Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Retrieval-augmented generation (RAG) has ...

This post explores how bias can creep into word embeddings like word2vec, and I thought it might make it more fun (for me, at least) if I analyze a model trained on what you, my readers (all three of ...

In the realm of natural language processing (NLP), the concept of embeddings plays a pivotal role. It is a technique that converts words, sentences, or even entire documents into numerical vectors.

To protect private information stored in text embeddings, it’s essential to de-identify the text before embedding and storing it in a vector database. In this article, we'll demonstrate how to ...

If you have large business documents that you would like to analyze, quickly and efficiently without having to read every word. You can harness the power of artificial intelligence to answer questions ...

Image: John Tredennick, Merlin Search Technologies. Anyone who has conducted document review knows the frustration of keyword search. You craft what seems like a comprehensive list of terms, run your ...

Ocrolus, a key player focused on AI-driven document automation for faster and more accurate lending decisions, announced it has integrated GPT embeddings from OpenAI into its set of technologies. The ...

The model can quickly search documents, whether they are text-based or include images, diagrams, graphs, tables, code, diagrams, or other components. Embedding models help transform complex data — ...