POMA AI Achieves Best-in-Class RAG Chunking and Document Ingestion With 77% Token Reduction vs. Conventional Models

Out of the box,POMA PrimeCut uses 77% fewer tokens than conventional models. The figure rises to 83% when used in customized ...
VentureBeat

New technique makes RAG systems much better at retrieving the right documents

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 ...
eWeek

What is Retrieval-Augmented Generation? How it Works & Use Cases

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
Search Engine Land

How generative information retrieval is reshaping search

Search is dead, long live search! Search isn’t what it used to be. Search engines no longer simply match keywords or phrases in user queries with webpages. We are moving well beyond the world of ...
VentureBeat

Mistral launches new code embedding model that outperforms OpenAI and Cohere in real-world retrieval tasks

With demand for enterprise retrieval augmented generation (RAG) on the rise, the opportunity is ripe for model providers to offer their take on embedding models. French AI company Mistral threw its ...
InfoWorld

What is retrieval-augmented generation? More accurate and reliable LLMs

Retrieval-augmented generation, or RAG, integrates external data sources to reduce hallucinations and improve the response accuracy of large language models. Retrieval-augmented generation (RAG) is a ...