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Google Cloud AI Platform vs IBM Watson Machine Learning comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Google Cloud AI Platform
Ranking in AI Development Platforms
7th
Average Rating
7.8
Number of Reviews
8
Ranking in other categories
No ranking in other categories
IBM Watson Machine Learning
Ranking in AI Development Platforms
11th
Average Rating
8.0
Number of Reviews
7
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2024, in the AI Development Platforms category, the mindshare of Google Cloud AI Platform is 7.5%, down from 7.6% compared to the previous year. The mindshare of IBM Watson Machine Learning is 2.7%, up from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Vipul-Kumar - PeerSpot reviewer
Nov 3, 2023
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
It's a host of use cases depending on, again, the the client requirement.  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…
Anurag Mayank - PeerSpot reviewer
Mar 16, 2023
A highly efficient solution that delivers the desired results to its users
We started to use the solution for POCs in our organization. So, we are not in a state where we use its services at a full-fledged level. Additionally, we use it to solve our queries and understand whether it is actually helping us solve our problems. Basically, this is how we have been using the…

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."
"The platform's Google Vision API is particularly valuable."
"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 initial setup is very straightforward."
"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."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"We can enable and change developer productivity with artificial intelligence-recommended code based on natural language input or exciting source code."
"It is has a lot of good features and we find the image classification very useful."
"Scalability-wise, I rate the solution ten out of ten."
"It has improved self-service and customer satisfaction."
"The most valuable aspect of the solution's the cost and human labor savings."
"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"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."
 

Cons

"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."
"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 solution can be improved by simplifying the process to make your own models."
"The initial setup was straightforward for me but could be difficult for others."
"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."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"Customizations are very difficult, and they take time."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
"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."
"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."
"In future releases, I would like to see a more flexible environment."
"Sometimes training the model is difficult."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"The supporting language is limited."
 

Pricing and Cost Advice

"The price of the solution is competitive."
"For every thousand uses, it is about four and a half euros."
"The solution has an attractive starting program, which costs only 300 USD for a duration of three months. During this period, one can accomplish a lot of work on the solution."
"The pricing is on the expensive side."
"The licenses are cheap."
"The pricing model is good."
"I've only been using the free tier, but it's quite competitive on a service basis."
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Top Industries

By visitors reading reviews
Computer Software Company
14%
Financial Services Firm
11%
Manufacturing Company
10%
University
9%
Computer Software Company
15%
University
13%
Educational Organization
12%
Financial Services Firm
12%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Google Cloud AI Platform?
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...
What is your primary use case for Google Cloud AI Platform?
We use Google Cloud AI Platform to extract text from images, such as forms.
What do you like most about IBM Watson Machine Learning?
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.
What needs improvement with IBM Watson Machine Learning?
Sometimes training the model is difficult. We need to have at least a few different components to evaluate and understand the behavior of different users to have a very, very high accuracy in the m...
 

Learn More

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Overview

 

Sample Customers

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Find out what your peers are saying about Google Cloud AI Platform vs. IBM Watson Machine Learning and other solutions. Updated: October 2024.
813,418 professionals have used our research since 2012.