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.
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
AI systems require big quantities of curated content to be really effective. Training an AI system with structured content produces more accurate results.
I’m a huge fan of structured content. However, I sometimes worry that structured content is my hammer and therefore all content problems look like nails.