resolution. Our objective is to ensure
that AI systems not only provide solutions but also possess an understanding of
the underlying limitations of the problem. This includes identifying the axioms
and theorems involved, allowing the solution process to be informed by a clear
comprehension of the problem’s structure and constraints.