Latest Graphwise offering bridges the gap between complex enterprise data and functional AI agents, using ontologies reduces inaccurate answers 2X in benchmarks Equally important, the company ...

Microsoft is making publicly available a new technology called GraphRAG, which enables chatbots and answer engines to connect the dots across an entire dataset, outperforming standard ...

Generative AI depends on data to build responses to user queries. Training large language models (LLMs) uses huge volumes of data—for example, OpenAI’s GPT-3 used the CommonCrawl data set, which stood ...

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

Memgraph, a leader in open-source, in-memory graph databases, is introducing a new capability designed to accelerate business adoption of graph-based retrieval-augmented generation (GraphRAG), Atomic ...

Generative language models such as ChatGPT can answer almost any question immediately and are easy to use. However, a closer look reveals a few problems. ist Data Scientist und Machine Learning ...

Through natural language queries and graph-based RAG, TigerGraph CoPilot addresses the complex challenges of data analysis and the serious shortcomings of LLMs for business applications. Data has the ...

We are in an exciting era where AI advancements are transforming professional practices. Since its release, GPT-3 has “assisted” professionals in the SEM field with their content-related tasks.