We performed a comparison between Google Cloud AI Platform and IBM Watson Machine Learning based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The initial setup is very straightforward."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients."
"A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up with an operational solution really quick."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour."
"Scalability-wise, I rate the solution ten out of ten."
"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."
"It has improved self-service and customer satisfaction."
"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"The most valuable aspect of the solution's the cost and human labor savings."
"It is has a lot of good features and we find the image classification very useful."
"Customizations are very difficult, and they take time."
"One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform."
"The solution can be improved by simplifying the process to make your own models."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite."
"At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning."
"The initial setup was straightforward for me but could be difficult for others."
"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."
"In future releases, I would like to see a more flexible environment."
"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."
"The supporting language is limited."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
Google Cloud AI Platform is ranked 6th in AI Development Platforms with 7 reviews while IBM Watson Machine Learning is ranked 9th in AI Development Platforms with 6 reviews. Google Cloud AI Platform is rated 7.8, while IBM Watson Machine Learning is rated 8.0. The top reviewer of Google Cloud AI Platform writes "An AI platform AI Platform to train your machine learning models at scale, to host your trained model in the cloud, and to use your model to make predictions about new data". On the other hand, the top reviewer of IBM Watson Machine Learning writes "A highly efficient solution that delivers the desired results to its users". Google Cloud AI Platform is most compared with Microsoft Azure Machine Learning Studio, Google Vertex AI, Azure OpenAI, Hugging Face and Amazon SageMaker, whereas IBM Watson Machine Learning is most compared with Azure OpenAI and TensorFlow. See our Google Cloud AI Platform vs. IBM Watson Machine Learning report.
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