A retrieval-augmented generation (RAG) system is built to answer strictly from the documents it retrieves. But when engineers optimize these AI pipelines end-to-end, the reader module can learn a shor [...]
As enterprise AI systems scale to handle complex workflows, practitioners face the challenge of routing subtasks to the right tools and skills. Agents can have hundreds of tools and skills and get con [...]
When an agentic AI system hands a task from a small model to a larger one — or back down again — it pays a steep tax: the receiving model has to recompute the entire conversation from scratch, dri [...]
One of the key challenges of building effective AI agents is teaching them to choose between using external tools or relying on their internal knowledge. But large language models are often trained to [...]
AI agents are now embedded in real enterprise workflows, and they're still failing roughly one in three attempts on structured benchmarks. That gap between capability and reliability is the defin [...]
Researchers at Nvidia have developed a novel approach to train large language models (LLMs) in 4-bit quantized format while maintaining their stability and accuracy at the level of high-precision mode [...]