Zafar MuhammedFounder and CEO at HiTech Solutions and Business Automation
We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"It reduces the required processing power on the CPU and GPU. With OpenVINO, you can run your normal algorithms and normal software on CPU, but don't require a huge amount of processor power. It is faster, and you have plenty of more resources for other jobs. It is easy to manage the software with OpenVINO. You can change the number of models or quotes. I can use five quotes for a model, or I can write a particular model with a quote. Management is easy without touching the software."
"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."
"Its interface is the most valuable. The ability to have an interface to train machine learning models and construct them with the high-level interface, without excess busting and reconstructing the same technical elements, is very useful."
"I like that PyTorch actually follows the pythonic way, and I feel that it's quite easy. It's easy to find compared to others who require us to type a long paragraph of code."
"Their resolution time for certain kinds of issues could be better. I had a problem during the implementation, and it took them two or three months to resolve it. I wasted so much time. If it is a simple problem or implementation issue, they will provide the answers and solve it quickly, but if there are some problems with the product, it can take time."
"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."
"There is not enough documentation about some methods and parameters. It is sometimes difficult to find information."
"I would like a model to be available. I think Google recently released a new version of EfficientNet. It's a really good classifier, and a PyTorch implementation would be nice."
"Specifically for our products, it was costly to use OpenVINO without using the OpenVINO hardware. This was because we had not used the same number of CPUs. We had reduced the CPU number, but we didn't reduce it too much. Therefore, the cost was more with OpenVINO, but the efficiency was also much higher. We didn't have any problems with CPU usage or memory usage. OpenVINO really helped us with these issues."
"We didn't have to pay for any licensing with Intel OpenVINO. Everything is available on their site and easily downloadable for free."
"It is free."
"PyTorch is an open-source solution."
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).
We've built this course as an introduction to deep learning. Deep learning is a field of machine learning utilizing massive neural networks, massive datasets, and accelerated computing on GPUs. Many of the advancements we've seen in AI recently are due to the power of deep learning. This revolution is impacting a wide range of industries already with applications such as personal voice assistants, medical imaging, automated vehicles, video game AI, and more.
In this course, we'll be covering the concepts behind deep learning and how to build deep learning models using PyTorch. We've included a lot of hands-on exercises so by the end of the course, you'll be defining and training your own state-of-the-art deep learning models.
OpenVINO is ranked 3rd in AI Development Platforms with 4 reviews while PyTorch is ranked 6th in AI Development Platforms with 2 reviews. OpenVINO is rated 8.6, while PyTorch is rated 9.0. The top reviewer of OpenVINO writes "Open-source, easy to integrate, and perfectly tailored to the Movidius chipset". On the other hand, the top reviewer of PyTorch writes "A highly user-friendly open-source machine learning library". OpenVINO is most compared with TensorFlow, Caffe, Microsoft Azure Machine Learning Studio and Google Cloud AI Platform, whereas PyTorch is most compared with .
See our list of best AI Development Platforms vendors.
We monitor all AI Development Platforms reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.