Five APAC countries can now access the service
Amazon Web Services (AWS) has launched Amazon Augmented Artificial Intelligence (A2I), a managed service that makes it easy to add human review to machine learning predictions to improve model and application accuracy by continuously identifying and improving low confidence predictions.
Amazon A2I is available in Singapore, Tokyo, Sydney, Seoul and Mumbai. As well as selected North American cities.
AWS states A2I helps developers add human review for model predictions to new or existing applications using reviewers from Mechanical Turk, third party vendors, or their own employees.
Amazon A2I is meant to make it easier for developers to build the human review system, structure the review process, and manage the human review workforce.
For example, developers could use Amazon A2I to quickly spin up and manage a workforce of humans to review and validate the accuracy of machine learning predictions for an application that extracts financial information from scanned mortgage documents or an application that uses image recognition to identify counterfeit items online, so that the quality of results improve over time.
There are no upfront commitments to use Amazon A2I, and users pay only for each review needed.
According to AWS machine learning provides predictions (known as “inferences”) for a variety of use cases, including identifying objects in images, extracting text from scanned documents, or transcribing and understanding spoken language.
In each case, machine learning models provide an inference and a confidence score that expresses how certain the model is in its prediction.
The interplay between machine learning and human reviewers is critical to the success of machine learning systems, but human reviews are challenging and expensive to build and operate at scale, often involving multiple workflow steps, operating custom software to manage human review tasks and results, and recruiting and managing large groups of reviewers.
As a result, developers sometimes spend more time managing the human review process than building the intended application, or they must forego having human reviews, which leads to less confidence in deploying applications that utilise machine learning.
Swami Sivasubramanian, vice president, Amazon Machine Learning, Amazon Web Services said developers can add human review to machine learning applications without the need to build or manage expensive and cumbersome systems for human review.
Amazon A2I provides about 60 pre-built human review workflows for common machine learning tasks (e.g. object detection in images, transcription of speech, and content moderation, etc.) that allow machine learning predictions from Amazon Rekognition and Amazon Textract to be human-reviewed more easily. Developers who build custom machine learning models in Amazon SageMaker (or other on-premises or cloud tools) can set up human review for their specific use case in the Augmented AI console or via its Application Programming Interface (API). After setting a confidence
“We often hear from our customers that Amazon SageMaker helps speed training, tuning, and deploying custom machine learning models, while fully managed services like Amazon Rekognition and Amazon Textract make it easy to build applications that incorporate machine learning without requiring any machine learning expertise,” he said.
“But even with these advancements, our customers still say there are critical use cases where human judgment is required like in law enforcement investigations, or times when human review can be used to resolve the ambiguity in predictions when confidence levels fall below a given threshold for less sensitive use cases, and the current human review process involves a lot of custom effort and cost.”
An example of customer utilising AI is the National Health Service, Business Services Authority (NHS BSA), the United Kingdom’s National Health Service, which provides a range of support services to NHS organisations, NHS contractors, and patients.
Chris Suter head of Cloud Platforms and Innovation at NHS BSA said, as part of their business process services, they process 54 million paper prescriptions and other healthcare documents each month.
“The NHS is investing in the promise of AI to improve the quality of public healthcare across the UK. Human judgment is critical and in fact is often required for decisions involving medical payments,” he said. “Amazon Textract is compelling because it offers AI powered extraction of text and structured data from virtually any document.
We are excited about Amazon Augmented AI because it allows us to take advantage of machine learning while still applying human judgment. That’s a game changer for us.”
Tags: AI & Machine LearningAmazonaugmentedAWSmachine learningNHS
