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What is Voyager SDK?

The Voyager SDK is crafted specifically for edge-based Computer Vision, enabling clients to seamlessly deploy AI solutions that are customized to their operational requirements on edge devices. Users of the SDK have the ability to merge their applications into the Metis AI platform and execute them on Axelera’s powerful Metis AI Processing Unit (AIPU), whether the applications utilize proprietary models or widely recognized industry frameworks. With its all-encompassing end-to-end integration, the Voyager SDK guarantees API compatibility with existing industry benchmarks, thereby optimizing the performance of the Metis AIPU and facilitating the rapid and smooth deployment of high-performance AI applications. Developers can define their entire application workflows with a straightforward, high-level declarative language called YAML, which supports one or more neural networks along with relevant pre- and post-processing tasks, including sophisticated image processing methods. This strategy not only streamlines the development process but also improves the effectiveness of implementing intricate AI solutions in practical situations. Additionally, the SDK empowers developers to innovate rapidly, fostering an environment where advanced AI technologies can be harnessed to solve real-world challenges efficiently.

What is Qualcomm Cloud AI SDK?

The Qualcomm Cloud AI SDK is a comprehensive software package designed to improve the efficiency of trained deep learning models for optimized inference on Qualcomm Cloud AI 100 accelerators. It supports a variety of AI frameworks, including TensorFlow, PyTorch, and ONNX, enabling developers to easily compile, optimize, and run their models. The SDK provides a range of tools for onboarding, fine-tuning, and deploying models, effectively simplifying the journey from initial preparation to final production deployment. Additionally, it offers essential resources such as model recipes, tutorials, and sample code, which assist developers in accelerating their AI initiatives. This facilitates smooth integration with current infrastructures, fostering scalable and effective AI inference solutions in cloud environments. By leveraging the Cloud AI SDK, developers can substantially enhance the performance and impact of their AI applications, paving the way for more groundbreaking solutions in technology. The SDK not only streamlines development but also encourages collaboration among developers, fostering a community focused on innovation and advancement in AI.

Media

Media

Integrations Supported

PyTorch
Airstack
Amazon Web Services (AWS)
Cirrascale
Docker
EndoAim
GIGABYTE Rack Server
HPE Apollo
Hugging Face
ONNX
TensorFlow

Integrations Supported

PyTorch
Airstack
Amazon Web Services (AWS)
Cirrascale
Docker
EndoAim
GIGABYTE Rack Server
HPE Apollo
Hugging Face
ONNX
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

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

Axelera AI

Date Founded

2021

Company Location

The Netherlands

Company Website

axelera.ai/ai-software

Company Facts

Organization Name

Qualcomm

Company Website

www.qualcomm.com/developer/software/cloud-ai-sdk

Categories and Features

Computer Vision

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

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

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