Blog

To make it easier and faster to launch projects in Toloka, we developed a new tool called Template Builder. You don't need any programming skills to design projects here. Template Builder is a convenient interface editor in JSON format with everything you need.

In this post, we cover a recent talk by Ivan Stelmakh, who presented his research with Nihar Shah and Aarti Singh on the importance of principled design of human decision-making systems.

We ran a survey to learn more about the Toloka community and gathered responses from over 500,000 Tolokers. Here's what we discovered.

The clarity and quality of the interface can affect how many people will respond to a given task, and how quickly and effectively they will complete it. In this post we have compiled a set of guidelines for effective interfaces.

In this post we'll talk about how the self-driving cars learn to see the world around them — what kind of data is collected, how it is processed, what algorithms are used, and the role Toloka plays.

Most chatbots aren’t that good at actually chatting and making small talk, but Toloka can help fix that. In this post, we'll tell you how.

In this post we’ll share how the DeepHD technology was developed, and how Toloka users helped with the process along the way.

Yandex.Fuel is growing fast, even more in outlying areas than in major cities. To find out how effective their gas station branding campaign is, Yandex.Fuel turned to Toloka.

Large companies are mentioned in social media thousands times a day. They need a tool to automate mention filtering. In this article we'll share how Toloka helps Yandex to analyze mentions and find only ones that need a quick response.

Toloka helps Yandex.Taxi to provide vehicle photo check to assess its external and internal condition. The purpose of this check is to decide whether the driver should be allowed to take orders

Yandex uses Toloka to label tens of thousands images needed to train neural network to distinguish surrounding objects in the cities of Russia.

Ozon uses Toloka to evaluate the quality of the new search engine, to determine the most effective ranking model and to improve the quality of the search algorithm using machine learning.

In this post, we'll share our insights on quality control in Toloka. To gauge the overall quality of the markup, we propose using post-hoc rating probability. We'll be calling this metric consistency.