AI Platforms Comparison: AWS vs Azure vs GCP
Artificial Intelligence (AI) is undoubtedly the future of technology, and choosing the right AI platform can be a game-changer for your business. AWS, Azure, and GCP are three major players when it comes to cloud-based AI platforms, offering features like Machine Learning (ML) frameworks, Natural Language Processing (NLP), and Computer Vision capabilities. In this blog post, we will compare these three platforms, so you can pick the right one for your business needs.
Overview
To start with, here is a brief overview of the three platforms:
- Amazon Web Services (AWS): Market leader with a wide range of AI products.
- Azure: Second-largest cloud provider with comprehensive ML stack.
- Google Cloud Platform (GCP): Strong on R&D and with an easy-to-use AI platform.
Cost
When it comes to AI platform cost, AWS, Azure, and GCP has different pricing strategies. We took a look at the general pricing information, and found that AWS charges $0.0001 per AI-based operation. Meanwhile, Azure has a simpler approach, charging $1.50 per hour for a virtual machine with AI capabilities. Lastly, GCP provides a free trial lasting 12 months or up to $300 in credit. After the free trial ends, the basic plan starts at $0.15 per hour.
Features
All three platforms offer comprehensive AI features, but the depth and breadth of those features differ. Let's take a closer look at their capabilities:
AWS
As the biggest cloud provider in the world, AWS is packed with products which facilitate machine learning and other AI features. They have SageMaker, which offers easy-as-ABC machine learning. They also offer pre-built AI services like Amazon Transcribe for converting audio-to-text, Amazon Comprehend for NLP, and Amazon Rekognition for computer vision.
Azure
Microsoft Azure has a comprehensive ML offering, which includes tools like AutoML, Cognitive Services, and Azure Machine Learning Studio. The Azure platform also supports various machine learning frameworks, including PyTorch, TensorFlow, and Keras. Additionally, Azure also provides cognitive services like Speech-to-text, Text-to-speech, Bing Search, and Image Analysis.
GCP
Google Cloud Platform (GCP) is known for its innovation and ease-of-use, and their AI and ML offerings are no exception. Google offers custom-built hardware to facilitate machine learning, including Tensor Processing Units (TPUs). They also provide easy-to-use tools like AutoML, which helps users build custom models without deep learning knowledge.
Support
When it comes to support, all three providers offer and premium options depending on the use case or enterprise setup.
AWS offers a Knowledge Center with documentation, and they have active online forums as well. Azure has similar documentation to AWS, and Microsoft provides 24/7 phone support to assist whenever needed. GCP also offers documentation, and they have Google Cloud Services experts for technical support.
Conclusion
Choosing an AI platform depends on several factors, including cost, features, and support. Our honest recommendation is to try out each platform using a free trial, then select the most suitable platform for your business needs. AWS, Azure, and GCP have their strengths and weaknesses, so it is essential to select the one that aligns with your business goals.
So if you're looking for a robust and comprehensive AI platform, then AWS is a good choice. For an easy-to-use platform, GCP is worth considering. Lastly, if you're searching for a straightforward and user-friendly platform, Azure should be on your list.
References
- AWS. (2021). Amazon AI. Retrieved from https://aws.amazon.com/machine-learning/
- Azure. (2021). Azure AI. Retrieved from https://azure.microsoft.com/en-us/services/artificial-intelligence/
- GCP. (2021). Google Cloud AI Platform. Retrieved from https://cloud.google.com/ai-platform