Google Cloud AI Platform vs IBM Watson Machine Learning comparison

Google and IBM are both solutions in the AI Development Platforms category. Google is ranked #7 with an average rating of 7.8, while IBM is ranked #11 with an average rating of 8.5. Google holds a 7.3% mindshare in AIDP, compared to IBM’s 2.6% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Google Cloud AI Platform

Read 8 Google Cloud AI Platform reviews

3,699 Views
2,842 Comparison Views

100% willing to recommend

IBM Watson Machine Learning

Read 7 IBM Watson Machine Learning reviews

1,348 Views
1,008 Comparison Views

100% willing to recommend

Google Cloud AI Platform

IBM Watson Machine Learning

Comparison Buyer's Guide

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Executive Summary

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.

To learn more, read our detailed Google Cloud AI Platform vs. IBM Watson Machine Learning Report (Updated: October 2024).

Buyer's Guide

Google Cloud AI Platform vs. IBM Watson Machine Learning

October 2024

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Categories and Ranking

Google Cloud AI Platform

Ranking in AI Development Platforms

7th

Average Rating

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

IBM Watson Machine Learning

Ranking in AI Development Platforms

11th

Average Rating

8.0

Reviews Sentiment

7.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of November 2024, in the AI Development Platforms category, the mindshare of Google Cloud AI Platform is 7.3%, down from 7.5% compared to the previous year. The mindshare of IBM Watson Machine Learning is 2.6%, 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

CTO at Intelli AI LLC

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

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.

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Anurag Mayank

Manager at Maruti Suzuki India Limited

A highly efficient solution that delivers the desired results to its users

I had not considered how the solution could be improved because I was focused on how it was helping me to solve my issues. 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. It would be beneficial to incorporate more AI into the solution.

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Quotes from Members

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

Pros

"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."

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

"The solution is able to read 90% of the documents correctly with a 10% error rate."

"The platform's Google Vision API is particularly valuable."

"The initial setup is very straightforward."

"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."

"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."

"It is has a lot of good features and we find the image classification very useful."

"We can enable and change developer productivity with artificial intelligence-recommended code based on natural language input or exciting source code."

"The most valuable aspect of the solution's the cost and human labor savings."

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."

"Improvements in text extraction accuracy and pricing adjustments would be helpful."

"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."

"Customizations are very difficult, and they take time."

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

"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."

"The supporting language is limited."

"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."

"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."

"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."

"Sometimes training the model is difficult."

Pricing and Cost Advice

"The licenses are cheap."

"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."

"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

15%

Financial Services Firm

11%

Manufacturing Company

10%

University

Computer Software Company

14%

University

14%

Financial Services Firm

12%

Educational Organization

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...

See all answers

What is your experience regarding pricing and costs for Google Cloud AI Platform?

The pricing is on the expensive side.

See all answers

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.

See all answers

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.

See all answers

What is your experience regarding pricing and costs for IBM Watson Machine Learning?

The solution is expensive.

See all answers

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...

See all answers

Comparisons

Azure OpenAI vs Google Cloud AI Platform

Compared 28% of the time

Microsoft Azure Machine Learning Studio vs Google Cloud AI Platform

Compared 14% of the time

Hugging Face vs Google Cloud AI Platform

Compared 13% of the time

Google Vertex AI vs Google Cloud AI Platform

Compared 10% of the time

Amazon SageMaker vs Google Cloud AI Platform

Compared 5% of the time

More Google Cloud AI Platform Competitors

Azure OpenAI vs IBM Watson Machine Learning

Compared 20% of the time

TensorFlow vs IBM Watson Machine Learning

Compared 10% of the time

IBM Watson Studio vs IBM Watson Machine Learning

Compared 4% of the time

More IBM Watson Machine Learning Competitors

Product Reports

Buyer's Guide

AI Development Platforms

November 2024

Download Google Cloud AI Platform product report

Buyer's Guide

AI Development Platforms

November 2024

Download IBM Watson Machine Learning product report

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Google

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IBM

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.

IBM Watson Machine Learning helps data scientists and developers accelerate AI and machine-learning deployment. With its open, extensible model operation, Watson Machine Learning helps businesses simplify and harness AI at scale across any cloud.

Sample Customers

Carousell

Information Not Available

Buyer's Guide

Google Cloud AI Platform vs. IBM Watson Machine Learning

October 2024

Free Report: Google Cloud AI Platform vs. IBM Watson Machine Learning

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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.