Jacob Liberman – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2024-10-28T21:58:37Z http://www.open-lab.net/blog/feed/ Jacob Liberman <![CDATA[How to Take a RAG Application from Pilot to Production in Four Steps]]> http://www.open-lab.net/blog/?p=79558 2024-10-28T21:58:37Z 2024-03-18T22:00:00Z Generative AI has the potential to transform every industry. Human workers are already using large language models (LLMs) to explain, reason about, and solve...]]>

Generative AI has the potential to transform every industry. Human workers are already using large language models (LLMs) to explain, reason about, and solve difficult cognitive tasks. Retrieval-augmented generation (RAG) connects LLMs to data, expanding the usefulness of LLMs by giving them access to up-to-date and accurate information. Many enterprises have already started to explore how…

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Jacob Liberman <![CDATA[The Need for Speed: Edge AI with NVIDIA GPUs and SmartNICs, Part 2]]> http://www.open-lab.net/blog/?p=41542 2022-08-21T23:53:07Z 2021-12-01T17:00:00Z This is the second post in a two part series. The first post described how to integrate the NVIDIA GPU and Network Operators using preinstalled drivers. This...]]>

This is the second post in a two part series. The first post described how to integrate the NVIDIA GPU and Network Operators using preinstalled drivers. This post describes the following tasks: The preinstalled driver integration method is suitable for edge deployments requiring signed drivers for secure and measured boot. Use the driver container method when the edge…

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Jacob Liberman <![CDATA[The Need for Speed: Edge AI with NVIDIA GPUs and SmartNICs, Part 1]]> http://www.open-lab.net/blog/?p=41400 2022-08-21T23:53:06Z 2021-11-19T16:30:00Z NVIDIA Operators simplify GPU and SmartNIC management on Kubernetes. This post shows how to integrate NVIDIA Operators into new edge AI platforms using...]]>

NVIDIA Operators simplify GPU and SmartNIC management on Kubernetes. This post shows how to integrate NVIDIA Operators into new edge AI platforms using preinstalled drivers. This is the first post in a two-part series. The next post describes how to integrate NVIDIA Operators using custom driver containers. Today every industry uses edge AI. Servers deployed in airplanes, stores…

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Jacob Liberman <![CDATA[Accelerating Data Center AI with the NVIDIA Converged Accelerator Developer Kit]]> http://www.open-lab.net/blog/?p=39603 2023-03-22T01:16:47Z 2021-11-10T13:50:00Z The modern data center is becoming increasingly difficult to manage.?There are billions of possible connection paths between applications and petabytes of log...]]>

The modern data center is becoming increasingly difficult to manage. There are billions of possible connection paths between applications and petabytes of log data. Static rules are insufficient to enforce security policies for dynamic microservices, and the sheer magnitude of log data is impossible for any human to analyze. AI provides the only path to the secure and self-managed data…

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Jacob Liberman <![CDATA[The Future of Edge AI is Cloud-Native]]> http://www.open-lab.net/blog/?p=38176 2022-08-21T23:52:47Z 2021-10-06T16:00:00Z Inference has emerged as THE killer app for edge computing due to its flexibility. Today, inference at the edge (also called edge AI) solves problems across...]]>

Inference has emerged as THE killer app for edge computing due to its flexibility. Today, inference at the edge (also called edge AI) solves problems across every industry: preventing theft, detecting illness, and reducing herbicide use in farms. But for many, the complexity associated with managing distributed edge servers can erode the business value. An edge AI data center does not have 10…

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Jacob Liberman <![CDATA[Deploying GPUDirect RDMA on the EGX Stack with the NVIDIA Network Operator]]> http://www.open-lab.net/blog/?p=21167 2022-08-21T23:40:40Z 2020-09-30T01:30:56Z Edge computing takes place close to the data source to reduce network stress and improve latency. GPUs are an ideal compute engine for edge computing because...]]>

Edge computing takes place close to the data source to reduce network stress and improve latency. GPUs are an ideal compute engine for edge computing because they are programmable and deliver phenomenal performance per dollar. However, the complexity associated with managing a fleet of edge devices can erode the GPU’s favorable economics. In 2019, NVIDIA introduced the GPU Operator to…

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