Getting your data right for AI [Webinar]

In this webinar, Harpreet Singh Riat, SciBite’s Director of Technical Sales talks about the challenges and solutions associated with using large language models (LLMs) when answering questions for Life Sciences research. He specifically focuses on the importance of adhering to the FAIR principle when preparing data. The talk sheds light on the limitations of LLMs, but also highlights their benefits in text summarization and language understanding, and how coupling with Retrieval Augmented Generation (RAG) and ontologies based data enrichment will enhance the accuracy of answers provided by LLMs.

Webinar Highlights:

• Challenges of using LLMs, including issues related source credibility and data accuracy caused by hallucinations etc.
• The significance of the FAIR (Findable, Accessible, Interoperable, and Reusable) principle in data preparation.
• Retrieval Augmented Generation (RAG) coupled with Ontologies based document retrieval as a means to enhance the accuracy of answers from LLMs.

If you’re interested in delving further into these insights and learning how to ensure your data is right, contact SciBite and find out more about our solutions and how they can help you enhance data accuracy in your specific domain.