The Center for Technologies and Society

A project by the Center for Technologies and Society and Southern Federal University to develop an intelligent research agent based on a large language model to accelerate the analysis of X-ray spectra of catalysts.

The Peterhof Museum-Reserve has implemented an AI system from Yandex Cloud and GlowByte to reduce queues and increase throughput. The solution uses modeling for route generation and infrastructure placement.

The Petrov Research Institute of Oncology has started using a YandexGPT-based solution to process applications for ethical approval of clinical trials, which now takes minutes instead of weeks.

Together with scientists from the Far Eastern Federal University and students from the School of Data Analysis, we created and trained a neural network that determines the volume, mass, and types of garbage. It helps environmental control services and volunteers to simplify waste collection on coastal areas.

Read about how a joint project between Yandex Cloud and Saint Petersburg State University helps assess the dynamics of stickleback populations, study reservoirs’ ecosystems, and better understand fish population sizes.

Together with Yandex Cloud, astrophysicists automated data analysis and created the largest catalog of dwarf star flares, which will help scientists better understand the nature of stellar and solar flares.

Find out how the Spina Bifida Foundation supports people with the disease, what the Kulakov National Research Medical Center does in the field of pathology treatment, and how technologies and expertise from Yandex Cloud and the Yandex School of Data Analysis help identify it in early pregnancy.

Ash clouds disrupt transport accessibility, and affect human health and the ecosystem. We developed a service that helps track the spread of ash and eliminate the effects of emissions around the world faster. The technology is already in use with volcanoes in Kamchatka.

Read about how Sechenov University specialists used Yandex Cloud services to develop a medical data platform. Doctors or residents can now search for information faster, collect statistics, and upload data in just seconds.

October 23 is celebrated as International Snow Leopard Day. We created a neural network for processing data from camera traps. Denis Malikov of Saylyugemsky National Park, and Dmitry Rybalko of Yandex Cloud, tell us why scientists need this.

Read about the technologies used to extend the forecast period for meteorogical anomalies in the Pacific Ocean, and how scientists from the Higher School of Economics and the Yandex School of Data Analysis built a model that predicts El Niño.

In April of 2022, RANEPA moved all its development processes from Jira Atlassian to Yandex Tracker. More than 12,000 tasks in 25 queues were moved to the new system with Active Directory integration for seamless authorization, and business processes configured.

Using machine learning algorithms, they identified where endangered trees and other plants were growing, while farmers were able to minimize lost crops.

Scientists and researchers unveiled a neural network to monitor the Lake Baikal ecosystem on the Yandex Cloud platform, an important project for tracking how the lake is doing, assessing the local impact of climate change, and measuring fish populations.

To organize the educational process, TSU, together with a technology partner, developed the Aktru platform, a Yandex Cloud solution that allows you to record lectures with parallel transmission of different cameras aimed at the blackboard and the teacher’s presentation.

The transition to Yandex Cloud made it possible to simplify the architecture of the platform and stop supporting a proprietary load balancer in favor of Yandex’s equivalent service. Using platform services led to infrastructure expenses dropping by 50%.

The Yandex Go service team, led by Ksenia Kolesnikova, head of internal efficiency analytics, conducted a product analytics course at MIPT to find promising interns and junior specialists.

The Bauman Moscow State Technical University student racing team is one of the first in Russia to design unmanned race cars for international Formula Student competitions. The autonomous driving system of an unmanned car must recognize objects on the racetrack. To do so, they used neural networks.

Yandex Cloud partnered with the Higher School of Economics to build a digital university.