A practical overview of security architectures, threat models, and controls for protecting proprietary enterprise data in retrieval-augmented generation (RAG) systems.

Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform ...

Retrieval-Augmented Generation (RAG) systems have emerged as a powerful approach to significantly enhance the capabilities of language models. By seamlessly integrating document retrieval with text ...

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 ...

The idea of the Instructed Retriever architecture is that it turns these implied conditions into explicit search parameters.

In today’s AI-first landscape, where leading companies are investing billions to scale compute capacity and processing power for large language models (LLMs), prompt engineering remains a critical ...

Artificial intelligence is evolving faster than most organizations can keep up with, and I’ve seen teams make the same mistake repeatedly: focusing on which large language model (LLM) to deploy, while ...

Everybody scrambling to get good at prompt engineering might want to take a look at a couple examples used by Microsoft engineers doing bleeding-edge research into the hot new field of multimodal ...

Azure AI Studio, while still in preview, checks most of the boxes for a generative AI application builder, with support for prompt engineering, RAG, agent building, and low-code or no-code development ...

Much of the interest surrounding artificial intelligence (AI) is caught up with the battle of competing AI models on benchmark tests or new so-called multi-modal capabilities. But users of Gen AI's ...