If you are interested in learning more about how to use Llama 2, a large language model (LLM), for a simplified version of retrieval augmented generation (RAG). This guide will help you utilize the ...

Every few months, the enterprise AI conversation resets around the same flawed premise that better models solve the problem. When large language models hallucinate, the instinct is to reach for a ...

Aquant Inc., the provider of an artificial intelligence platform for service professionals, today introduced “retrieval-augmented conversation,” a new way for large language models to retrieve and ...

Large language models (LLMs) like OpenAI’s GPT-4 and Google’s PaLM have captured the imagination of industries ranging from healthcare to law. Their ability to generate human-like text has opened the ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Retrieval Augmented Generation (RAG) is a groundbreaking development in the field of artificial intelligence that is transforming the way AI systems operate. By seamlessly integrating large language ...

We introduce ChronoQA, a benchmark dataset for Chinese question answering focused on evaluating temporal reasoning in Retrieval-Augmented Generation (RAG) systems. Built from over 300,000 news ...

Multimodal industrial documents–such as operation manuals, circuit diagrams, and parameter tables–contain domain knowledge distributed across text, images, and document layout. However, most existing ...