Natalia Kuzminykh

Natalia Kuzminykh is a language engineer specializing in NLP and Generative AI development. Her primary goal is to improve communication between humans and machines, focusing on creating strong AI systems for various industries. Natalia has completed both the AI Professional Program at Stanford School of Engineering and an MSc degree in Cognitive Science from the University of Siena combining academic knowledge with practical expertise.

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LLM Prompt Best Practices For Large Context Windows

Explore the benefits and challenges of large context windows in AI, learning to design effective prompts to enhance AI performance.

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Calculating Token Counts for LLM Context Windows: A Practical Guide

How do LLM tokenizers work? Understand what they do and learn how to calculate token counts for popular large language models, with examples.

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