Introduction
Artificial Intelligence and Machine Learning are currently at the forefront of technological advancements in computing. To make the development of Machine Learning models more accessible, several cloud service providers offer services that allow developers to build, train, and deploy Machine Learning models using tools such as Google Cloud AI Platform and Amazon's AWS SageMaker. However, with several comparible services to choose from, Flare Compare takes a closer look to make it easier for enterprises to make an informed decision.
Pricing
Pricing is an important criterion for most enterprises to consider while selecting a service provider. Google Cloud AI Platform offers a range of pricing options, including pay-as-you-go computing, training, and storage options that allow you to tailor a plan to suit your specific needs. AWS SageMaker offers a similar range of pricing options; however, the pricing model for both services is quite different.
For example, with Google Cloud AI Platform, you pay for the resources and services you consume on an hourly basis, while with AWS SageMaker, you pay for the specific instance types you use based on a fixed rate. Furthermore, AWS SageMaker also charges for training and deploying models separately from the instance cost, whereas, with Google Cloud AI Platform, the whole cost is consolidated into one bill.
Features
When it comes to features, both services offer a similar range of tools, such as pre-built model architectures, notebooks, real-time model serving, and automated model tuning. However, Google Cloud AI Platform offers some unique features, such as AutoML, which can help you quickly design Machine Learning models even if you don't have a background in Machine Learning. It also offers 'explainable AI', which provides you with insight into how and why decisions are made. However, AWS SageMaker is equipped with features to offer developer's flexibility to build and train across a more extensive range of services such as TensorFlow, Apache MXNet, PyTorch, and XGBoost frameworks.
Scalability
Both Google Cloud AI Platform and AWS SageMaker offer scalable solutions capable of meeting the needs of the largest enterprises around the globe. By leveraging the cloud's scalable infrastructure, you can quickly and efficiently respond to resource demands as they arise.
Conclusion
Both Google Cloud AI Platform and AWS SageMaker offer developers the tools they need to build, train, and deploy Machine Learning models at scale. Which one you choose depends on specific needs and with this comparison, Flare Compare provides businesses with a better understanding of the pay structure, features and scalability benchmarks between the two providers so that an informed decision is realized.