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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
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‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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EEG Correlates of Decision-Making and Preparation of Saccades in Human

International Journal of Psychology. 2014. Vol. 1. No. 1. P. 68–73.
Moiseeva V., Slavutskaya M., Kotenev A., Karelin S., Shulgovskiy V.

A modificated version of experimental   scheme "double step" was used to study the decision- making process in saccade programming. Two short visual    stimuli were presented sequentially in opposite hemifields    (scheme pulse overshoot). The “pattern” of response    (double saccade or single saccade at the second target) and    latency of the first saccade depended on the duration of    the first stimulus (150 or 50 ms). Positive ERP components    were revealed within the interval 100 - 120 ms before    the saccade onset by using the method of selective EEG    averaging. These potentials can be considered as markers    of the decision-making process. The parameters and    topography of these components indicate involvement of    the frontal-parietal neural network of saccadic control and    frontal-parietal-and medial-thalamic activation systems of    selective attention at the stage of decision-making process.

Priority areas: humanitarian
Language: English
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Keywords: decision-makingпринятие решениявызванные потенциалыERPspositive componentsaccade programmingпозитивный компонентсаккадические движения глаз
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