Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
ModelArts, an all-encompassing AI development platform from Huawei Cloud, is crafted to optimize the complete AI workflow for both developers and data scientists. This platform encompasses a comprehensive toolchain that facilitates various phases of AI development, including data preprocessing, semi-automated data labeling, distributed training, automated model creation, and versatile deployment across cloud, edge, and on-premises systems. It is compatible with widely used open-source AI frameworks such as TensorFlow, PyTorch, and MindSpore, while also enabling the integration of customized algorithms to meet unique project requirements. The platform's end-to-end development pipeline fosters enhanced collaboration among DataOps, MLOps, and DevOps teams, resulting in improved development efficiency by as much as 50%. Furthermore, ModelArts offers budget-friendly AI computing resources with a range of specifications, supporting extensive distributed training and accelerating inference processes. This flexibility empowers organizations to adapt their AI solutions to meet evolving business challenges effectively.
Description
SiMa presents a cutting-edge, software-focused embedded edge machine learning system-on-chip (MLSoC) platform that provides efficient, high-performance AI solutions suitable for diverse applications. This MLSoC seamlessly integrates various modalities such as text, images, audio, video, and haptic feedback, enabling it to conduct intricate ML inferences and generate outputs across any of these formats. It is compatible with numerous frameworks, including TensorFlow, PyTorch, and ONNX, and has the capability to compile over 250 different models, ensuring that users enjoy a smooth experience alongside exceptional performance-per-watt outcomes. In addition to its advanced hardware, SiMa.ai is built for comprehensive machine learning stack application development, supporting any ML workflow that customers wish to implement at the edge while maintaining both performance and user-friendliness. Furthermore, Palette's integrated ML compiler allows for the acceptance of models from any neural network framework, enhancing the platform's adaptability and versatility in meeting user needs. This combination of features positions SiMa as a leader in the rapidly evolving edge AI landscape.
API Access
Has API
No
API Access
Has API
No
Integrations
PyTorch
Yes
TensorFlow
Yes
Ascend Cloud Service
Yes
Bloomberg
No
MindSpore
Yes
ONNX
No
Integrations
PyTorch
Yes
TensorFlow
Yes
Ascend Cloud Service
No
Bloomberg
Yes
MindSpore
No
ONNX
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
Huawei Cloud
Founded
1987
Country
China
Website
www.huaweicloud.com/intl/en-us/product/modelarts.html
Vendor Details
Company Name
SiMa
Country
United States
Website
sima.ai/
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Artificial Intelligence
Chatbot
No
For Healthcare
No
For Sales
No
For eCommerce
No
Image Recognition
No
Machine Learning
No
Multi-Language
No
Natural Language Processing
No
Predictive Analytics
No
Process/Workflow Automation
No
Rules-Based Automation
No
Virtual Personal Assistant (VPA)
No