Punnam Raju Manthena, Co-Founder & CEO at Tekskills Inc. Partnering with clients across the globe in their digital transformation journeys. Retrieval-augmented generation (RAG) is a technique for ...

Rahul is the Chief Product and Marketing Officer for Innodata, a global data engineering company powering next-generation AI applications. Generative AI is transforming industries and lives. It ...

The hallucinations of large language models are mainly a result of deficiencies in the dataset and training. These can be mitigated with retrieval-augmented generation and real-time data. Artificial ...

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 ...

What is Retrieval-Augmented Generation (RAG)? Retrieval-Augmented Generation (RAG) is an advanced AI technique combining language generation with real-time information retrieval, creating responses ...

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 ...

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 ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Today’s large language models (LLMs) are increasingly complex, but often, ...

RAG is a recently developed process to ingest, chunk, embed, store, retrieve and feed first-party data into AI models. Here’s how to use these tools to inject first-party data into your next ...

In the communications surrounding LLMs and popular interfaces like ChatGPT the term ‘hallucination’ is often used to reference false statements made in the output of these models. This infers that ...