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
7
Ranking in other categories
No ranking in other categories
IBM Watson Machine Learning
Ranking in AI Development Platforms
10th
Average Rating
8.0
Number of Reviews
6
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2024, in the AI Development Platforms category, the mindshare of Google Cloud AI Platform is 5.7%, up from 5.5% compared to the previous year. The mindshare of IBM Watson Machine Learning is 1.9%, up from 1.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
Unique Categories:
No other categories found
No other categories found
 

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…
MS
Jan 3, 2024
Good fit for medium-sized companies, and offers good AutoML feature
I'm mainly checking how easy it is to use this platform to implement products. My idea isn't very flexible, and it's quite easy to do something basic.  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…

Quotes from Members

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

Pros

"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."
"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."
"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."
"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."
"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"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."
"Scalability-wise, I rate the solution ten out of ten."
"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."
 

Cons

"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."
"Customizations are very difficult, and they take time."
"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."
"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 initial setup was straightforward for me but could be difficult for others."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"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."
"The supporting language is limited."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"In future releases, I would like to see a more flexible environment."
 

Pricing and Cost Advice

"For every thousand uses, it is about four and a half euros."
"The pricing is on the expensive side."
"The licenses are cheap."
"The price of the solution is competitive."
"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."
"I've only been using the free tier, but it's quite competitive on a service basis."
"The pricing model is good."
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Top Industries

By visitors reading reviews
Computer Software Company
13%
Financial Services Firm
12%
Manufacturing Company
10%
University
9%
Educational Organization
17%
Computer Software Company
14%
University
12%
Financial Services Firm
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
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?
It's a host of use cases depending on, again, the the client requirement.
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 is your experience regarding pricing and costs for IBM Watson Machine Learning?
I've only been using the free tier, but it's quite competitive on a service basis. Heavy data usage and management can drive up the costs, but that's true for most platforms. Ultimately, pricing sh...
What needs improvement with IBM Watson Machine Learning?
In future releases, I would like to see a more flexible environment. It's a good product for customization and developing products. But when we need the most control over the delivery, Watson isn't...
 

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: May 2024.
792,098 professionals have used our research since 2012.