ZDNet

Want generative AI LLMs integrated with your business data? You need RAG

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...
VentureBeat

Vector database company Qdrant wants RAG to be more cost-effective

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More More companies are looking to include retrieval augmented generation (RAG ...
techtimes

How RAG and Vector Databases Improve LLMs

Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) are two distinct yet complementary AI technologies. Understanding the differences between them is crucial for leveraging their ...
Computerworld

How RAG makes generative AI tools even better

Retrieval augmented generation, or 'RAG' for short, creates a more customized and accurate generative AI model that can greatly reduce anomalies such as hallucinations. As more organizations turn to ...
VentureBeat

Vectorize debuts agentic RAG platform for real time enterprise data

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 While vector databases are now increasingly ...
CRN

Infinidat Introduces RAG AI Data Services

‘We work with [customers’ file data] to accelerate the process of learning and help avoid hallucination. We are targeting on-prem data. So this is not designed to go search the web or anything. That’s ...
Computer Weekly

RAG AI: ‘Do it yourself,’ says NYC data scientist

Organisations should build their own generative artificial intelligence-based (GenAI-based) on retrieval augmented generation (RAG) with open source products such as DeepSeek and Llama. This is ...
InfoWorld

Teradata adds Enterprise Vector Store to augment RAG

Teradata’s partnership with Nvidia will allow developers to fine-tune NeMo Retriever microservices with custom models to build document ingestion and RAG applications. Teradata is adding vector ...
dbta

Augmenting Applications with Vector Search and RAG

AI is undoubtedly a formidable capability that poses to bring any enterprise application to the next level. Offering significant benefits for both the consumer and the developer alike, technologies ...
TechCrunch

Voyage AI is building RAG tools to make AI hallucinate less

AI tends to make things up. That’s unappealing to just about anyone who uses it on a regular basis, but especially to businesses, for which fallacious results could hurt the bottom line. Half of ...
dbta

Bringing Your Own Data to Generative AI with RAG

However, when it comes to adding generative AI capabilities to enterprise applications, we usually find that something is missing—the generative AI programs simply don't have the context to interact ...
InfoWorld

Using the Pinecone vector database in .NET

If you’re building generative AI applications, you need to control the data used to generate answers to user queries. Simply dropping ChatGPT into your platform isn’t going to work, especially if ...