comprehension technology

ABOUT THE CONTEST

The Up Great technology contest READ//ABLE is designed to stimulate the development of new approaches to machine learning to let the artificial intelligence to understand deeply the meaning of the text and to analyze the causal relationships in a wide range of topics.

To complete the task, participants will have to go beyond the typical processing of statistical data and developing of predictions based on them.

New technologies will significantly improve the interaction between a computer and a human, create tools for a more efficient solving a wide range of intelligent tasks.

The competition is held as part of the Up Great technology contests, an instrument for the formation and support of teams engaged in the search for qualitatively new solutions in various fields.

PRIZE PURSE
₽100
million
* The award paid out from the federal budget may only be paid to Russian entities and individuals — tax residents of the Russian Federation.
*The bonus can only be paid to tax residents of the Russian Federation from the Federal budget
TECHNOLOGICAL BARRIER

TECHNOLOGICAL BARRIER

Development of a stably working software package for identifying factual and semantic errors in academic essays, the result of which corresponds to the result of a specialist's work in a limited period of time.

TASK

To develop an AI product capable of successfully identifying semantic and factual errors in an academic essay at the specialist level within the limited time.

The volume of each essay is no more than 12,000 characters.

Solution time - no more than 30 seconds per essay.

CONTEST TIMELINE

Contest is held until December 2022 and is divided into cycles. Each cycle consists of registration, qualification and final stages.
If the technological barrier is not overcome in the current cycle, the next one is launched.
First cycle takes place during autumn 2020.
Registration is available anytime.
FIRST CYCLE
11.12.2019 – 29.10.2020
Registration for the 1st cycle
01.10 – 02.11.2020
Qualification 1st cycle
09.11.2020
Tests for texts in Russian
16.11.2020
Tests for texts in English
mid December
1st cycle results announced
LATEST NEWS
17.11.2020
Second lecture of our course on deep learning with Jürgen Schmidhuber, Scientific Director, Swiss AI Lab: “ Deep Feedforward Neural Networks
16.11.2020
1st cycle tests for texts in English took place. 8 teams participated. Official results to be announced in mid December.
09.11.2020
We launched a course on deep learning with Jürgen Schmidhuber, Scientific Director, Swiss AI Lab IDSIA. Lecture one “ How does pattern recognition work”.
09.11.2020
1st cycle tests for texts in Russian took place. 9 teams participated. Official results to be announced in mid December.

EXPERTS

Keep track of tests’ progress and monitor compliance with regulations
Fix the process and results of the tests
Verify the results of AI systems of participants
Do not provide expert support to participants
Konstantin Vorontsov
Konstantin Vorontsov
Head of the MIPT Machine Intelligence Laboratory, Ph.D.
Valentin Malykh
Valentin Malykh
Senior Research Scientist at Huawei Hoah's Ark lab
Tatiana Shavrina
Tatiana Shavrina
Team Lead, R&D in NLP – Sberbank, HSE Linguistics Department
Anastasia Kishkun
Anastasia Kishkun
Data scientist at Sber (computer vision specialist), Skoltech PhD student (Data science in Mobile Robotics)
Dmitry Abulkhanov
Dmitry Abulkhanov
NLP researcher at Huawei Hoah's Ark lab
Oleg Golubev
Oleg Golubev
Computer science teacher at leading schools in Moscow, coordinator of the program "Robotics: Engineering and Technical Personnel of Russia"
Oksana Ganabova
Oksana Ganabova
Teacher of Russian language and literature, finalist of the Moscow Teacher of the Year 2005 competition, senior examiner of the Unified State Exam in Russian
Alina Mikanba
Alina Mikanba
English language teacher, expert in USE
Yelena Saplina
Yelena Saplina
Social studies teacher, Chairman of the Subject Commission of the Unified State Exam on social studies in Moscow
Bakhargul Yunusova
Bakhargul Yunusova
Russian language teacher
Alex Malyshev
Alex Malyshev
Executive Officer at Steinbeis AI
Diana Fadeeva
Diana Fadeeva
History teacher, Deputy Chairman of the Subject Commission on the History of Moscow
Yulia Yevseeva
Yulia Yevseeva
English teacher, expert in Unified State Exam in English
Rimma Yusupova
Rimma Yusupova
English teacher, expert in Unified State Exam in English

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