Yandex Data Factory, a B2B business unit which Yandex launched in 2014 to develop custom-made Big Data solutions, has developed significantly both in Russia and abroad, its CEO Jane Zavalishina said in an exchange with tech blog 150.com at an industry conference.
From its offices in Moscow and Amsterdam, Yandex Data Factory aims to make Yandex’s technologies – especially in the fields of machine learning, image and voice recognition, deep neural networks, and natural voice processing – accessible to companies needing to make sense of their accumulated mass of data and solve their business tasks.
The offer targets, in particular, such vertical sectors as mining, metals, food & beverage, oil & gas, chemicals, pharmaceutical, and other process industries.
“Our solutions deliver directly increase the productivity, reduce costs and waste, improve energy efficiency. The models are AI-enhanced in order to make the accurate predictions, real-time recommendations, and automated decisions for the most complex industrial processes,” said Zavalishina.
“Now we have a good list of customer companies in [Western Europe and Russia], among them Intel, AstraZeneca, CERN, Magnitogorsk Iron and Steel Works, Gazprom Neft, and Schlumberger.”
Yandex Data Factory is also interested in South America: “The companies over there have got very developed infrastructures already and are willing to invest into the disrupting technologies like ours.”
Asian markets, meanwhile, “still need to mature a bit, since the processing industries over there have been a bit stuck with marginal improvements and often lack the long-term vision and infrastructure,” believes Zavalishina.
“Therefore it’s harder to persuade [these Asian companies] to invest into the new and unexplored previously for them technologies,” she told 150sec.com.
Gradient boosting for free
In a separate move this month, the Russian search giant also made its advanced machine learning algorithm, CatBoost, available free of charge for developers around the globe, reports Russia Beyond The Headlines.
“CatBoost is based on gradient boosting, a machine learning technology that works very well with data from different sources,” said Anna-Veronika Dorogush, head of machine learning systems development at Yandex.
Thus the algorithm applies not only to numbers, but also to such other types of data as audio, and text or imagery, including historical data.
In weather forecasting, for example, it is important to analyze a combination of historical data, weather models and meteorological data. Yandex is already using CatBoost as a part of its weather forecasting service to improve accuracy.
