Blog

T-RAG = RAG + Fine-Tuning + Entity Detection- Discover T-RAG, a powerful model that combines RAG, fine-tuning, and entity detection for better AI accuracy.

Beyond Chain-of-Thought LLM Reasoning This approach can be implemented on a prompt level and does not require any dedicated frameworks or pre-processing.

A recent study, focusing on the healthcare & preoperative medicine compared expert human feedback with LLM generation and RAG enhanced responses.

In this article I illustrate how to achieve intent alignment by making use of the Kore.ai XO Platform Intent Discovery Tool.

A Chain-of-Thought is only as strong as its weakest link; a recent study from Google Research created a benchmark for Verifiers of Reasoning Chains

Seven RAG Engineering Failure Points Retrieval-Augmented Generation (RAG) systems remains a compelling solution to the challenge of relevant up-to-date reference data at inference time. Integrating retrieval mechanisms with the generative capabilities of LLMs & RAG systems can synthesise accurate, up-to-date and contextually relevant information.