AI is completely disrupting how organizations need to think about their content, whether it is customer-facing or internal. The data reveals just how profound—and significant–this disruption has become
Ain’t that the truth? When projects are easy, inexpensive, and quick they are likely to get done. Even tasks that might not be so important have a chance.
As a person who is hard of hearing (HoH), I’ve had my fair share of struggles in the business world, which has not been as inclusive as it could be. I’m not going to point fingers or cast blame, as we live in a hearing world and often just don’t
I was recently playing 20 Questions with my good friend John when it occurred to me that it has a lot in common with taxonomy—and, by extension, a solid content strategy.
Did you know that one of the best things you can do for your customers is to create less content?I know what you’re thinking. “Why is Content Rules, a company that has been creating excellent content for our customers for over 30 years, telling me to create less content?”
Recently, I have been doing a bunch of research on Retrieval Augmented Generation (RAG). RAG uses a combination of generative-based and retrieval-based artificial intelligence to produce results. Essentially, it combines what it finds with what it creates and gives you an answer to a query.
The main gist of the article is large AI companies including OpenAI, Google, and Meta are running out of training content for their AI engines. Before we talk about what they did next, let’s think about the implications of this.
Master effective writing best practices to enhance content quality across translations, structured content, and AI training.
Content automation is the practice of using systems to perform repetitive tasks to create content; such as formatting, data retrieval, and document assembly. Content automation in the pharmaceutical industry is often implemented for the following reasons: