RAG is changing the face of generative AI by aggregating retrieval and generation to bring out precise, pertinent and ...

Generative diffusion models like Stable Diffusion, Flux, and video models such as Hunyuan rely on knowledge acquired during a ...

Things are moving quickly in AI — and if you’re not keeping up, you’re falling behind. Two recent developments are reshaping the landscape for developers and enterprises ali ...

As law firms and legal departments race to leverage artificial intelligence for competitive advantage, many are contemplating ...

RAG takes large language models a step further by drawing on trusted sources of domain-specific information. This brings clear benefits to healthcare, where access to technical and medical data is ...

RAG has revolutionised how AI systems process and respond to user queries by using external knowledge sources.

Integrating RAG in LLM-based chat systems has two main benefits, it makes sure that the model can access the current and reliable facts, and it also ensures that the users can verify that its ...

Called cache-augmented generation (CAG), this approach can be a simple and efficient replacement for RAG in enterprise settings where the knowledge corpus can fit in the model’s context window.

"When Citations is enabled, the API processes user-provided source documents (PDF documents and plaintext files) by chunking them into sentences," Anthropic says. "These chunked sentences, along with ...