dida at the data2day conference

dida’s ML Scientist Jakob Scharlau had a presentation at the data2day conference, where he shared insights on "Semantic Search and Machine Learning: Finding the Right Document." His talk introduced the audience to the use of machine learning and pre-trained language models to build semantic search systems that understand text contextually.

He highlighted recent advances in text embeddings and large language models (LLMs), and provided a technical overview of modern approaches to building tailored search solutions. Using examples from real-world projects, he demonstrated how these techniques are implemented to improve search accuracy and relevance.

His goal was to provide a comprehensive yet accessible introduction that would allow attendees with any level of technical expertise to gain an understanding of embedding techniques, their evolution, and live applications of domain-specific semantic search.

We sincerely thank data2day for this opportunity to contribute to the advancement of data and AI expertise in the industry.