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Tatiana Verbitskaya

Tatiana Verbitskaya

Tatiana Verbitskaya is a Solutions Engineer dedicated to solving complex problems. In addition to her client-facing work at Keymakr, she is also an active contributor to the computer vision community.

LLM training data quality

LLM training data quality

Data quality is essential for training large language models (LLMs). High-quality data annotation, careful dataset curation, and effective data filtering ensure the accuracy and reliability of models. Adherence to annotation standards and implementation of quality assurance systems can minimize errors, reduce bias, and improve performance in real-world applications. Quick take

Few-Shot Learning with LLMs: In-Context Learning Explained

Few-Shot Learning with LLMs: In-Context Learning Explained

The key mechanism that enables models to generate text, translate, create summaries, and solve complex tasks is Few-Shot Learning — an approach in which a model learns a new task after being shown only a few examples of how to solve it. In-Context Learning, where the model learns directly while interacting

LLM output optimization

LLM output optimization

Scaling large language systems can increase maintenance costs if memory and maintenance design are ignored. Stacking transformer layers improves accuracy but also increases memory usage and the cost per call. Decoder-only models process tokens in two stages during model inference: a pre-fill stage that relies on GPU computation and a

Complete Guide to LLMs for Synthetic Data

Complete Guide to LLMs for Synthetic Data

The modern development of many artificial intelligence models requires volumes of information that exceed all available supplies of high-quality content on the internet. Synthetic generation is becoming the only way to provide algorithms with the fuel they need for training. Since synthetic data does not belong to real individuals, its

Training LLMs for Code Generation: Data, Evaluation & Best Practices

Training LLMs for Code Generation: Data, Evaluation & Best Practices

In today’s AI world, large language models are becoming powerful tools not only for natural language processing but also for automatic code generation. The ability of models to deliver functional software solutions opens new horizons for developers, accelerating development, testing, and integration. However, the effectiveness of such models largely

LLM legal: AI language models for law firms and legal automation

LLM legal: AI language models for law firms and legal automation

In modern legal practice, the speed of information processing, the accuracy of analysis, and workflows are becoming the main factors of competitiveness. Legal LLM for law firms open up new automation opportunities for quickly processing large volumes of documents, contract analysis, and predicting case law AI. They combine a deep

AI Language Models in Healthcare Compliance

AI Language Models in Healthcare Compliance

The integration of LLMs into the healthcare sector has become a natural response to the growing volume of medical information. Modern medicine generates a colossal amount of unstructured data, most of which is stored in text format. The ability of AI to effectively process, analyze, and systematize these arrays allows