Compare Google Cloud AI Platform vs. OpenVINO

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Top Review
Find out what your peers are saying about Microsoft, TensorFlow, OpenVINO and others in AI Development Platforms. Updated: September 2021.
533,638 professionals have used our research since 2012.
Quotes From Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."

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"The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models.""The inferencing and processing capabilities are quite beneficial for our requirements.""The initial setup is quite simple."

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Cons
"The initial setup was straightforward for me but could be difficult for others."

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"It has some disadvantages because when you're working with very complex models, neural networks if OpenVINO cannot convert them automatically and you have to do a custom layer and later add it to the model. It is difficult.""The model optimization is a little bit slow — it could be improved.""At this point, the product could probably just use a greater integration with more machine learning model tools."

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Pricing and Cost Advice
"The price of the solution is competitive."

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"We didn't have to pay for any licensing with Intel OpenVINO. Everything is available on their site and easily downloadable for free."

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Questions from the Community
Top Answer: Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture.
Top Answer: The price of the solution is competitive.
Top Answer: In the past, I have deployed the solution for government clients wanting cloud applications and databases services.
Top Answer: The inferencing and processing capabilities are quite beneficial for our requirements.
Top Answer: We didn't have to pay anything for Intel OpenVINO, everything was available on their site. All of their solutions, inference engines, and other model optimizations are all available for free. We… more »
Top Answer: The model optimization is a little bit slow — it could be improved. They should introduce some type of deep learning accelerator, like Jetson Xavier NX. There is a lacking in vehicle recognition —… more »
Ranking
7th
Views
124
Comparisons
67
Reviews
1
Average Words per Review
138
Rating
8.0
3rd
Views
1,523
Comparisons
1,080
Reviews
3
Average Words per Review
731
Rating
8.7
Comparisons
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Google
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OpenVINO
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Overview

Google AI Platform is a managed service that enables you to easily build machine learning models, that work on any type of data, of any size. Create your model with the powerful TensorFlow framework that powers many Google products, from Google Photos to Google Cloud Speech.

OpenVINO toolkit quickly deploys applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends computer vision (CV) workloads across Intel hardware, maximizing performance. The OpenVINO toolkit includes the Deep Learning Deployment Toolkit (DLDT).

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Sample Customers
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Top Industries
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VISITORS READING REVIEWS
Manufacturing Company31%
Comms Service Provider23%
Computer Software Company18%
Educational Organization4%
Find out what your peers are saying about Microsoft, TensorFlow, OpenVINO and others in AI Development Platforms. Updated: September 2021.
533,638 professionals have used our research since 2012.

Google Cloud AI Platform is ranked 7th in AI Development Platforms with 1 review while OpenVINO is ranked 3rd in AI Development Platforms with 3 reviews. Google Cloud AI Platform is rated 8.0, while OpenVINO is rated 8.6. The top reviewer of Google Cloud AI Platform writes "Many services, priced well, and has enhanced AI architecture". On the other hand, the top reviewer of OpenVINO writes "Open-source, easy to integrate, and perfectly tailored to the Movidius chipset". Google Cloud AI Platform is most compared with , whereas OpenVINO is most compared with TensorFlow, PyTorch, Microsoft Azure Machine Learning Studio, Caffe and IBM Watson OpenScale.

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