Amazon AI is a set of artificial intelligence (AI) services that offer deep learning and machine learning to Amazon Web Services (AWS) users.
AWS’s machine learning and artificial intelligence (AI) services help your business meet its needs, whether you’re improving customer experiences, improving productivity, or accelerating innovation. No ML experience is required to implement AWS services for horizontal and industry use cases. In an integrated environment, Amazon SageMaker makes it easy to build, train, and deploy machine learning models quickly.
Over one hundred thousand customers choose AWS Machine Learning over all other cloud platforms, from the largest enterprises to the hottest startups.
Our generation will benefit greatly from artificial intelligence (AI) applied through machine learning (ML), which will address some of humanity’s most challenging issues, enhance human performance, and increase productivity. To foster continued innovation, these technologies need to be used responsibly. With AWS, you can build AI and ML applications responsibly with tools and guidance that are fair, accurate, and easy to use.
By using a conversational, ChatOps interface, the Amazon AI suite can converse with end users via text or voice. It can also understand human languages, convert text into speech, and analyze images to identify faces, places, and objects. Developers can include speech recognition, text-to-speech, image recognition, and machine learning services in their applications without learning algorithms or managing infrastructure.
Specialized AI services for specific business scenarios
The use of AI in business can be a powerful tool for modernizing processes.
Launch solutions in days, not months, with built-in business logic.
With cloud-based and intelligent edge security, you can run responsibly anywhere.
A comprehensive family of customizable cognitive APIs for vision, speech, language, and decision making
AI models with the most comprehensive portfolio of AI capabilities, including OpenAI models, are easily accessible.
Create confidently with the first AI services that achieve human parity in computer vision, speech, and language.
With containers, you can deploy anywhere from the cloud to the edge.
Make your own unique solutions and get started quickly.
An end-to-end platform for building, training, and deploying machine learning models
Choose from Jupyter Notebook, drag-and-drop designer, and automated machine learning tools to develop your project.
Utilize automated and reproducible machine learning workflows to build and deploy models at scale.
With built-in responsibility capabilities, you can understand, protect, and manage data, models, and processes responsibly.
Take advantage of the best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.
Advanced, large-scale AI infrastructures and innovative training tools
Take advantage of large-scale infrastructure with hyper-clusters containing thousands of state-of-the-art GPUs, interconnected with the latest high-bandwidth networks inside every server, to accelerate AI.
The Azure Arc-enabled Kubernetes platform enables hybrid and multi-cloud deployments.
With specialized hardware, such as FPGAs, GPUs, and general-purpose CPUs, you can access the most comprehensive AI hardware portfolio.
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