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7 Things to Know About AWS ML: Swami Sivasubramanian

‘Advancements in machine learning, fueled by scientific research, abundance of compute resources and access to data, has … meant that machine learning is going mainstream,’ says Sivasubramanian, vice president of artificial intelligence and machine learning at Amazon Web Services. ‘We see this in our customers’ adoption of the machine learning technology.’

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Industry-Specific AI Services

For developers and increasingly business users, AWS is building AI services to address common horizontal and industry-specific use cases to easily add intelligence to any application without needing ML skills. They include Amazon Textract, Amazon Rekognition, Amazon Lookout for Vision and Amazon Monitron.

“We embed AutoML in these AI services so that customers don’t need to worry about data preparation, feature engineering, algorithm selection, training and tuning, inference and model monitoring,” Sivasubramanian said. ”Instead, they can remain focused on their business outcomes. These services help customers do things like personalize the customer experience, identify and triage anomalies in business metrics, image recognition, automatically extract meaning from documents and more.”

AWS also has built a suite of solutions for the industrial sector that use visual data to improve processes and services that use data from machines for predictive maintenance. In health care, it has purpose-built solutions for transcription, medical text comprehension and Amazon HealthLake, a new HIPAA-eligible service to store, transform, query and analyze petabytes of health data in the cloud.


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