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What is VMware Private AI Foundation?

VMware Private AI Foundation is a synergistic, on-premises generative AI solution built on VMware Cloud Foundation (VCF), enabling enterprises to implement retrieval-augmented generation workflows, tailor and refine large language models, and perform inference within their own data centers, effectively meeting demands for privacy, selection, cost efficiency, performance, and regulatory compliance. This platform incorporates the Private AI Package, which consists of vector databases, deep learning virtual machines, data indexing and retrieval services, along with AI agent-builder tools, and is complemented by NVIDIA AI Enterprise that includes NVIDIA microservices like NIM and proprietary language models, as well as an array of third-party or open-source models from platforms such as Hugging Face. Additionally, it boasts extensive GPU virtualization, robust performance monitoring, capabilities for live migration, and effective resource pooling on NVIDIA-certified HGX servers featuring NVLink/NVSwitch acceleration technology. The system can be deployed via a graphical user interface, command line interface, or API, thereby facilitating seamless management through self-service provisioning and governance of the model repository, among other functionalities. Furthermore, this cutting-edge platform not only enables organizations to unlock the full capabilities of AI but also ensures they retain authoritative control over their data and underlying infrastructure, ultimately driving innovation and efficiency in their operations.

What is NVIDIA TensorRT?

NVIDIA TensorRT is a powerful collection of APIs focused on optimizing deep learning inference, providing a runtime for efficient model execution and offering tools that minimize latency while maximizing throughput in real-world applications. By harnessing the capabilities of the CUDA parallel programming model, TensorRT improves neural network architectures from major frameworks, optimizing them for lower precision without sacrificing accuracy, and enabling their use across diverse environments such as hyperscale data centers, workstations, laptops, and edge devices. It employs sophisticated methods like quantization, layer and tensor fusion, and meticulous kernel tuning, which are compatible with all NVIDIA GPU models, from compact edge devices to high-performance data centers. Furthermore, the TensorRT ecosystem includes TensorRT-LLM, an open-source initiative aimed at enhancing the inference performance of state-of-the-art large language models on the NVIDIA AI platform, which empowers developers to experiment and adapt new LLMs seamlessly through an intuitive Python API. This cutting-edge strategy not only boosts overall efficiency but also fosters rapid innovation and flexibility in the fast-changing field of AI technologies. Moreover, the integration of these tools into various workflows allows developers to streamline their processes, ultimately driving advancements in machine learning applications.

Media

Media

Integrations Supported

CUDA
Hugging Face
NVIDIA DRIVE
NVIDIA NIM
Kimi K2
Kimi K2.5
Kimi K2.7 Code
Kimi K3
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA Riva Studio
NVIDIA virtual GPU
PostgreSQL
PyTorch
RankGPT
RankLLM
Rosepetal AI
TensorFlow
Thunder Compute
VMware Cloud

Integrations Supported

CUDA
Hugging Face
NVIDIA DRIVE
NVIDIA NIM
Kimi K2
Kimi K2.5
Kimi K2.7 Code
Kimi K3
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA Riva Studio
NVIDIA virtual GPU
PostgreSQL
PyTorch
RankGPT
RankLLM
Rosepetal AI
TensorFlow
Thunder Compute
VMware Cloud

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Pricing Information

Free
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

VMware

Date Founded

1998

Company Location

United States

Company Website

www.vmware.com/products/cloud-infrastructure/private-ai-foundation-nvidia

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/tensorrt

Categories and Features

Categories and Features

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