Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

AWS Deep Learning AMIs (DLAMI) offer machine learning professionals and researchers a secure and curated collection of frameworks, tools, and dependencies to enhance deep learning capabilities in cloud environments. Designed for both Amazon Linux and Ubuntu, these Amazon Machine Images (AMIs) are pre-equipped with popular frameworks like TensorFlow, PyTorch, Apache MXNet, Chainer, Microsoft Cognitive Toolkit (CNTK), Gluon, Horovod, and Keras, enabling quick deployment and efficient operation of these tools at scale. By utilizing these resources, you can create sophisticated machine learning models for the development of autonomous vehicle (AV) technology, thoroughly validating your models with millions of virtual tests. The setup and configuration process for AWS instances is expedited, facilitating faster experimentation and assessment through access to the latest frameworks and libraries, including Hugging Face Transformers. Furthermore, the incorporation of advanced analytics, machine learning, and deep learning techniques allows for the discovery of trends and the generation of predictions from scattered and raw health data, ultimately leading to more informed decision-making. This comprehensive ecosystem not only fosters innovation but also enhances operational efficiency across various applications.

Description

ExecuTorch is an open-source framework developed for PyTorch, specifically designed to deploy AI and machine learning models directly onto edge devices, facilitating tasks such as text, vision, speech, recommendation, and multimodal inference without the need for cloud connectivity. This framework allows for the exportation of models from PyTorch without any need for intermediate conversion formats, effectively maintaining ATen operators and employing ahead-of-time compilation to enhance performance tailored to specific hardware prior to deployment. Developers benefit from a modular architecture that offers flexibility in selecting both compile-time and runtime optimizations, all within the well-known PyTorch environment, which includes torchao specifically for quantization. With a lightweight C++ runtime that occupies roughly 50 KB, ExecuTorch is versatile enough to operate on a variety of platforms, including smartphones, desktops, embedded systems, microcontrollers, DSPs, and Cortex-M processors. It is compatible with multiple operating systems such as Android, iOS, Linux, Windows, macOS, and WebAssembly, and offers native APIs in C++, Swift, Kotlin, and Objective-C. As a result, ExecuTorch provides developers with a powerful tool to streamline the deployment of AI models across diverse devices and applications.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS Marketplace Yes 
AWS Neuron Yes 
Amazon EC2 G5 Instances Yes 
Amazon EC2 Inf1 Instances Yes 
Amazon EC2 P4 Instances Yes 
Amazon EC2 Trn1 Instances Yes 
Amazon EC2 Trn2 Instances Yes 
Amazon Web Services (AWS) Yes 
C++ No 
Facebook No 
Instagram No 
Kotlin No 
LLaVA No 
Llama 3.2 No 
Muse Glimmer No 
Objective-C No 
OpenAI Whisper No 
Qwen3 No 
Swift No 
Voxtral No 

Integrations

AWS Marketplace No 
AWS Neuron No 
Amazon EC2 G5 Instances No 
Amazon EC2 Inf1 Instances No 
Amazon EC2 P4 Instances No 
Amazon EC2 Trn1 Instances No 
Amazon EC2 Trn2 Instances No 
Amazon Web Services (AWS) No 
C++ Yes 
Facebook Yes 
Instagram Yes 
Kotlin Yes 
LLaVA Yes 
Llama 3.2 Yes 
Muse Glimmer Yes 
Objective-C Yes 
OpenAI Whisper Yes 
Qwen3 Yes 
Swift Yes 
Voxtral Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based No 
On-Premises Yes 
iPhone App Yes 
iPad App Yes 
Android App Yes 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

2006

Country

United States

Website

aws.amazon.com/machine-learning/amis/

Vendor Details

Company Name

ExecuTorch

Country

United States

Website

executorch.ai/

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

Alternatives

Alternatives

AWS Neuron Reviews

AWS Neuron

Amazon Web Services
AWS Neuron Reviews

AWS Neuron

Amazon Web Services
LiteRT Reviews

LiteRT

Google