Almost daily, I have conversations with content leaders struggling to solve complex challenges in their organizations. They’re trying to help employees find critical information scattered across multiple systems, scale content creation without ballooning costs, measure the business impact of their content investments, and ensure consistency across thousands of content assets.
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
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.
Artificial intelligence (AI) used to be something we thought about as a future need or threat. Just a couple of years ago, the impact of AI on our daily lives was indirect. Companies employed AI systems that ran behind a user interface. Even though we have interacted with AI for