computer science

Toloka

Toloka is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Toloka rather than just read about it. In short: Toloka is a Dutch multinational data services company based in Amsterdam, Netherlands. It delivers human-in-the-loop annotation and evaluation work that supports the development of generative AI and large language models.

Key takeaways

Toloka belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Toloka to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Toloka from memory before moving on to harder problems.

Reference excerpt

Toloka is a Dutch multinational data services company based in Amsterdam, Netherlands. It delivers human-in-the-loop annotation and evaluation work that supports the development of generative AI and large language models. Toloka is a unit of Nasdaq-listed AI infrastructure provider Nebius Group NV. In May 2025, Jeff Bezos’ investment firm, Bezos Expeditions, led a 72 million USD funding round into the company. Mikhail Parakhin, CTO of Shopify, also participated in the round. Toloka’s clients include Amazon, Microsoft, Anthropic, Shopify, and poolside.

History Toloka was founded in 2014 by Olga Megorskaya as a crowdsourcing and microtasking platform for data markup that improved machine learning and search algorithms. As generative AI advanced, it evolved into a provider of specialized data annotation and model refinement for frontier AI developers. In 2024, the company's Russian operations were sold to Russian investors.

Services

Generative AI

Agentic AI Toloka develops data and evaluation systems that help train and assess AI agents. Its work includes RL-Gyms that let models learn through simulated tasks, along with human-in-the-loop methods that combine people and AI in shared workflows.

Machine learning On Toloka, trainers are tasked with identifying the presence or absence of objects in content, as specified by algorithms. They also assess chatbot responses within given dialogues for relevance and engagement. Additionally, translation verification tasks involve evaluating the accuracy of translations from multiple annotators. For the fine-tuning of large language models (LLMs), experts are required to generate and provide context-based prompts that can be single-turn or multi-turn, serving various domains and purposes.

Natural language processing In the natural language processing (NLP) domain, Toloka facilitates optical character recognition and classification, sentiment analysis, named-entity recognition, and search relevance evaluation. It also provides transcription and classification of audio data.

Annotators Toloka mainly works with domain experts, such as physicists, scientists, lawyers, and software engineers, to develop specialized data for models targeting niche tasks. Contributors are recruited and trained through Mindrift, Toloka’s platform for sourcing skilled participants in AI projects. The platform supports work on data annotation and model evaluation, particularly for large language models and other generative AI systems. Toloka also collaborates with freelancers, referred to as “Tolokers,” who annotate and create data for a wide range of applications, including labelling personally identifiable information, translating content, summarising text, and transcribing audio.

Research In May 2019, Toloka's research team began publishing datasets for non-commercial and academic purposes to support the scientific community and attract researchers to Toloka. Such datasets are addressed to researchers in different directions like linguistics, computer vision, testing of result aggregation models, and chatbot training. Toloka research has been showcased at a range of conferences, including the Conference on Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML) and the International Conference on Very Large Data Bases (VLDB).

Controversies

Enabling arrests of protesters via facial recognition software (March 2024) In March 2024, Toloka's Russian division was criticized for helping develop the facial recognition software used by Russia to track and arrest protesters after the death of Alexei Navalny. The company's Russian operations were sold in July 2024.

References

External links Official website

Worked examples

Example 1 — a first encounter with Toloka

Start with the simplest possible case. Write down what Toloka claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Toloka before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Toloka ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Toloka

In research: Toloka appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Toloka in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Toloka is common in secondary-school and first-year university syllabi. It links to neighbouring topics Companies based in Amsterdam, Crowdsourcing, Human-based computation, so understanding it makes those chapters shorter.
In everyday life: Look for Toloka outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Toloka in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Toloka means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Toloka out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Toloka in simple terms?

Why does Toloka matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Toloka?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Toloka.