VentureBeat

Table-augmented generation shows promise for complex dataset querying, outperforms text-to-SQL

AI has transformed the way companies work and interact with data. A few years ago, teams had to write SQL queries and code to extract useful information from large swathes of data. Today, all they ...
VentureBeat

Multimodal RAG is growing, here’s the best way to get started

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more As companies begin experimenting with ...
datanami.com

AtScale Claims Text-to-SQL Breakthrough with Semantic Layer

One of the bottlenecks in getting value out of generative AI is the difficulty in turning natural language into SQL queries. Without detailed contextual understanding of the data, the text is ...
Forbes

Text-To-SQL: Making Enterprise Data More Accessible To Users

While data warehouses and cloud-native architectures have grown rapidly, business users are still finding it difficult to reach enterprise data. Even as dashboards and query tools become easier to use ...
InfoWorld

How to create your own RAG applications in R

See how to query documents using natural language, LLMs, and R—including dplyr-like filtering on metadata. Plus, learn how to use an LLM to extract structured data for text filtering. One of the ...
InfoWorld

Retrieval-augmented generation, step by step

RAG is a pragmatic and effective approach to using large language models in the enterprise. Learn how it works, why we need it, and how to implement it with OpenAI and LangChain. Typically, the use of ...
Statetechmagazine

What Is Retrieval Augmented Generation, and How Are State and Local Agencies Using It?

RAG allows government agencies to infuse generative artificial intelligence models and tools with up-to-date information, creating more trust with citizens. Phil Goldstein is a former web editor of ...