Blog

There are two ways to accept tasks completed by performers in Toloka: automatic acceptance and non-automatic acceptance. Let's look at how these methods differ, which types of tasks they work best on, and how to review tasks with non-automatic acceptance quickly and efficiently.

Toloka went through some massive changes this week. We launched a full-scale rebrand and revealed a new logo and brand identity. Our sites and products now have a more refined, crisp look that we hope you’re enjoying as much as we are. Keep reading to find out how we went from our old daisy logo to a dandelion that’s also a bouquet of popsicles.

Neural Information Processing Systems is an annual conference that featured more than 2,000 papers when it was last held in December 2020. We have chosen six papers from the conference as essential reading in crowd science and shared our perspective on trends in crowdsourcing research.

Toloka has teamed up with Liza Alert, a volunteer search-and-rescue organization, to look for missing people in drone images. As part of the process, Tolokers can check aerial images for signs of people to boost searches in progress.

Scale your data labeling projects with Toloka Kit – an open-source Python library from Toloka! A great tool for ML engineers and data scientists who want to have more flexibility when building labeling pipelines.

The first online course on practical crowdsourcing for data labeling is now available on Coursera!

Our users have a fascinating mix of backgrounds, languages, occupations, hobbies and interests, but there is one thing they all share: Toloka fits into their lifestyle. In this post we’ll introduce you to three Tolokers from India, Brazil, and Russia.

Here at Toloka, 2021 is off to a roaring start! In this post we’ll get you up to speed on everything that’s been going on: updates we’ve made in Toloka, events we’ve participated in, and more.

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.