Amazon Deep Learning AMIs vs. IBM watsonx.ai

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Deep Learning AMIs
Score 8.8 out of 10
N/A
AMIs are Amazon Machine Images, virtual appliance deployed on EC2. The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at scale. Users can launch Amazon EC2 instances pre-installed with deep learning frameworks and interfaces such as TensorFlow, PyTorch, Apache MXNet, Chainer, Gluon, Horovod, and Keras to train sophisticated, custom AI models, experiment with new algorithms, or to learn new…N/A
IBM watsonx.ai
Score 7.7 out of 10
N/A
Watsonx.ai is part of the IBM watsonx platform that brings together new generative AI capabilities, powered by foundation models, and traditional machine learning into a studio spanning the AI lifecycle. Watsonx.ai can be used to train, validate, tune, and deploy generative AI, foundation models, and machine learning capabilities, and build AI applications with less time and data.
$0
Pricing
Amazon Deep Learning AMIsIBM watsonx.ai
Editions & Modules
No answers on this topic
Essentials
$0
per month
Free Trial
$0
per month
Standard
$1,500
per month
Offerings
Pricing Offerings
Amazon Deep Learning AMIsIBM watsonx.ai
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsGet started building differentiated AI assets with watsonx.ai, our studio for generative AI, foundation models and machine learning. Scale up your AI use cases as needed with integrations to watsonx.data, a fit-for-purpose data store built on an open data lakehouse architecture, and watsonx.governance (coming soon), a toolkit to accelerate responsible, transparent and explainable AI workflows. Pricing for watsonx.ai includes: model inference per 1000 tokens and ML tools and ML runtimes based on capacity unit hours.
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Community Pulse
Amazon Deep Learning AMIsIBM watsonx.ai
Top Pros

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Top Cons

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Best Alternatives
Amazon Deep Learning AMIsIBM watsonx.ai
Small Businesses
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Medium-sized Companies
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Enterprises
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User Ratings
Amazon Deep Learning AMIsIBM watsonx.ai
Likelihood to Recommend
10.0
(2 ratings)
7.7
(4 ratings)
User Testimonials
Amazon Deep Learning AMIsIBM watsonx.ai
Likelihood to Recommend
Amazon AWS
Amazon AMIs has been very useful for the quick setup and implementation of deep learning for data analysis which is something I have used the service for in my own research. We commonly use the service to enable students to run intensive deep learning algorithms for their assessments. This service works well in this scenario as it allows students to quickly set up a suitable environment and get started with little hassle. If you are looking to run simple, surface level deep learning algorithms (kind of contradictory statement I know) then AMI is more complicated than most will need. When it comes to teaching the basics of Machine Learning, this kind of system is unnecessary and there are other alternatives which can be used. That being said this service is a must if you are looking to run complex deep learning via the cloud.
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IBM
Based on my experience, I can recommend that you have a good AI management system in your company account, and if you have the money at your disposal to invest in IBM watsonx, do not hesitate. We are using API models to obviously build a work environment with sustainable flow as well. We have AI and ML lifecycle support.
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Pros
Amazon AWS
  • Setting up environment
  • Support for different types of machines
  • Perfect for Machine Learning / Deep Learning use cases
  • Nvidia / Cuda / Conda support easily
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IBM
  • it has many Reliable tools for algorithm modeling visualization.
  • Highly secured, Integrated and all data optimized in one management
  • Easily prepared and extract data from document.
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Cons
Amazon AWS
  • Some aspects of the User Interface are quite confusing and activating packages can be a bit convoluted
  • It can be a bit confusing to switch between frameworks for novice users
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IBM
  • APIs integration could be improved.
  • steep learnings for tuning AI models
  • performance lag
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Alternatives Considered
Amazon AWS
Both of these services provide similar functionality and from my experience both are top class services which cover most of your needs. I think ultimately it comes down to what you need each service for. For example Amazon DL AMIs allows for clustering by default meaning I am able to run several clustering algorithms without a problem whereas IBM Watson Studio doesn't provide this functionality. They both provide a wide range of default packages such as Amazon providing caffe-2 and IBM providing sci-kitlearn. My main point is that both are very good services which have very similar functionality, you just need to think about the costs, suitability of features and integration with other services you are using.
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IBM
IBM watsonx.ai is more enterprise oriented providing more options regarding on-premises setup and other compliance issues. Better suited for the corporate world.
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Return on Investment
Amazon AWS
  • Saves a lot of Infra Costs
  • Saves a lot of time in handling environment issues
  • Easy to start a new instance
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IBM
  • We have already met our objectives in creating a supportive environment.
  • This open-source tool increases the financial feasibility of the workflow.
  • High price.
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ScreenShots

IBM watsonx.ai Screenshots

Screenshot of Foundation models available in watsonx.ai. Clients have access to IBM selected open source models from Hugging Face, as well as other third-party models, and a family of IBM-developed foundation models of different sizes and architectures.Screenshot of Prompt Lab in watsonx.ai where AI builders can work with foundation models and build prompts using prompt engineering techniques in watsonx.ai to support a range of Natural Language Processing (NLP) type tasks.Screenshot of Tuning Studio in watsonx.ai where AI builders can tune foundation models with labeled data for better performance and accuracy.Screenshot of Data science toolkit in watsonx.ai where AI builders can build machine learning models automatically with model training, development, visual modeling, and synthetic data generation.