Zuzanna Dubanowska
About Zuzanna Dubanowska
Zuzanna Dubanowska is an AI Deployment Engineer known for her contributions to the understanding of AI as a service through several published articles.
AI Deployment Engineer
Zuzanna Dubanowska holds the title of AI Deployment Engineer. In this role, she specializes in the implementation and integration of artificial intelligence solutions within various business contexts. Her work involves configuring AI systems, ensuring their effective deployment, and monitoring their performance post-deployment. Her technical expertise ensures that AI technologies are seamlessly integrated into existing frameworks, contributing to operational efficiency and innovation.
AIaaS: The What, Why, And Wow of AI as a Service
Zuzanna Dubanowska authored an article titled 'AIaaS: The What, Why, And Wow of AI as a Service.' This article delves into the concept of AI as a Service (AIaaS), exploring its significance, benefits, and the impact it can have on businesses. Through this publication, she provides valuable insights into the adoption and advantages of leveraging AI solutions on a service-based model, highlighting practical applications and potential use cases.
RAG vs Fine-tuning for Your Business? Here's What You Need to Know
In her article 'RAG vs Fine-tuning for your business? Here's what you need to know,' Zuzanna Dubanowska discusses the comparative merits of Retrieval-Augmented Generation (RAG) and Fine-tuning in the context of AI deployment. This piece offers an in-depth analysis of these two methodologies, helping businesses understand which approach may be more suitable for their specific needs and objectives. It serves as a guide for decision-makers looking to optimize their AI strategy through informed choices.
Product Tutorial: Human Handoff
Zuzanna Dubanowska wrote an article titled 'Product tutorial: Human Handoff,' which provides a step-by-step guide on implementing Human Handoff processes in AI systems. This tutorial is designed to assist businesses in integrating human oversight and intervention within automated workflows, ensuring a balance between AI efficiency and human judgment. The article details practical instructions and best practices for achieving effective human-AI collaboration.