Maxim Dupont

In 2025, annotation software is an inseparable part of any machine learning project. Raw materials, such as photographs, video streams, and spatial datasets, require detailed labels that train algorithms to recognize patterns. Effective labeling directly determines how well artificial intelligence performs tasks in the real world. The higher the quality

Any data collected from systems can reflect historical, social, or technical biases. If these biases remain in the training set, the model can reproduce or even amplify them in predictions, recommendations, or decisions, which can have serious consequences. Just like historical data, algorithmic decisions or human judgments that enter the

In modern AI projects, the efficiency of data annotation directly determines the speed and quality of model development. Therefore, the question is whether to build an internal team of annotators or outsource the work to an external provider. The primary difference between the two approaches is most often reflected in

AI systems deployed today cannot fully explain their decision-making processes. This is a problem as global regulations tighten. The EU AI law, which governs how organizations develop and deploy AI, requires clarity and auditability for moderate- and high-risk systems. As AI becomes increasingly complex, industry leaders acknowledge the lack of

Cross-Lingual Multimodal Understanding (CLMU) for global AI systems is a direction in AI that combines two major technologies: the recognition and integration of information from different modalities (text, images, audio, and video) and multilingual support, which is the ability to work with information in other languages without compromising accuracy. The

Modern multimedia AI models increasingly combine work with different types of data, including images, video, audio, and text. They are trained on large, multimodal datasets, where each piece of information reinforces the next. Such models learn not only to recognize individual objects or words, but also to understand the connections