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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

The Linker VisionAI Platform offers a holistic, all-in-one solution for vision AI, incorporating elements of simulation, training, and deployment to enhance the capabilities of smart cities and businesses. It is built around three essential components: Mirra, which generates synthetic data through NVIDIA Omniverse and NVIDIA Cosmos; DataVerse, which streamlines data curation, annotation, and model training with NVIDIA NeMo and NVIDIA TAO; and Observ, designed for the deployment of large-scale Vision Language Models (VLM) using NVIDIA NIM. This cohesive strategy facilitates a smooth progression from simulated data to practical application, ensuring that AI models are both resilient and flexible. By utilizing urban camera networks and advanced AI technologies, the Linker VisionAI Platform supports a variety of functions, such as managing traffic, enhancing worker safety, and responding to disasters. In addition, its comprehensive capabilities allow organizations to make well-informed decisions in real-time, significantly improving operational efficiency across diverse sectors.

Description

NVIDIA TensorRT is a comprehensive suite of APIs designed for efficient deep learning inference, which includes a runtime for inference and model optimization tools that ensure minimal latency and maximum throughput in production scenarios. Leveraging the CUDA parallel programming architecture, TensorRT enhances neural network models from all leading frameworks, adjusting them for reduced precision while maintaining high accuracy, and facilitating their deployment across a variety of platforms including hyperscale data centers, workstations, laptops, and edge devices. It utilizes advanced techniques like quantization, fusion of layers and tensors, and precise kernel tuning applicable to all NVIDIA GPU types, ranging from edge devices to powerful data centers. Additionally, the TensorRT ecosystem features TensorRT-LLM, an open-source library designed to accelerate and refine the inference capabilities of contemporary large language models on the NVIDIA AI platform, allowing developers to test and modify new LLMs efficiently through a user-friendly Python API. This innovative approach not only enhances performance but also encourages rapid experimentation and adaptation in the evolving landscape of AI applications.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

NVIDIA DRIVE
NVIDIA NIM
Amazon Web Services (AWS)
Cisco CX Cloud
Kimi K2
Kimi K2.6
LaunchX
Microsoft 365
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA DeepStream SDK
NVIDIA Jetson
NVIDIA Omniverse
NVIDIA Riva Studio
PyTorch
Python
Rosepetal AI
TensorFlow
ThinkUEM
Ultralytics

Integrations

NVIDIA DRIVE
NVIDIA NIM
Amazon Web Services (AWS)
Cisco CX Cloud
Kimi K2
Kimi K2.6
LaunchX
Microsoft 365
NVIDIA AI Enterprise
NVIDIA Clara
NVIDIA DeepStream SDK
NVIDIA Jetson
NVIDIA Omniverse
NVIDIA Riva Studio
PyTorch
Python
Rosepetal AI
TensorFlow
ThinkUEM
Ultralytics

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Linker Vision

Founded

2021

Country

China

Website

www.linkervision.com

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/tensorrt

Product Features

Computer Vision

Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration

Product Features

Alternatives

Alternatives

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