As AI becomes increasingly integrated into all industries, organizations are striving to ensure that the insights generated by AI systems are reliable, accurate, and grounded in truth. Achieving trustworthy AI requires not only robust algorithms but also careful attention to the quality and structure of the information fed into them.

Training sets for large language models (LLMs) is changing how we think about copyright but the law hasn’t quite caught up yet. In this sharp, timely webinar, legal experts unpack the evolving landscape of fair use as it applies to generative AI: What counts as truly “transformative”?

Recently Dipo Ajose-Coker, RWS; Marianne Calilhanna, DCL; and Sarah O'Keefe, Scriptorium discussed how to future-proof content, teams, and tech stack by effectively leveraging AI.

DCL's power trio Mark, Tammy, and Rich discuss how organizations can mitigate AI hallucinations.

DCL developers curated a selection of insightful articles and resources that provide a general overview AND delve deeper into RAG technology

RAG is a technique that allows LLMs to incorporate external information from a corpus of documents during the text generation process.

from The Content Strategy Experts— a Scriptorium podcast Rich Dominelli is a system architect at DCL. Rich recently sat down with The...

AI art generated via Hotpot. The prompt was "Picture of a talking robot that evokes the uncanny valley feeling." OpenAI recently...

I find myself reflecting on the many industry changes I’ve witnessed since DCL first opened for business in 1981.

Data harvesting is the process of programmatically combing through content posted online, collecting specific and relevant information, then