AWS Augmented AI

AWS Augmented AI was launched by Amazon Web Services in 2019. It was developed to address the need for integrating human review into machine learning processes, especially in scenarios requiring high accuracy and reliability. The service aimed to simplify the implementation of human-in-the-loop workflows, allowing businesses to enhance the quality of their AI models by leveraging human input where necessary.

Strengths of AWS Augmented AIAWS Augmented AI include seamless integration with existing AWS services, flexibility in designing human review workflows, and the ability to ensure high accuracy and reliability in AI applications. Weaknesses may involve dependency on AWS infrastructure and potential costs associated with human review processes. Competitors include Google Cloud's AI Platform, IBM Watson, and Microsoft Azure Machine LearningMicrosoft Azure Machine Learning, which also offer solutions for integrating human input into AI workflows.

An AWS Augmented AI expert should have skills in AWS services, particularly SageMaker for building and deploying machine learning models. Proficiency in designing human-in-the-loop workflows and creating custom review tasks is essential. Knowledge of integrating AI with existing systems using APIs and familiarity with data labeling and annotation processes are also important. Expertise in managing IAM roles and permissions for secure access to A2I components is crucial.