Russia: Cognitive Agro Pilot, an autonomous AI-based driving system for farming equipment which was designed by Sber and its ecosystem member Cognitive Pilot – has succeeded in industrial use across 35 regions of Russia when reaping the 2020 harvest. From June to October 2020, over 350 New Holland, John Deere and CLAAS autonomous combines equipped with Cognitive Agro Pilot system farmed over 160,000 hectares of field and harvested more than 720,000 tonnes of crops. With the help of Cognitive Agro Pilot as many as 590,000 metric tonnes of grain crops such as wheat, soybeans, barley, oats, sorghum, buckwheat, among others, were harvested over 130,000 hectares, and some 130,000 metric tonnes of row crops and roll crops (corn, sunflower, etc.) were harvested over 30,000 hectares in Kaliningrad, Kaluga, Kursk, Belgorod, Tambov, Penza, Rostov, Tomsk, Kurgan, Krasnodar, Krasnoyarsk and Stavropol regions. Thanks to the use of Cognitive Agro Pilot, this harvesting season stakeholders were able to save – on fuel and other related materials, shorter harvesting time (machine hours), equipment depreciation, extended active use of equipment before capital expenditures, fewer human errors, optimisation of business processes, and other parameters. According to the estimates of project members, in the next three years, every 10th harvester in Russia may become autonomous.

Scientists at the TSU Laboratory of Biophotonics, working with Tomsk National Research Medical Center (TNIMC) oncologists, have developed a new approach to the diagnosis of adenocarcinoma, a malignant tumor of the prostate gland, that uses artificial intelligence to identify oncopathology and determine the stage of the disease. Using machine learning, a computer model was taught to distinguish between healthy tissues and pathology with 100 percent accuracy. The gold standard for the diagnosis of cancer is histology, during which tissue from a patient is examined for malignant changes. So that the samples can be stored for a long time, they are dehydrated and packed in paraffin. Then experts make thin sections and examine these slides under a microscope.

Researchers at Tomsk Polytechnic University jointly with the University of Chemistry and Technology (Prague) conducted a series of experiments which proved that artificial neural networks can accurately identify DNA damage caused by UV radiation. In the future, this approach can be used in modern medical diagnostics. An article, dedicated to those studies, was published in the Biosensors and Bioelectronics journal. According to the authors, the ways UV could affect the DNA structure, especially with short-term irradiation, remain practically unstudied. UV radiation is also known to cause cancer.