Christian Munley – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-06-10T21:45:07Z http://www.open-lab.net/blog/feed/ Christian Munley <![CDATA[Stanford Das Lab Accelerates RNA Folding Research with NVIDIA DGX Cloud]]> http://www.open-lab.net/blog/?p=96840 2025-04-17T19:35:35Z 2025-04-09T16:00:00Z The Das Lab at Stanford is revolutionizing RNA folding research with a unique approach that leverages community involvement and accelerated computing. With the...]]>

The Das Lab at Stanford is revolutionizing RNA folding research with a unique approach that leverages community involvement and accelerated computing. With the support of NVIDIA DGX Cloud through the NAIRR Pilot program, the lab gained access to 32 NVIDIA A100 DGX Cloud nodes with eight GPUs each for three months, enabling the team to transition from small-scale experiments to large-scale…

Source

]]>
Christian Munley <![CDATA[Improve AI Code Generation Using NVIDIA NeMo Agent Toolkit]]> http://www.open-lab.net/blog/?p=96937 2025-06-10T21:45:07Z 2025-03-18T19:07:50Z With the release of NVIDIA NeMo Agent toolkit��an open-source library for connecting and optimizing teams of AI agents��developers, professionals, and...]]>

With the release of NVIDIA NeMo Agent toolkit—an open-source library for connecting and optimizing teams of AI agents—developers, professionals, and researchers can create their own agentic AI applications. This tutorial shows you how to develop apps in the Agent toolkit through an example of AI code generation. We build a test-driven coding agent using LangGraph and reasoning models to scale test…

Source

]]>
1
Christian Munley <![CDATA[Accelerating Oracle Database Generative AI Workloads with NVIDIA NIM and NVIDIA cuVS]]> http://www.open-lab.net/blog/?p=88963 2024-10-28T21:54:43Z 2024-09-17T19:04:16Z The vast majority of the world's data remains untapped, and enterprises are looking to generate value from this data by creating the next wave of generative AI...]]>

The vast majority of the world’s data remains untapped, and enterprises are looking to generate value from this data by creating the next wave of generative AI applications that will make a transformative business impact. Retrieval-augmented generation (RAG) pipelines are a key part of this, enabling users to have conversations with large corpuses of data and turning manuals, policy documents…

Source

]]>
���˳���97caoporen����